电液比例变量施肥系统参数模型辨识及滑模变结构控制研究
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摘要
电控液压系统以响应速度快、输出功率大、控制精度高的特点,适应大型变量施肥播种机的作业需求,在变量施肥控制系统中得到广泛应用。由于液压伺服系统存在时变参数以及外干扰引起的不确定性,有些参数难以用理论方法确定,而且随着工况的不同和压力流量等主参数的变化,这些参数的值也会发生变化。建立准确描述电液系统动态特性的数学模型是控制系统性能研究的前提和关键,本文提出一种系统参数辨识建模法,该方法以系统的试验输入输出数据为依据,融合参数估计和误差准则建立电液变量系统的数学模型,比以往机理分析建模法更能准确表达系统状态传递关系。针对常规PID控制规律采用线性定常组合方案,难于协调快速性和稳态性之间的矛盾,鲁棒性能欠佳,提出对参数摄动和外部干扰具有自适应能力的变结构控制策略,克服非线性和参数不确定对系统性能造成的不利影响。并针对变结构控制的抖振缺陷提出了模糊控制优化趋近过程,抑制抖振提高系统动态品质和稳态精度。本研究从非线性、时变液压系统参数辨识角度出发,探索基于系统辨识的电液比例变量施肥系统数学模型的途径,并采用具有较强鲁棒性的变结构控制结合智能控制,提高系统的鲁棒性和跟踪特性,进而提高变量施肥播种机的施肥精度。本研究主要完成了以下内容：
1.利用系统辨识法建立电液比例变量施肥系统的数学模型。通过机理分析法,确定系统的最高工作频率,得到M序列的时钟周期Δt与序列长度Np。依据信号发生器产生的辨识输入信号M序列和数据采集仪获取的液压马达转速,选择一种模型类,利用最小二乘法,对系统进行模型参数的辨识,再由最终预报误差准则(FPE),进一步系统阶次。本研究根据系统实际工作状况,分别选择带控制量的自回归模型ARX和带控制量的平均自回归模型ARMAX,通过MATLAB编程获取系统的参数模型,并对比研究两类模型的拟合度,确定ARMAX4431为该电液变量施肥系统的数学模型。
2.研究电液变量施肥系统的滑模变结构控制策略。利用变量施肥控制系统的辨识模型ARMAX4431,转换为状态空间模型,将模型转换为能控标准型,并通过坐标变换法和最优二次型法确定比例切换函数的系数,选择指数趋近律,利用广义滑模和系统模型确定滑模控制策略,实现电液变量施肥系统的滑模变结构控制。利用MATLAB编程对比研究了PID控制和滑模变结构控制(SMC)的阶跃跟踪及正弦跟踪特性。
3.研究电液变量施肥系统的离散滑模变结构控制策略。计算机参与控制的电液变量施肥系统是一个离散时间系统,状态变量是采样周期的时间序列,趋近运动只能形成准滑动模态。利用MATLAB仿真研究等效控制离散变结构和离散指数趋近律变结构控制性能,结果可以看出系统状态在一定宽度的切换带内是形成准滑动模态运动,针对这一缺陷,提出变速指数趋近律削弱准滑动模态的抖振幅度,改善了准滑模稳态阶段的运动性能。考虑指数趋近律在系统稳态时,系统状态在切换带内往复运动,不能稳定于零点；变速指数趋近律渐进稳定于原点,但是在切换初期会产生幅度较大的抖振,综合二者优点研究组合趋近控制律,达到指数趋近的优化控制。
4.研究电液变量施肥系统的模糊滑模变结构控制策略。模糊滑模控制,采用二维模糊滑模控制器,以滑模切换函数s及其导数s的模糊值为输入,通过模糊逻辑推理,根据距离切换面的位置调节切换增益消除抖振,模糊自适应滑模控制,为二输入单输出模糊控制器,取切换函数s(k)及其变化率ds(k)作为输入,fs(k)作为输出,模糊推理符号函数增益,消除抖振。
5.试验研究电液变量施肥系统PID、滑模变结构和模糊滑模变结构跟踪性能和抗干扰性能,系统初始状态运行,采集系统的采样频率1000Hz,记录液压马达转速和控制器输出时域数据文件,试验数据进行处理,分别研究三种控制策略的阶跃跟踪性能和正弦跟踪性能,并对系统稳态误差和抗干扰性能进行对比研究。研究结果与结论如下：
1.通过参数模型辨识法研究电液变量施肥控制系统的数学模型,采用最小二乘法辨识系统模型参数、最终预报误差准则确定系统的结构,得到本系统拟合程度好的模型为ARMAX4431。
2.通过PID控制和滑模变结构控制(SMC)的跟踪特性和抗干扰特性对比研究,结果表明PID控制稳态性能好,但动态调节时间长、抗干扰能力差；SMC控制动态调节快速,鲁棒性好,但存在抖振,影响系统稳态性能。
3.通过电液变量施肥系统离散滑模变结构性能研究,结果表明等效控制动态调节迅速,系统响应有振荡,并存在抖振；离散指数趋近律是准滑模运动,系统存在抖振,不能渐进稳定于零点；变速指数趋近律调节了切换带形状,系统状态渐进稳定于零点,但切换初始阶段存在大幅度抖动；组合控制综合二者优点,实现有限步长内趋近滑模切换面,并渐进稳定零点,削弱了抖振。
4.通过切换增益和指数趋近律模糊滑模变结构控制性能的研究,结果表明模糊自适应滑模趋近律控制系统的跟踪性能更好,控制输出更稳定,系统的抖振更小。
5.通过对PID控制,SMC控制、模糊SMC控制的动态特性、稳态特性和抗干扰特性的试验研究,结果表明模糊SMC在稳态特性和抗干扰特性方面都优于前两种控制,而且较好地抑制了系统抖振。
因此,利用系统参数模型辨识法可以获得更精确的数学模型,变结构控制系统调节快速且无超调,但存在抖振,离散组合控制和模糊指数趋近律控制都可以削弱抖振,但模糊控制指数趋近律在跟踪性能方面优于组合控制,而且抑制抖振效果更优。
Electrically controlled hydraulic system has fast response, large output power and high control precision, suitable for operation demand of large-scale variable fertilizer and seed drill, widely used in variable fertilization control system. Because the hydraulic servo system is uncertainty caused by time-varying parameters and external disturbance, some parameters are difficult to determine with theoretical method, and with the changes of main parameters such as pressure and flow conditions, the value of these parameters will change. The premise and key of control system is to establish an accurate mathematical model to describe the dynamic characteristics of electro-hydraulic system, pose the system identification modeling method, this method based on the input-output data of the system, fusing the parameter estimation and error criterion to establish the mathematical model of electro hydraulic variables system, which lays the foundation for the research of control algorithm. According to the law of conventional PID control which using the linear combination scheme, is difficult to coordinate the contradiction between rapidity and stability, and it's robust performance is poor, the variable structure parameter perturbation and external disturbance with adaptive control strategy is given to overcome the nonlinearity and parameter uncertainty impact on system performance. Aiming at the defects of the chattering variable structure control is proposed to optimize the reaching process fuzzy control, suppress chattering and improve the system dynamic performance and steady-state precision. This study based on the nonlinear, time-varying parameter identification of hydraulic system perspective, and explore the way of system identification of the electro-hydraulic proportional variable fertilization system of mathematical model, and the variable structure robust control with intelligent control, to improve the system robustness and tracking features, and then to improve the variable fertilization seeder fertilization precision.
Research contents:
1. To establish the mathematical model of the electro-hydraulic proportional variable fertilization system based on system identification method. Through mechanism analysis, to determine the maximum working frequency of system clock cycle and the length of the sequence, M sequence. Based on the signal generator of the input signal for identification of M sequence and data acquisition instrument to obtain hydraulic motor speed, choosing a model class and using the least square method for identification of model parameters on the system, then from the final prediction error criterion (FPE), further to determine the optimal control system of electro-hydraulic variable fertilization model. In this study, according to the actual working condition, respectively choose autoregressive model ARX with controlled auto regressive moving average amount of ARMAX with control volume, identified model parameters on the system by least square method through MATLAB programming and the final prediction error (FPE) criterion for model structure identification, and a comparative study of the two model fitting degree, determined that ARMAX4431is the mathematical model of the electro-hydraulic variable fertilization system.
2. Research on electro hydraulic variable fertilization system sliding mode variable structure control strategy. Using the ARMAX4431identification model of control system of variable rate fertilizer applicator, transformed into state space model, the model is converted into the control standard, and through the coordinate transformation method and optimal two quadratic coefficient method to determine the selection of proportion switching function, exponential rate, determine the sliding mode control strategy using the generalized sliding mode and system model, the sliding mode of electro-hydraulic variable fertilization system with variable structure control. Research on PID control and sliding mode variable structure control using MATLAB programming contrast (SMC) step tracking and sinusoidal tracking characteristic; control using MATLAB programming of PID, SMC control step tracking and sinusoidal tracking response characteristics.
3. Discrete sliding mode variable structure control strategy of the electro-hydraulic variable fertilization system. Electro hydraulic variable fertilization system on computer is involved in the control of a discrete time system, the state variable is the time series of the sampling period, the formation of quasi sliding mode. By using MATLAB simulation study on the equivalent discrete variable structure control and discrete exponential reaching law of variable structure control performance, the system state switching in a certain width of the band is the formation of quasi sliding mode motion, to solve this problem, the variable exponent reaching law chattering amplitude of quasi sliding mode is mentioned to improve the motion performance of quasi sliding mode state stage. Considering the exponential reaching law in the state system, the system state in the reciprocating motion in band switching, can not be stable at zero; variable exponent reaching law asymptotically stable at the origin, but in early switching may produce buffeting larger amplitude, integrated two advantages of combined reaching control law, to optimize the control index approach.
4. Fuzzy sliding mode of the electro-hydraulic variable fertilization system variable structure control strategy. Fuzzy sliding mode control, which use the two-dimensional fuzzy sliding mode controller, has input from the fuzzy sliding mode switching function5and its derivative values s(k), by the fuzzy logic reasoning, according to the position of the switching surface distance adjusting switch gain to eliminate the chattering, adaptive fuzzy sliding mode control, two input single output fuzzy controller, the switching function s(k) and its change rate ds(k) as input, the output fs(k) fuzzy reasoning, the sign function gain, eliminate chattering.
5. Experimental study on electro hydraulic system of variable rate fertilizer PID, sliding mode variable structure and fuzzy sliding mode variable structure tracking performance and anti-jamming performance, the initial state of system operation, acquisition system sampling frequency of1000Hz, record the hydraulic motor speed and the controller output time domain data files, test data for processing, respectively, of three kinds of control strategy for step tracking performance and sinusoidal tracking performance, and compare the system steady-state error and anti disturbance performance.
Results and conclusion:
1. Through mathematical model parameter identification model of electro-hydraulic control system of variable rate fertilizer applicator, parameters, using least squares identification system model to determine the final prediction error criterion system structure, model fitting degree of the system for ARMAX4431.
2. Through the contrast research of tracking performance and disturbance performance of PID control and SMC control, the result showed that PID control had better steady-state characteristics but long dynamically adjust time and poor disturbance performance; which SMC control had less dynamically adjust time and better robustness but system steady-state characteristics was impacted by chattering.
3. Through the research of the equivalent control, exponential reaching law, variable exponent reaching law and the combination control of discrete sliding mode variable structure performance, results show that the equivalent control dynamically adjust quickly, the system response is oscillatory, and the presence of buffeting; discrete exponential reaching law is quasi sliding mode, system chattering, cannot be asymptotically stable zero; variable exponent reaching rate adjustment switch with shape, the state of the system is asymptotically stable at zero, but the initial stage of the switchover in large amplitude jitter; combined control integrated two advantages, realization of reaching sliding cutting surface finite step, and asymptotic stability of zero, chattering.
4. The switching gain and index reaching study on fuzzy sliding mode variable structure control performance, the results show that the fuzzy adaptive sliding mode reaching law control system better tracking performance, control more stable output, buffeting smaller system.
5. Based on the experimental study of PID,SMC,FSMC control, dynamic characteristics and steady-state characteristics of the anti interference characteristics, the results show that the fuzzy SMC control is better than that of the steady state characteristics and anti-interference characteristics before two, but also suppress chattering.
Therefore, the use of system model parameter identification method can obtain more accurate mathematical model of variable structure control system to adjust quickly and without overshoot, but there are chattering, discrete combination control and fuzzy index reaching rate control can weaken chattering, but fuzzy control index reaching rate due to the combination control in tracking performance, and restrain the chattering effect is better.
1.利用系统辨识法建立电液比例变量施肥系统的数学模型。通过机理分析法,确定系统的最高工作频率,得到M序列的时钟周期Δt与序列长度Np。依据信号发生器产生的辨识输入信号M序列和数据采集仪获取的液压马达转速,选择一种模型类,利用最小二乘法,对系统进行模型参数的辨识,再由最终预报误差准则(FPE),进一步系统阶次。本研究根据系统实际工作状况,分别选择带控制量的自回归模型ARX和带控制量的平均自回归模型ARMAX,通过MATLAB编程获取系统的参数模型,并对比研究两类模型的拟合度,确定ARMAX4431为该电液变量施肥系统的数学模型。
2.研究电液变量施肥系统的滑模变结构控制策略。利用变量施肥控制系统的辨识模型ARMAX4431,转换为状态空间模型,将模型转换为能控标准型,并通过坐标变换法和最优二次型法确定比例切换函数的系数,选择指数趋近律,利用广义滑模和系统模型确定滑模控制策略,实现电液变量施肥系统的滑模变结构控制。利用MATLAB编程对比研究了PID控制和滑模变结构控制(SMC)的阶跃跟踪及正弦跟踪特性。
3.研究电液变量施肥系统的离散滑模变结构控制策略。计算机参与控制的电液变量施肥系统是一个离散时间系统,状态变量是采样周期的时间序列,趋近运动只能形成准滑动模态。利用MATLAB仿真研究等效控制离散变结构和离散指数趋近律变结构控制性能,结果可以看出系统状态在一定宽度的切换带内是形成准滑动模态运动,针对这一缺陷,提出变速指数趋近律削弱准滑动模态的抖振幅度,改善了准滑模稳态阶段的运动性能。考虑指数趋近律在系统稳态时,系统状态在切换带内往复运动,不能稳定于零点；变速指数趋近律渐进稳定于原点,但是在切换初期会产生幅度较大的抖振,综合二者优点研究组合趋近控制律,达到指数趋近的优化控制。
4.研究电液变量施肥系统的模糊滑模变结构控制策略。模糊滑模控制,采用二维模糊滑模控制器,以滑模切换函数s及其导数s的模糊值为输入,通过模糊逻辑推理,根据距离切换面的位置调节切换增益消除抖振,模糊自适应滑模控制,为二输入单输出模糊控制器,取切换函数s(k)及其变化率ds(k)作为输入,fs(k)作为输出,模糊推理符号函数增益,消除抖振。
5.试验研究电液变量施肥系统PID、滑模变结构和模糊滑模变结构跟踪性能和抗干扰性能,系统初始状态运行,采集系统的采样频率1000Hz,记录液压马达转速和控制器输出时域数据文件,试验数据进行处理,分别研究三种控制策略的阶跃跟踪性能和正弦跟踪性能,并对系统稳态误差和抗干扰性能进行对比研究。研究结果与结论如下：
1.通过参数模型辨识法研究电液变量施肥控制系统的数学模型,采用最小二乘法辨识系统模型参数、最终预报误差准则确定系统的结构,得到本系统拟合程度好的模型为ARMAX4431。
2.通过PID控制和滑模变结构控制(SMC)的跟踪特性和抗干扰特性对比研究,结果表明PID控制稳态性能好,但动态调节时间长、抗干扰能力差；SMC控制动态调节快速,鲁棒性好,但存在抖振,影响系统稳态性能。
3.通过电液变量施肥系统离散滑模变结构性能研究,结果表明等效控制动态调节迅速,系统响应有振荡,并存在抖振；离散指数趋近律是准滑模运动,系统存在抖振,不能渐进稳定于零点；变速指数趋近律调节了切换带形状,系统状态渐进稳定于零点,但切换初始阶段存在大幅度抖动；组合控制综合二者优点,实现有限步长内趋近滑模切换面,并渐进稳定零点,削弱了抖振。
4.通过切换增益和指数趋近律模糊滑模变结构控制性能的研究,结果表明模糊自适应滑模趋近律控制系统的跟踪性能更好,控制输出更稳定,系统的抖振更小。
5.通过对PID控制,SMC控制、模糊SMC控制的动态特性、稳态特性和抗干扰特性的试验研究,结果表明模糊SMC在稳态特性和抗干扰特性方面都优于前两种控制,而且较好地抑制了系统抖振。
因此,利用系统参数模型辨识法可以获得更精确的数学模型,变结构控制系统调节快速且无超调,但存在抖振,离散组合控制和模糊指数趋近律控制都可以削弱抖振,但模糊控制指数趋近律在跟踪性能方面优于组合控制,而且抑制抖振效果更优。
Electrically controlled hydraulic system has fast response, large output power and high control precision, suitable for operation demand of large-scale variable fertilizer and seed drill, widely used in variable fertilization control system. Because the hydraulic servo system is uncertainty caused by time-varying parameters and external disturbance, some parameters are difficult to determine with theoretical method, and with the changes of main parameters such as pressure and flow conditions, the value of these parameters will change. The premise and key of control system is to establish an accurate mathematical model to describe the dynamic characteristics of electro-hydraulic system, pose the system identification modeling method, this method based on the input-output data of the system, fusing the parameter estimation and error criterion to establish the mathematical model of electro hydraulic variables system, which lays the foundation for the research of control algorithm. According to the law of conventional PID control which using the linear combination scheme, is difficult to coordinate the contradiction between rapidity and stability, and it's robust performance is poor, the variable structure parameter perturbation and external disturbance with adaptive control strategy is given to overcome the nonlinearity and parameter uncertainty impact on system performance. Aiming at the defects of the chattering variable structure control is proposed to optimize the reaching process fuzzy control, suppress chattering and improve the system dynamic performance and steady-state precision. This study based on the nonlinear, time-varying parameter identification of hydraulic system perspective, and explore the way of system identification of the electro-hydraulic proportional variable fertilization system of mathematical model, and the variable structure robust control with intelligent control, to improve the system robustness and tracking features, and then to improve the variable fertilization seeder fertilization precision.
Research contents:
1. To establish the mathematical model of the electro-hydraulic proportional variable fertilization system based on system identification method. Through mechanism analysis, to determine the maximum working frequency of system clock cycle and the length of the sequence, M sequence. Based on the signal generator of the input signal for identification of M sequence and data acquisition instrument to obtain hydraulic motor speed, choosing a model class and using the least square method for identification of model parameters on the system, then from the final prediction error criterion (FPE), further to determine the optimal control system of electro-hydraulic variable fertilization model. In this study, according to the actual working condition, respectively choose autoregressive model ARX with controlled auto regressive moving average amount of ARMAX with control volume, identified model parameters on the system by least square method through MATLAB programming and the final prediction error (FPE) criterion for model structure identification, and a comparative study of the two model fitting degree, determined that ARMAX4431is the mathematical model of the electro-hydraulic variable fertilization system.
2. Research on electro hydraulic variable fertilization system sliding mode variable structure control strategy. Using the ARMAX4431identification model of control system of variable rate fertilizer applicator, transformed into state space model, the model is converted into the control standard, and through the coordinate transformation method and optimal two quadratic coefficient method to determine the selection of proportion switching function, exponential rate, determine the sliding mode control strategy using the generalized sliding mode and system model, the sliding mode of electro-hydraulic variable fertilization system with variable structure control. Research on PID control and sliding mode variable structure control using MATLAB programming contrast (SMC) step tracking and sinusoidal tracking characteristic; control using MATLAB programming of PID, SMC control step tracking and sinusoidal tracking response characteristics.
3. Discrete sliding mode variable structure control strategy of the electro-hydraulic variable fertilization system. Electro hydraulic variable fertilization system on computer is involved in the control of a discrete time system, the state variable is the time series of the sampling period, the formation of quasi sliding mode. By using MATLAB simulation study on the equivalent discrete variable structure control and discrete exponential reaching law of variable structure control performance, the system state switching in a certain width of the band is the formation of quasi sliding mode motion, to solve this problem, the variable exponent reaching law chattering amplitude of quasi sliding mode is mentioned to improve the motion performance of quasi sliding mode state stage. Considering the exponential reaching law in the state system, the system state in the reciprocating motion in band switching, can not be stable at zero; variable exponent reaching law asymptotically stable at the origin, but in early switching may produce buffeting larger amplitude, integrated two advantages of combined reaching control law, to optimize the control index approach.
4. Fuzzy sliding mode of the electro-hydraulic variable fertilization system variable structure control strategy. Fuzzy sliding mode control, which use the two-dimensional fuzzy sliding mode controller, has input from the fuzzy sliding mode switching function5and its derivative values s(k), by the fuzzy logic reasoning, according to the position of the switching surface distance adjusting switch gain to eliminate the chattering, adaptive fuzzy sliding mode control, two input single output fuzzy controller, the switching function s(k) and its change rate ds(k) as input, the output fs(k) fuzzy reasoning, the sign function gain, eliminate chattering.
5. Experimental study on electro hydraulic system of variable rate fertilizer PID, sliding mode variable structure and fuzzy sliding mode variable structure tracking performance and anti-jamming performance, the initial state of system operation, acquisition system sampling frequency of1000Hz, record the hydraulic motor speed and the controller output time domain data files, test data for processing, respectively, of three kinds of control strategy for step tracking performance and sinusoidal tracking performance, and compare the system steady-state error and anti disturbance performance.
Results and conclusion:
1. Through mathematical model parameter identification model of electro-hydraulic control system of variable rate fertilizer applicator, parameters, using least squares identification system model to determine the final prediction error criterion system structure, model fitting degree of the system for ARMAX4431.
2. Through the contrast research of tracking performance and disturbance performance of PID control and SMC control, the result showed that PID control had better steady-state characteristics but long dynamically adjust time and poor disturbance performance; which SMC control had less dynamically adjust time and better robustness but system steady-state characteristics was impacted by chattering.
3. Through the research of the equivalent control, exponential reaching law, variable exponent reaching law and the combination control of discrete sliding mode variable structure performance, results show that the equivalent control dynamically adjust quickly, the system response is oscillatory, and the presence of buffeting; discrete exponential reaching law is quasi sliding mode, system chattering, cannot be asymptotically stable zero; variable exponent reaching rate adjustment switch with shape, the state of the system is asymptotically stable at zero, but the initial stage of the switchover in large amplitude jitter; combined control integrated two advantages, realization of reaching sliding cutting surface finite step, and asymptotic stability of zero, chattering.
4. The switching gain and index reaching study on fuzzy sliding mode variable structure control performance, the results show that the fuzzy adaptive sliding mode reaching law control system better tracking performance, control more stable output, buffeting smaller system.
5. Based on the experimental study of PID,SMC,FSMC control, dynamic characteristics and steady-state characteristics of the anti interference characteristics, the results show that the fuzzy SMC control is better than that of the steady state characteristics and anti-interference characteristics before two, but also suppress chattering.
Therefore, the use of system model parameter identification method can obtain more accurate mathematical model of variable structure control system to adjust quickly and without overshoot, but there are chattering, discrete combination control and fuzzy index reaching rate control can weaken chattering, but fuzzy control index reaching rate due to the combination control in tracking performance, and restrain the chattering effect is better.
引文
1.靳双珍,刘国顺,闫新甫等.2010.我国发展精准农业的必要性与应用前景.浙江农业科学,(2)：414-416
2.吴才聪.2003.精确农业变量施肥决策研究与技术经济分析.吉林大学,博士学位论文
3.耿向宇.2007.基于GPS\GPRS的变量施肥机控制系统研究.上海交通大学,硕士学位论文
4.邵俊鹏,王仲文,李建英等.2010.电液位置伺服系统的规则自校正模糊PID控制器[J].中南大学学报(自然科学版),41(3)：960-965.
5.白寒,王庆九,徐振等.2009.阀控非对称缸系统多级滑模鲁棒自适应控制[J].农业机械学报,40(10)：193-198.
6. G.Zames.1998.Adaptive control:Towards a complexity-based general theory. automation,34(10):1161-1167
7. Z.Jiao,P.Chen,Q.Hu,S.Wang.2003.Adaptive vibration active control of fluid pressure pulsations proceedings of the Institution of mechanical engineers.Part Ⅰ:Journal of systems and control engineering,217(4):311-318
8. B.Yao,F.P.Bu,J.Reedy.2000.Adaptive robust motion control of single-rod hydraulic actuators:Theory and experiments.ieee/asme transactions on mechatronics,(2):759-763
9. B.Yao.1997.High performance adaptive robust control of nonlinear systems:a general framework and new schemes.Proceedings of the 36th ieee conference on decision and control, (3):2489-2494
10. G.Kreisselmeier,B.D.O.Anderson.1986.Robust model reference adaptive control.Ieee transations on automatic control,31(2):127-133
11. D.J.Sandoz,M.J.Desforges,B.Lennox,et al.2000.Algorithms for industrial model predictive control. Computing & control encineiering journal,11 (3):125-134
12. B.L.Shields,E.J.Barth,M.Goldfarb.2006.Predictive control for time-delayed switching control systems. Transactions of the asme,128(4):999-1004
13. Chen Wenhua,Hu Xiaobing.2004.Model predictive control of linear systems with nonlinear terminal control.International journal of robust and nonlinear control,14(4):327-339
14.乔丰立,唐兵,卢堃等.2005.比例控制径向柱塞泵性能预测.机械工程学报,41(10)：66-70
15. A.L.D.Franco,H.Bourles,E.R.De Pieri,et al.2006.Robust nonlinear control associating robust feedback linearization and h infinity control.Ieee transactions on automatic control,51 (7):1200-1207
16. Martinez-Salamero, L., Calvente, J., Romero, A.2006.An H∞ control strategy for switching converters in sliding-mode current control. IEEE Transactions on power electronics,21(2):553-556
17. Piao Fengxian,Zhang Qingling,Ma Xiuzhen.2006.Robust h infinity control for uncertain descriptor systems with state and control delay.Journal of systems engineering and electronics,17(3):571-575
18. Shao Keyong,Zhao Wanchun,Zhou Luanjie,et al.2004.Robust H-infinity control for linear uncertainty systems based on PI control laws. Institute of electrical and electronics engineers inc:Proceedings of 2004 international conference on machine learning and cybernetics,1:648-652
19. Zhang Ke.2006.A study on intelligent control for hybrid actuator. Lecture notes in computer Science,3972:1116-1123.
20. Ariuna,Damba,Shigeyoshi,et al.2004.Intelligent control in dynamic system 2004 ieee conference on robotics,automation and mechatronics. Singapore.institute of electrical and electronics engineers inc,2:644-648
21.李静,李晶瑜.2011.中国粮食生产的化肥利用效率及决定因素研究.农业现代化研究,32(5)：565-569
22.王祖力,肖海峰.2008.化肥施用对粮食产量增长的作用分析.农业经济问题,(8)：65-68
23.房丽萍,孟军化.2013.肥施用对中国粮食产量的贡献率分析.中国农学通报,29(17)：156-160
24.张福锁,王激清,张卫峰等.2008.中国主要粮食作物肥料利用率现状与提高途径.土壤学报,45(5)：915-924
25.张小超,胡小安,苑严伟等.2011.精准农业智能变量作业装备研究开发.农业工程,1(3)：26-32
26. M.L.Stone,J.B.Solie,W.R.Raun,et al.1996.Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Ransactions of asae,39(6):1623-1631
27.张维理,田哲旭,张宁等.我国北方农用氮肥造成地下水硝酸盐污染的调查.植物营养与肥料学报,1(2)：80-87
28.李军,黄敬峰,程家安.2003.我国化肥施用量及其可能污染的时空分布特征.生态环境,12(2)：145-149
29.孟志军.2007.基于处方图的变量施肥作业系统关键技术研究.中国农业大学,博士学位论文
30.周惠秋.2005.东北地区粮食综合生产能力研究.北京：中国农业出版社
31.毛惠忠.2005.新阶段中国粮食问题研究.北京：中国农业出版
32.李彦明.2005.变量施肥机研究技术报告.上海：上海交通大学
33. Precision agriculture in the 21st century.Geospatial and information technologies in crop management.national research council
34.段洁利,李君,卢玉华,.2011.变量施肥机械研究现状与发展对策.农机化研究,5：245-248
35. GL.Tian.1990.Dynamic smdy on typical area of huang he basin with remote sensing(in Chinese).Beijing:Science Press
36.薛利红,杨林章,李刚华.2004.遥感技术在精确施肥管理中的应用进展.农业工程学报,20(4)：224-226
37.赵军.2004.变量技术及其在农业机械中的应用.现代化农业,(12)：25
38.赵登峰,张立新,范子胜.2011.变量施肥装备的研究现状及展望.新疆农机化,4：29-34
39. Mark Morgan, Dan Ess.1997.The Precision-Farming Guide for Agriculturists. USA:Deere & Company
40.曲桂宝,田耘.2005.变量施肥的实现过程及其发展前景.中国农机化,4：50-54
41. P.A.S.Radite,M.Umeda,M.Iida,et al.2000.Variable rate fertilizer applicator for paddy field.Usa:asae annual international meeting
42.邓在京.2004.日本精准农业研究与开发现状.农机化研究,(9)：4-6
43.张晓辉,李汝萃.2002.法国的精确农业研究及应用现状.农机化研究,(1)：12-17
44. Litchman,Gennadi,Ivanovich.2002关于精确农业发展的研讨报告.中国：中国吉林大学
45. AgGPSTM124/132 OperationManua,1999. Revision.A TrimbleNavigation Limited
46.张书慧,马成林,吴才聪,等.2003.一种精确农业自动变量施肥技术及其实施.农业工程学报,19(1)：129-131
47.张书慧,马成林,杜巧玲.2004.精确农业自动变量施肥机控制系统设计与实现.农业工程学报,20(1)：113-116
48.吴才聪,马成林,张书慧,等.2003精确农业倾斜网格划分及其应用.农业工程学报,19(1)：137-141
49.张书慧,齐江涛,廖宗建,等.2010.基于CPLD的变量施肥控制系统开发与应用.农业工程学报26(8)：200-204
50.张林焕,张书慧,王薇.2010.基于PLC的液压无级调速变量施肥控制系统的研究.农业网络信息,7：9-13
51.马成林,吴才聪,张书慧.2004.基于数据包络分析和人工神经网络的变量施肥决策方法研究.农业工程学报,20(2)：152-155
52.付卫强,孟志军,黄文倩,等.2008.基于CAN总线的变量施肥控制系统.农业工程学报,24(Supp.2)：127-132
53.陈立平,黄文倩.2008.基于CAN总线的变量施肥控制器设计.农业机械学报,39(8)：101-104
54.邵利敏,王秀,牛晓.2007.基于PLC的变量施肥控制系统设计与试验颖.农业机械学报,38(11)：84-87
55.牛晓颖.2005.精准农业变量施肥技术及其实施系统的研究.河北农业大学,硕士学位论文
56.胡玲燕,王秀,韩应征.2010.光传感器变量施肥控制系统开发.农机化研究,11：91-94
57.王秀,赵春江,孟志军等.2004.精准变量施肥机的研制与试验.农业工程学报,20(5)：114-117
58.孟志军,赵春江,刘卉.2009.基于处方图的变量施肥作业系统设计与实现.江苏大学学报(自然科学版),30(4)：338-342
59.潘世强,曲桂宝,孙振中,等.2009.2BFJ-6型变量施肥精密播种机的研制.中国农机化,(6)：66-69,76
60.伟利国,张小超,苑严伟等.2012.2F-6-BP1型变量配肥施肥机研制与试验.农业工程学报,28(7)：14-18.
61.张辉,李树君,张小超,等.2010.变量施肥电液比例控制系统的设计与实现.农业工程学报,26(Supp.2)：218-222
62.刘阳春,张小超,伟利国等.2010.一种变量施肥技术的实现及其台架试验.农业机械学报,41(9)：159-162
63.张小超,胡小安,苑严伟等.2011.精准农业智能变量作业装备研究开发.农业工程,1(3)：26-32
64.梁春英,王熙,赵军.2003.变量施肥播种机电控液压驱动控制系统设计.黑龙江八一农垦大学学报,15(3)：47-50
65.梁春英,衣淑娟,王熙.2010.变量施肥控制系统PID控制策略研究.农业机械学报,41(7)：157-162
66.王新忠,王熙,汪春,等.2008.黑龙江垦区大豆变量施肥播种应用试验.农业工程学报,24(5)：143-146
67.赵军,王熙,庄卫东.2006.基于GPS的变量施肥播种机的试验研究.农机化研究,12：154-156
68.李爱传,王熙,汪志强.2009.电液驱动式变量施肥闭环控制系统研究.中国农学通报,25(7)：272-275
69.刘成良苑进.2010.基于ARM和DSP的双变量施肥控制系统设计与试验.农业机械学报51(Supp)：233-238
70.耿向宁,李彦明,苗玉彬等.2007.基于GPRS的变量施肥机系统研究研究.农业工程学报,23(11)：164-167
71.古玉雪,苑进,刘成良.2011.基于模糊系统的开度转速双变量施肥控制序列生成方法.农业工程学报,27(11)：134-139
72.李加念,洪添胜,冯瑞珏等.2012.基于脉宽调制的文丘里变量施肥装置设计与试验.农业工程学报,28(8)：105-110
73.张国梁,李成华,杨宇.2008.自动变量播种机控制系统设计.沈阳农业大学学报,39(6)：704-707
74.赵春超,赵克定,邵鸿德等.2003.基于Elman网络的液压系统辨识.机床与液压,(1)：129-130
75.阚超.2007.电液伺服与比例压力控制系统辨识与特性比较研究.燕山大学,博十学位论文
76.李鹏波.2010.系统辨识.北京：中国水利水电出版社
77.王荣.2007.双液压马达同步驱动控制与系统辨识研究.哈尔滨工业大学,硕十学位论文
78. L.A.Zadech
79.倪博溢,萧德云.2006MATLAB环境下的系统辨识仿真工具箱.系统仿真学报,18(6)：1493-1496
80.孙书立,胡守印.2005.MATLAB在热工系统辨识中的应用.科学技术与工程,5(5)：309-312
81.干琳,马平.2001.系统辨识方法综述[J].电力情报,(4)：63-66
82.方崇智,萧德云.1988.过程辨识.北京：清华大学出版社
83.莫建林,王伟,许晓鸣等.2002.系统辨识中的闭环问题.控制理论与应用,19(1)：9-14
84.王益群,王海芳,高英杰等.2004.基于神经网络的轧机液压AGC系统自适应辨识.中国机械工程,15(5)：450-453
85.王文韬,李成利,田军.2005.基于一种改进BP神经网络的一类非线性系统辨识方法.青岛科技大学学报(自然科学版),26(1)：85-88
86.姜春福,余跃庆,刘迎春.2004.冗余度机器人运动模型的神经网络辨识及实现.控制理论与应用21(3)：373-378
87.李保奎.2002.神经网络辨识方法及其在轧钢控制中的应用.北京理工大学学报,22(3)：311-314
88. S.V.Huffel,J.Vandwalle.1985.The use of total least squares techniques for identification and parameter estimation.Ifac.Identification and system Parameter Estimation,1985:1167-1172
89. Q.M.zhu,S.A.Billings.1993.Parameter estimation for stochastic nonlinear rational models. Int.j. control, 57(7):309-333'
90.庞中华,崔红.2009.系统辨识与自适应控伟MATLAB仿真.北京：北京航空航天大学出版社
91.胡干耀.2003.现代控制理论：系统辨识.北京：北京航空航天大学出版社
92. Shen ShuXiong,Zhao Zhou.2003.Neural filtering of colored noise based on kalman filter structure. Instrumentation and measurement,IEEE Transactions,52(3):742-747
93.李鹏波,胡德文,张纪阳.2010.系统辨识.北京：中国水利水电出版社
94.韩江,屈胜利,王效杰.2005.伺服系统辨识的仿真与实现.航空计算技术,35(4)：50-52
95.陈海龙,李宏.2005.基于MATLAB的伪随机序列的产生和分析.计算机仿真,22(5)：98-100
96.吴晓燕,周延延,张双选.2003.一种用于模型结构辨识的新方法.空军工程大学学报(自然科学版),4(4)：77-80
97. L.Ljung.2002.system identification theory for the user (second edition)北京：清华大学出版社
98.王秀峰.2004.系统建模与辨识.北京：电子工业出版社
99.杨承志.2003.系统辨识与自适应控制.重庆：重庆大学出版社
100.于刚.2007.伺服阀控液压马达系统的辨识与控制研究.山东大学,硕士学位论文
101. H.Unbehauen.1982.Identification of dynamic systems. Second iasted intenetional symposium, Modeling identification and robotics
102. K.Diekmann,H.Unbehanen.1982.Tests for determining the order of canonical models of multivariable systems.Ifacs symposium on theory and application of digital control,13:1-7
103. H.Akaika.1987.Faetor analysis and aic.Psychometrik,(52):97-104
104.鲁万波,余竞.2003.用AIC准则识别最佳因子分析模型.成都大学学报(自然科学版),22(2)：28-32
105.H.Akaika.1972.Use of an information.theoretic for statistical model identification.Hawaii:proc.of 5th hawaii int,conf on system Science
106.方崇智,萧德云.1988.过程辨识.北京：清华大学出版社
107. V.S.Emelyanov,A.L.Fedotova.1962.Design of a static tracking systems with variable structure. Automation and remote contro,(10):1223-1235
108. V.S.Emelyanov,B.P.Matic,N.E.Kostyleva.1973.A universal uniform control system with variable structure.inst.Contr.system,(1):5-10
109. V.I.Utkin.1965.On compensation of the forced component in the motion of control systems with variable structure.Eng.Cybem,(4):167-171
110. V.I.Utkin,1983.vss:Vresent and future.Automation and remote control,(44):1105-1120
111.高为炳.1990.变结构控制理论基础.北京：中国科学技术出版社
112.高为炳.1996.变结构控制的理论及设计方法.北京：科学出版社
113.王丰尧.1995.滑模变结构控制.北京：机械工业出版社
114.高为炳.1995.离散时间系统的变结构控制.自动化学报,21(2)：154-160
115.翟长连,吴智铭.2000.一种离散时间系统的变结构控制方法.上海交通大学学报,1.14(5)：719-722
116.胡云安,顾文锦.1995.模糊变结构控制及其应用.航天控制,(4)：54-59
117.David Munoz,Daniel Sbarbaro.2000.An adaptive sliding-mode controller for discrete nonlinear systems.IEEE Transactions on industrial electronics,1.47(3):547-581
118. C.Canudas de Wit,H.Olsson,K.J.Astrom,et al.1995.A new model for control of systems with friction.IEEE Transactions on automatic control,1.40(3):419-424
119.张春雷.2012.基于变结构方法的倒立摆控制研究.三峡大学,硕士学位论文
120.解磊.2006.基于变结构控制策略的转台控制技术研究.南京航空航天大学,硕士学位论文
121.马亚丽.2010.基于滑模变控制理论的电液位置伺服控制方法研究.太原理工大学,硕士学位论文
122.K.D.Young,V.I.Utkin,U.Ozguner.1999.A control engineer's guide to sliding mode control.IEEE Transactions on control systems technology,7(3):328-342
123.S.C.Y.Chung,C.L.Lin.1999.A transformed lure problem for sliding mode control and chattering reduction.IEEE Transactions on automatic control,44(3):563-568
124.K.Jiang,J.G.Zhang,Z.M.Chen.2002.A new approach for the sliding mode control based on fuzzyreaching law. Intelligent control and automation,proceedings of the 4th world congress on,(1):656-660
125.胡云安,顾文锦.1995.模糊变结构控制及其应用.航天控制,(4)：54-59
126.H.Yanada,H.Ohnishi.1999.Frequency-shaped sliding mode control of an electrohydraulic servomotor. Journal of systems and control and dynamics21(1):441-448
127.A.Kawamura,H.Itoh,K.Sakamoto.1994.Chattering reduction of disturbance observer based sliding mode control.IEEE Transactions on industry applications,30(2):456-461
128.C.L.Hwang.1996.Sliding mode control using time-varying switching gain and boundary layer for electrohydraulic position and differential pressure contro.IEEE Proceedings-control theoryand applications,143(4):325-332
129.Y.Konno,H.Hashmoto.1992.Design of sliding mode dynamics in frequency domain.IEEE Workshop on variable structure and lyapunov control of uncertain dynamical Systems,1992:120-125
130.靳宝全.2010.电液位置伺服控制系统的模糊滑模控制方法研究.太原理工大学,博士学位论文
131. W.B.Gao,Y.F.Wang.1995.Discrete-time variable structure control systems.IEEE Transaction on industrial electronics,42(2):117-122
132.K.Furuta.1990.Sliding mode control of a discrete system.Systems & control leters,14(2):145-152
133.高为炳,1995.离散时间系统的变结构控制.自动化学报,21(2)：154-160
134.翟长连,吴智铭.2000.一种离散时间系统的变结构控制方法.上海交通大学学报,214(5)：719-722
135.姚琼荟,宋立忠,温洪.2000.离散变结构控制系统的比例—等速—变速控制.控制与决 策,15(3)：229-332
136.翟长连,吴智铭.2000.不确定离散时间系统的变结构控制设计.自动化学报,26(2)：184-191
137.宋立忠,陈少吕.2004.滑模预测离散变结构控制.控制理论与应用,21(5)：826-829
138. Y.P.Chen,J.L.Chang,.S.R.Chu.1999.Pc-based sliding-mode control applied to parallel-type double inverted pendulum system.Mechatronics,9:553-564
139. David Munoz,Daniel Sbarbaro.2000.An adaptive sliding-mode controller for discrete nonlinear systems.IEEE Transactions on industrial electronics,47(3):547-581
140.胡云安,顾文锦.1995.模糊变结构控制及其应用.航天控制,(4)：54-59
141. Q.P.Ha,Q.H.Nguyen,D.C.Rye.2001.Fuzzy sliding-mode controller withapplications. IEEE Transactions on industrial electronics48(1):38-46
142. Meliksah Ertugrul,Okyay Kaynak.1998.Neural computation of the equivalent control in sliding mode for robot trajectory control applications.Proceedings of the 1998 ieee international conference on robotic & automation,1998:2042-2047
143. Milo savljevie.1985.General conditions for the existence of a quasi-sliding mode on the switching byperplane in discrete variable structure system.Automation and remote control,46(3):307-314
144. Y.Dot,R.G.Holf.1980. Microprocessor based sliding mode controller for dc motor drives. Cincinnati: presented at the Industrial Application Society Annual Meeting
145. S.Z.Sapturk,Y.Istefanopulos,Kaynak O.1987.On the stability of discrete-time sliding mode control systems. IEEE Transautom at contr,32 (10):930-932
146.高为炳.1998.变结构控制的理论及设计方法.北京：科学出版社
147.刘金琨.2005.滑模变结构MATLAB仿真.北京；清华大学出版社
148.杨勇,文丹,罗安等.2006.基于多目标优化的模糊滑模变结构控制及应用.中南大学学报(自然科学版)37(6)：1149-1154
149.刘金琨.2005.滑模变结构控制MATLAB仿真.北京：清华大学出版社
150.曾光奇,胡均安,王东等.2006.模糊控制理论与工程应用.武汉：华中科技大学出版社
151.陈志梅,王贞艳,张井冈.2012.滑模变结构控制理论及应用.北京：电子工业出版社
152.孙成.2008.变量施肥机控制系统的研究,吉林农业大学,硕士论文
153.曲桂宝.2006.变量施肥机的试验研究.吉林农业大学,硕士论文
154.赵登峰.2012.棉花变量施肥关键技术及装置研究.石河子大学,硕士论文
155.李红岩.2006.精准农业田间变量施肥控制系统研究.西安科技大学,硕士论文
156.王熙.2006.精准农业大豆变量施肥控制技术研究.黑龙江八一农垦大学,博士论文
157.刘阔,郭大猛,刘杰,等.2009.液压挖掘机自适应模糊滑模控制的研究与仿真.东北大学学报(自然科学版),30(11)：1649-1652
158.席爱民.2008.模糊控制技术.西安：西安电子科技大学出版社
159.黄文芳.2011.农业化肥污染的政策成因及对策分析.生态环境学,20(1)：193-198.
160.靳双珍,刘国顺,闫新甫,等.2010.我国发展精准农业的必要性与应用前景,浙江农业科学,(2)：414-416.
161.周智艳,罗锡文,臧英.2010.水稻-稻田环境系统重要信息快速获取技术研究进展.中国科学：信息科学,40(Supp)：38-53.
162.杨玉建,朱建华.尚明华,等.2006.精准农业关键技术及其发展前景.山东农业科学,(6)：66-69.
163.樊金海.2009.精准农业变量施肥技术研究进展.现代农业科学,16(9)：90-91.
164.刘焱选,白慧东,蒋桂英.2007.中国精准农业的研究现状利发展方向.中国农学通报,23(7)：577-582.
165.曾希柏,李菊梅.2004.中国不同地区化肥施用及其对粮食生产的影响.中国农业科学,37(3)：387-392.
166.岑豫皖,叶金杰,潘紫微.2008.非线性状态空间方法辨识电液伺服控制系统.机械工程学报,44(12)：80-85.
167.曹健,马育华.2009.灰箱辨识在连续回转电液伺服马达中的应用.哈尔滨工业大学学报,41(5)：43-46.
168.马维金,王俊元,李凤兰,等.2010.基于ARX模型的控制系统辨识及稳定性分析.中北大学学报(自然科学版),31(1)：9-13.
169.王福斌,刘杰,陈至坤,等.2010.挖掘机器人阀控缸系统RBF神经网络参数辨识.东北大学学报(自然科学版),31(10)：1475-1478.
170.王晓晶,邵俊鹏,姜继海,等.2011.连续回转马达电液伺服系统辨识及控制.哈尔滨工程大学学报,32(8)：1045-1051.
171.朱建新,梅勇兵,杨翔,等.2007.液压挖掘机振动掘削系统辨识模型及算法研究.机电工程技术,36(10)：71-74.
172. Frank T.C.Tsai,Xiaobao Li.2008.multiple parameterization for hydraulic conductivity identification, ground water,46(6):851-864.
173. Bruno H.G.Barbosa,Luis A.Aguirre,Carlos B.Martinez,et al.2011.black and gray-box identification of a hydraulic pumping System.ieee transaction on control sysems technology,19(2):398-406.
174.马维金,王俊元,李凤兰,等.2010.基于ARX模型的控制系统辨识及稳定性分析.中北大学学报(自然科学版),31(1)：9-13.
175.高翔宇,苏东海.2009.比例变量泵控马达系统的PID控制与仿真.装备制造技术,(2)：1-3.
176.李伟,韩崇伟,位红军,等.2011.伺服系统的滑模变结构控制器设计.计算机仿真,28(12)：5-8,13.
177.王岩.2010.变量泵控制变量马达系统变结构控制算法.北京航空航天大学学报,36(12)：1453-1456.
178. Liu Rong,Pan Huachen,Chen Ying.2009. control strategy for electro-hydraulic position servo system with generalized pulse code modulation.chinese journal of mechanical engineering,20(3):50-53.
179. Zhong Tianyu,Wang Qingfeng,LiYanmin.2006.electro-hydraulic compound control method and characteristic of control for tension system with high inertia loads.chinese journal of mechanical engineering,19(3):391-394.
180.管成,朱善安.2005.电液伺服系统的多滑模鲁棒自适应控制[J].控制理论与应用,(22)：931-938.
181.仲伟峰,何小溪.2008.电液位置伺服系统的模糊神经网络控制.电机与控制学报,12(4)：478-482.
182.孟珺遐,王渝,王西彬.2010.高精度电液系统的模糊滑模控制仿真研究.电子科技大学学报,39(3)：338-342.
183.高强,王力,钱林方.2007.自适应模糊滑模控制在火箭炮电液伺服系统中的应用.兵工学报,28(9)：1148-1152.
184. Yao Jianiun,Wang Xiancheng,Wu Zhenshun,et al.2006. variable structure control applied in electro-hydraulic servo system with ann.chinese journal of mechanical engineering,19(1):32-36.
185.余愿,傅剑.2010.基于模糊滑模控制的液压位置伺服系统仿真.武汉理工大学学报(信息与管理工程版),32(2)：210-212.
186.孟珺遐,王渝,王西彬.2010.高精度电液系统的模糊滑模控制仿真研究.电子科技大学学报,39(3)：392-396.
187.张彩虹,刘云龙,高存臣,等.2012.Delta算子不确定系统的滑模变结构控制.控制与决策,27(2)：237-242.
188. O.Barambones,P.Alkorta.2010.vector control for induction motor drives based on adaptive variable structure control algorithm.asian journal of control,12(5):640-649.
189. E.Mirzaee,M.Eghtesad,S.A.Fazelzadeh.2010.maneuver control and active vibration suppression of a two-link flexible arm using a hybrid variable structure/Lyapunov control design.acta astronautica, 67:1218-1232.
190. Fabricio Garelli,Pablo Camocardi,Ricardo J.Mantz.2010.variable structure strategy to avoid amplitude and rate saturation in pitch control of a wind turbine.international journal of hydrogen energy, 35:5869-5875.
191.陈刚,柴毅,丁宝苍,等.2009.电液位置伺服系统的多滑模神经网络控制.控制与决策,24(2)：221-225.
192. Saeed Balochian,Ali Khaki Sedigh,Asef Zare.2011.variable structure control of linear time invariant fractional order systems using a finite number of state feedback law[J].commun nonlinear sci numer simulat,16:1433-1442.
2.吴才聪.2003.精确农业变量施肥决策研究与技术经济分析.吉林大学,博士学位论文
3.耿向宇.2007.基于GPS\GPRS的变量施肥机控制系统研究.上海交通大学,硕士学位论文
4.邵俊鹏,王仲文,李建英等.2010.电液位置伺服系统的规则自校正模糊PID控制器[J].中南大学学报(自然科学版),41(3)：960-965.
5.白寒,王庆九,徐振等.2009.阀控非对称缸系统多级滑模鲁棒自适应控制[J].农业机械学报,40(10)：193-198.
6. G.Zames.1998.Adaptive control:Towards a complexity-based general theory. automation,34(10):1161-1167
7. Z.Jiao,P.Chen,Q.Hu,S.Wang.2003.Adaptive vibration active control of fluid pressure pulsations proceedings of the Institution of mechanical engineers.Part Ⅰ:Journal of systems and control engineering,217(4):311-318
8. B.Yao,F.P.Bu,J.Reedy.2000.Adaptive robust motion control of single-rod hydraulic actuators:Theory and experiments.ieee/asme transactions on mechatronics,(2):759-763
9. B.Yao.1997.High performance adaptive robust control of nonlinear systems:a general framework and new schemes.Proceedings of the 36th ieee conference on decision and control, (3):2489-2494
10. G.Kreisselmeier,B.D.O.Anderson.1986.Robust model reference adaptive control.Ieee transations on automatic control,31(2):127-133
11. D.J.Sandoz,M.J.Desforges,B.Lennox,et al.2000.Algorithms for industrial model predictive control. Computing & control encineiering journal,11 (3):125-134
12. B.L.Shields,E.J.Barth,M.Goldfarb.2006.Predictive control for time-delayed switching control systems. Transactions of the asme,128(4):999-1004
13. Chen Wenhua,Hu Xiaobing.2004.Model predictive control of linear systems with nonlinear terminal control.International journal of robust and nonlinear control,14(4):327-339
14.乔丰立,唐兵,卢堃等.2005.比例控制径向柱塞泵性能预测.机械工程学报,41(10)：66-70
15. A.L.D.Franco,H.Bourles,E.R.De Pieri,et al.2006.Robust nonlinear control associating robust feedback linearization and h infinity control.Ieee transactions on automatic control,51 (7):1200-1207
16. Martinez-Salamero, L., Calvente, J., Romero, A.2006.An H∞ control strategy for switching converters in sliding-mode current control. IEEE Transactions on power electronics,21(2):553-556
17. Piao Fengxian,Zhang Qingling,Ma Xiuzhen.2006.Robust h infinity control for uncertain descriptor systems with state and control delay.Journal of systems engineering and electronics,17(3):571-575
18. Shao Keyong,Zhao Wanchun,Zhou Luanjie,et al.2004.Robust H-infinity control for linear uncertainty systems based on PI control laws. Institute of electrical and electronics engineers inc:Proceedings of 2004 international conference on machine learning and cybernetics,1:648-652
19. Zhang Ke.2006.A study on intelligent control for hybrid actuator. Lecture notes in computer Science,3972:1116-1123.
20. Ariuna,Damba,Shigeyoshi,et al.2004.Intelligent control in dynamic system 2004 ieee conference on robotics,automation and mechatronics. Singapore.institute of electrical and electronics engineers inc,2:644-648
21.李静,李晶瑜.2011.中国粮食生产的化肥利用效率及决定因素研究.农业现代化研究,32(5)：565-569
22.王祖力,肖海峰.2008.化肥施用对粮食产量增长的作用分析.农业经济问题,(8)：65-68
23.房丽萍,孟军化.2013.肥施用对中国粮食产量的贡献率分析.中国农学通报,29(17)：156-160
24.张福锁,王激清,张卫峰等.2008.中国主要粮食作物肥料利用率现状与提高途径.土壤学报,45(5)：915-924
25.张小超,胡小安,苑严伟等.2011.精准农业智能变量作业装备研究开发.农业工程,1(3)：26-32
26. M.L.Stone,J.B.Solie,W.R.Raun,et al.1996.Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Ransactions of asae,39(6):1623-1631
27.张维理,田哲旭,张宁等.我国北方农用氮肥造成地下水硝酸盐污染的调查.植物营养与肥料学报,1(2)：80-87
28.李军,黄敬峰,程家安.2003.我国化肥施用量及其可能污染的时空分布特征.生态环境,12(2)：145-149
29.孟志军.2007.基于处方图的变量施肥作业系统关键技术研究.中国农业大学,博士学位论文
30.周惠秋.2005.东北地区粮食综合生产能力研究.北京：中国农业出版社
31.毛惠忠.2005.新阶段中国粮食问题研究.北京：中国农业出版
32.李彦明.2005.变量施肥机研究技术报告.上海：上海交通大学
33. Precision agriculture in the 21st century.Geospatial and information technologies in crop management.national research council
34.段洁利,李君,卢玉华,.2011.变量施肥机械研究现状与发展对策.农机化研究,5：245-248
35. GL.Tian.1990.Dynamic smdy on typical area of huang he basin with remote sensing(in Chinese).Beijing:Science Press
36.薛利红,杨林章,李刚华.2004.遥感技术在精确施肥管理中的应用进展.农业工程学报,20(4)：224-226
37.赵军.2004.变量技术及其在农业机械中的应用.现代化农业,(12)：25
38.赵登峰,张立新,范子胜.2011.变量施肥装备的研究现状及展望.新疆农机化,4：29-34
39. Mark Morgan, Dan Ess.1997.The Precision-Farming Guide for Agriculturists. USA:Deere & Company
40.曲桂宝,田耘.2005.变量施肥的实现过程及其发展前景.中国农机化,4：50-54
41. P.A.S.Radite,M.Umeda,M.Iida,et al.2000.Variable rate fertilizer applicator for paddy field.Usa:asae annual international meeting
42.邓在京.2004.日本精准农业研究与开发现状.农机化研究,(9)：4-6
43.张晓辉,李汝萃.2002.法国的精确农业研究及应用现状.农机化研究,(1)：12-17
44. Litchman,Gennadi,Ivanovich.2002关于精确农业发展的研讨报告.中国：中国吉林大学
45. AgGPSTM124/132 OperationManua,1999. Revision.A TrimbleNavigation Limited
46.张书慧,马成林,吴才聪,等.2003.一种精确农业自动变量施肥技术及其实施.农业工程学报,19(1)：129-131
47.张书慧,马成林,杜巧玲.2004.精确农业自动变量施肥机控制系统设计与实现.农业工程学报,20(1)：113-116
48.吴才聪,马成林,张书慧,等.2003精确农业倾斜网格划分及其应用.农业工程学报,19(1)：137-141
49.张书慧,齐江涛,廖宗建,等.2010.基于CPLD的变量施肥控制系统开发与应用.农业工程学报26(8)：200-204
50.张林焕,张书慧,王薇.2010.基于PLC的液压无级调速变量施肥控制系统的研究.农业网络信息,7：9-13
51.马成林,吴才聪,张书慧.2004.基于数据包络分析和人工神经网络的变量施肥决策方法研究.农业工程学报,20(2)：152-155
52.付卫强,孟志军,黄文倩,等.2008.基于CAN总线的变量施肥控制系统.农业工程学报,24(Supp.2)：127-132
53.陈立平,黄文倩.2008.基于CAN总线的变量施肥控制器设计.农业机械学报,39(8)：101-104
54.邵利敏,王秀,牛晓.2007.基于PLC的变量施肥控制系统设计与试验颖.农业机械学报,38(11)：84-87
55.牛晓颖.2005.精准农业变量施肥技术及其实施系统的研究.河北农业大学,硕士学位论文
56.胡玲燕,王秀,韩应征.2010.光传感器变量施肥控制系统开发.农机化研究,11：91-94
57.王秀,赵春江,孟志军等.2004.精准变量施肥机的研制与试验.农业工程学报,20(5)：114-117
58.孟志军,赵春江,刘卉.2009.基于处方图的变量施肥作业系统设计与实现.江苏大学学报(自然科学版),30(4)：338-342
59.潘世强,曲桂宝,孙振中,等.2009.2BFJ-6型变量施肥精密播种机的研制.中国农机化,(6)：66-69,76
60.伟利国,张小超,苑严伟等.2012.2F-6-BP1型变量配肥施肥机研制与试验.农业工程学报,28(7)：14-18.
61.张辉,李树君,张小超,等.2010.变量施肥电液比例控制系统的设计与实现.农业工程学报,26(Supp.2)：218-222
62.刘阳春,张小超,伟利国等.2010.一种变量施肥技术的实现及其台架试验.农业机械学报,41(9)：159-162
63.张小超,胡小安,苑严伟等.2011.精准农业智能变量作业装备研究开发.农业工程,1(3)：26-32
64.梁春英,王熙,赵军.2003.变量施肥播种机电控液压驱动控制系统设计.黑龙江八一农垦大学学报,15(3)：47-50
65.梁春英,衣淑娟,王熙.2010.变量施肥控制系统PID控制策略研究.农业机械学报,41(7)：157-162
66.王新忠,王熙,汪春,等.2008.黑龙江垦区大豆变量施肥播种应用试验.农业工程学报,24(5)：143-146
67.赵军,王熙,庄卫东.2006.基于GPS的变量施肥播种机的试验研究.农机化研究,12：154-156
68.李爱传,王熙,汪志强.2009.电液驱动式变量施肥闭环控制系统研究.中国农学通报,25(7)：272-275
69.刘成良苑进.2010.基于ARM和DSP的双变量施肥控制系统设计与试验.农业机械学报51(Supp)：233-238
70.耿向宁,李彦明,苗玉彬等.2007.基于GPRS的变量施肥机系统研究研究.农业工程学报,23(11)：164-167
71.古玉雪,苑进,刘成良.2011.基于模糊系统的开度转速双变量施肥控制序列生成方法.农业工程学报,27(11)：134-139
72.李加念,洪添胜,冯瑞珏等.2012.基于脉宽调制的文丘里变量施肥装置设计与试验.农业工程学报,28(8)：105-110
73.张国梁,李成华,杨宇.2008.自动变量播种机控制系统设计.沈阳农业大学学报,39(6)：704-707
74.赵春超,赵克定,邵鸿德等.2003.基于Elman网络的液压系统辨识.机床与液压,(1)：129-130
75.阚超.2007.电液伺服与比例压力控制系统辨识与特性比较研究.燕山大学,博十学位论文
76.李鹏波.2010.系统辨识.北京：中国水利水电出版社
77.王荣.2007.双液压马达同步驱动控制与系统辨识研究.哈尔滨工业大学,硕十学位论文
78. L.A.Zadech
79.倪博溢,萧德云.2006MATLAB环境下的系统辨识仿真工具箱.系统仿真学报,18(6)：1493-1496
80.孙书立,胡守印.2005.MATLAB在热工系统辨识中的应用.科学技术与工程,5(5)：309-312
81.干琳,马平.2001.系统辨识方法综述[J].电力情报,(4)：63-66
82.方崇智,萧德云.1988.过程辨识.北京：清华大学出版社
83.莫建林,王伟,许晓鸣等.2002.系统辨识中的闭环问题.控制理论与应用,19(1)：9-14
84.王益群,王海芳,高英杰等.2004.基于神经网络的轧机液压AGC系统自适应辨识.中国机械工程,15(5)：450-453
85.王文韬,李成利,田军.2005.基于一种改进BP神经网络的一类非线性系统辨识方法.青岛科技大学学报(自然科学版),26(1)：85-88
86.姜春福,余跃庆,刘迎春.2004.冗余度机器人运动模型的神经网络辨识及实现.控制理论与应用21(3)：373-378
87.李保奎.2002.神经网络辨识方法及其在轧钢控制中的应用.北京理工大学学报,22(3)：311-314
88. S.V.Huffel,J.Vandwalle.1985.The use of total least squares techniques for identification and parameter estimation.Ifac.Identification and system Parameter Estimation,1985:1167-1172
89. Q.M.zhu,S.A.Billings.1993.Parameter estimation for stochastic nonlinear rational models. Int.j. control, 57(7):309-333'
90.庞中华,崔红.2009.系统辨识与自适应控伟MATLAB仿真.北京：北京航空航天大学出版社
91.胡干耀.2003.现代控制理论：系统辨识.北京：北京航空航天大学出版社
92. Shen ShuXiong,Zhao Zhou.2003.Neural filtering of colored noise based on kalman filter structure. Instrumentation and measurement,IEEE Transactions,52(3):742-747
93.李鹏波,胡德文,张纪阳.2010.系统辨识.北京：中国水利水电出版社
94.韩江,屈胜利,王效杰.2005.伺服系统辨识的仿真与实现.航空计算技术,35(4)：50-52
95.陈海龙,李宏.2005.基于MATLAB的伪随机序列的产生和分析.计算机仿真,22(5)：98-100
96.吴晓燕,周延延,张双选.2003.一种用于模型结构辨识的新方法.空军工程大学学报(自然科学版),4(4)：77-80
97. L.Ljung.2002.system identification theory for the user (second edition)北京：清华大学出版社
98.王秀峰.2004.系统建模与辨识.北京：电子工业出版社
99.杨承志.2003.系统辨识与自适应控制.重庆：重庆大学出版社
100.于刚.2007.伺服阀控液压马达系统的辨识与控制研究.山东大学,硕士学位论文
101. H.Unbehauen.1982.Identification of dynamic systems. Second iasted intenetional symposium, Modeling identification and robotics
102. K.Diekmann,H.Unbehanen.1982.Tests for determining the order of canonical models of multivariable systems.Ifacs symposium on theory and application of digital control,13:1-7
103. H.Akaika.1987.Faetor analysis and aic.Psychometrik,(52):97-104
104.鲁万波,余竞.2003.用AIC准则识别最佳因子分析模型.成都大学学报(自然科学版),22(2)：28-32
105.H.Akaika.1972.Use of an information.theoretic for statistical model identification.Hawaii:proc.of 5th hawaii int,conf on system Science
106.方崇智,萧德云.1988.过程辨识.北京：清华大学出版社
107. V.S.Emelyanov,A.L.Fedotova.1962.Design of a static tracking systems with variable structure. Automation and remote contro,(10):1223-1235
108. V.S.Emelyanov,B.P.Matic,N.E.Kostyleva.1973.A universal uniform control system with variable structure.inst.Contr.system,(1):5-10
109. V.I.Utkin.1965.On compensation of the forced component in the motion of control systems with variable structure.Eng.Cybem,(4):167-171
110. V.I.Utkin,1983.vss:Vresent and future.Automation and remote control,(44):1105-1120
111.高为炳.1990.变结构控制理论基础.北京：中国科学技术出版社
112.高为炳.1996.变结构控制的理论及设计方法.北京：科学出版社
113.王丰尧.1995.滑模变结构控制.北京：机械工业出版社
114.高为炳.1995.离散时间系统的变结构控制.自动化学报,21(2)：154-160
115.翟长连,吴智铭.2000.一种离散时间系统的变结构控制方法.上海交通大学学报,1.14(5)：719-722
116.胡云安,顾文锦.1995.模糊变结构控制及其应用.航天控制,(4)：54-59
117.David Munoz,Daniel Sbarbaro.2000.An adaptive sliding-mode controller for discrete nonlinear systems.IEEE Transactions on industrial electronics,1.47(3):547-581
118. C.Canudas de Wit,H.Olsson,K.J.Astrom,et al.1995.A new model for control of systems with friction.IEEE Transactions on automatic control,1.40(3):419-424
119.张春雷.2012.基于变结构方法的倒立摆控制研究.三峡大学,硕士学位论文
120.解磊.2006.基于变结构控制策略的转台控制技术研究.南京航空航天大学,硕士学位论文
121.马亚丽.2010.基于滑模变控制理论的电液位置伺服控制方法研究.太原理工大学,硕士学位论文
122.K.D.Young,V.I.Utkin,U.Ozguner.1999.A control engineer's guide to sliding mode control.IEEE Transactions on control systems technology,7(3):328-342
123.S.C.Y.Chung,C.L.Lin.1999.A transformed lure problem for sliding mode control and chattering reduction.IEEE Transactions on automatic control,44(3):563-568
124.K.Jiang,J.G.Zhang,Z.M.Chen.2002.A new approach for the sliding mode control based on fuzzyreaching law. Intelligent control and automation,proceedings of the 4th world congress on,(1):656-660
125.胡云安,顾文锦.1995.模糊变结构控制及其应用.航天控制,(4)：54-59
126.H.Yanada,H.Ohnishi.1999.Frequency-shaped sliding mode control of an electrohydraulic servomotor. Journal of systems and control and dynamics21(1):441-448
127.A.Kawamura,H.Itoh,K.Sakamoto.1994.Chattering reduction of disturbance observer based sliding mode control.IEEE Transactions on industry applications,30(2):456-461
128.C.L.Hwang.1996.Sliding mode control using time-varying switching gain and boundary layer for electrohydraulic position and differential pressure contro.IEEE Proceedings-control theoryand applications,143(4):325-332
129.Y.Konno,H.Hashmoto.1992.Design of sliding mode dynamics in frequency domain.IEEE Workshop on variable structure and lyapunov control of uncertain dynamical Systems,1992:120-125
130.靳宝全.2010.电液位置伺服控制系统的模糊滑模控制方法研究.太原理工大学,博士学位论文
131. W.B.Gao,Y.F.Wang.1995.Discrete-time variable structure control systems.IEEE Transaction on industrial electronics,42(2):117-122
132.K.Furuta.1990.Sliding mode control of a discrete system.Systems & control leters,14(2):145-152
133.高为炳,1995.离散时间系统的变结构控制.自动化学报,21(2)：154-160
134.翟长连,吴智铭.2000.一种离散时间系统的变结构控制方法.上海交通大学学报,214(5)：719-722
135.姚琼荟,宋立忠,温洪.2000.离散变结构控制系统的比例—等速—变速控制.控制与决 策,15(3)：229-332
136.翟长连,吴智铭.2000.不确定离散时间系统的变结构控制设计.自动化学报,26(2)：184-191
137.宋立忠,陈少吕.2004.滑模预测离散变结构控制.控制理论与应用,21(5)：826-829
138. Y.P.Chen,J.L.Chang,.S.R.Chu.1999.Pc-based sliding-mode control applied to parallel-type double inverted pendulum system.Mechatronics,9:553-564
139. David Munoz,Daniel Sbarbaro.2000.An adaptive sliding-mode controller for discrete nonlinear systems.IEEE Transactions on industrial electronics,47(3):547-581
140.胡云安,顾文锦.1995.模糊变结构控制及其应用.航天控制,(4)：54-59
141. Q.P.Ha,Q.H.Nguyen,D.C.Rye.2001.Fuzzy sliding-mode controller withapplications. IEEE Transactions on industrial electronics48(1):38-46
142. Meliksah Ertugrul,Okyay Kaynak.1998.Neural computation of the equivalent control in sliding mode for robot trajectory control applications.Proceedings of the 1998 ieee international conference on robotic & automation,1998:2042-2047
143. Milo savljevie.1985.General conditions for the existence of a quasi-sliding mode on the switching byperplane in discrete variable structure system.Automation and remote control,46(3):307-314
144. Y.Dot,R.G.Holf.1980. Microprocessor based sliding mode controller for dc motor drives. Cincinnati: presented at the Industrial Application Society Annual Meeting
145. S.Z.Sapturk,Y.Istefanopulos,Kaynak O.1987.On the stability of discrete-time sliding mode control systems. IEEE Transautom at contr,32 (10):930-932
146.高为炳.1998.变结构控制的理论及设计方法.北京：科学出版社
147.刘金琨.2005.滑模变结构MATLAB仿真.北京；清华大学出版社
148.杨勇,文丹,罗安等.2006.基于多目标优化的模糊滑模变结构控制及应用.中南大学学报(自然科学版)37(6)：1149-1154
149.刘金琨.2005.滑模变结构控制MATLAB仿真.北京：清华大学出版社
150.曾光奇,胡均安,王东等.2006.模糊控制理论与工程应用.武汉：华中科技大学出版社
151.陈志梅,王贞艳,张井冈.2012.滑模变结构控制理论及应用.北京：电子工业出版社
152.孙成.2008.变量施肥机控制系统的研究,吉林农业大学,硕士论文
153.曲桂宝.2006.变量施肥机的试验研究.吉林农业大学,硕士论文
154.赵登峰.2012.棉花变量施肥关键技术及装置研究.石河子大学,硕士论文
155.李红岩.2006.精准农业田间变量施肥控制系统研究.西安科技大学,硕士论文
156.王熙.2006.精准农业大豆变量施肥控制技术研究.黑龙江八一农垦大学,博士论文
157.刘阔,郭大猛,刘杰,等.2009.液压挖掘机自适应模糊滑模控制的研究与仿真.东北大学学报(自然科学版),30(11)：1649-1652
158.席爱民.2008.模糊控制技术.西安：西安电子科技大学出版社
159.黄文芳.2011.农业化肥污染的政策成因及对策分析.生态环境学,20(1)：193-198.
160.靳双珍,刘国顺,闫新甫,等.2010.我国发展精准农业的必要性与应用前景,浙江农业科学,(2)：414-416.
161.周智艳,罗锡文,臧英.2010.水稻-稻田环境系统重要信息快速获取技术研究进展.中国科学：信息科学,40(Supp)：38-53.
162.杨玉建,朱建华.尚明华,等.2006.精准农业关键技术及其发展前景.山东农业科学,(6)：66-69.
163.樊金海.2009.精准农业变量施肥技术研究进展.现代农业科学,16(9)：90-91.
164.刘焱选,白慧东,蒋桂英.2007.中国精准农业的研究现状利发展方向.中国农学通报,23(7)：577-582.
165.曾希柏,李菊梅.2004.中国不同地区化肥施用及其对粮食生产的影响.中国农业科学,37(3)：387-392.
166.岑豫皖,叶金杰,潘紫微.2008.非线性状态空间方法辨识电液伺服控制系统.机械工程学报,44(12)：80-85.
167.曹健,马育华.2009.灰箱辨识在连续回转电液伺服马达中的应用.哈尔滨工业大学学报,41(5)：43-46.
168.马维金,王俊元,李凤兰,等.2010.基于ARX模型的控制系统辨识及稳定性分析.中北大学学报(自然科学版),31(1)：9-13.
169.王福斌,刘杰,陈至坤,等.2010.挖掘机器人阀控缸系统RBF神经网络参数辨识.东北大学学报(自然科学版),31(10)：1475-1478.
170.王晓晶,邵俊鹏,姜继海,等.2011.连续回转马达电液伺服系统辨识及控制.哈尔滨工程大学学报,32(8)：1045-1051.
171.朱建新,梅勇兵,杨翔,等.2007.液压挖掘机振动掘削系统辨识模型及算法研究.机电工程技术,36(10)：71-74.
172. Frank T.C.Tsai,Xiaobao Li.2008.multiple parameterization for hydraulic conductivity identification, ground water,46(6):851-864.
173. Bruno H.G.Barbosa,Luis A.Aguirre,Carlos B.Martinez,et al.2011.black and gray-box identification of a hydraulic pumping System.ieee transaction on control sysems technology,19(2):398-406.
174.马维金,王俊元,李凤兰,等.2010.基于ARX模型的控制系统辨识及稳定性分析.中北大学学报(自然科学版),31(1)：9-13.
175.高翔宇,苏东海.2009.比例变量泵控马达系统的PID控制与仿真.装备制造技术,(2)：1-3.
176.李伟,韩崇伟,位红军,等.2011.伺服系统的滑模变结构控制器设计.计算机仿真,28(12)：5-8,13.
177.王岩.2010.变量泵控制变量马达系统变结构控制算法.北京航空航天大学学报,36(12)：1453-1456.
178. Liu Rong,Pan Huachen,Chen Ying.2009. control strategy for electro-hydraulic position servo system with generalized pulse code modulation.chinese journal of mechanical engineering,20(3):50-53.
179. Zhong Tianyu,Wang Qingfeng,LiYanmin.2006.electro-hydraulic compound control method and characteristic of control for tension system with high inertia loads.chinese journal of mechanical engineering,19(3):391-394.
180.管成,朱善安.2005.电液伺服系统的多滑模鲁棒自适应控制[J].控制理论与应用,(22)：931-938.
181.仲伟峰,何小溪.2008.电液位置伺服系统的模糊神经网络控制.电机与控制学报,12(4)：478-482.
182.孟珺遐,王渝,王西彬.2010.高精度电液系统的模糊滑模控制仿真研究.电子科技大学学报,39(3)：338-342.
183.高强,王力,钱林方.2007.自适应模糊滑模控制在火箭炮电液伺服系统中的应用.兵工学报,28(9)：1148-1152.
184. Yao Jianiun,Wang Xiancheng,Wu Zhenshun,et al.2006. variable structure control applied in electro-hydraulic servo system with ann.chinese journal of mechanical engineering,19(1):32-36.
185.余愿,傅剑.2010.基于模糊滑模控制的液压位置伺服系统仿真.武汉理工大学学报(信息与管理工程版),32(2)：210-212.
186.孟珺遐,王渝,王西彬.2010.高精度电液系统的模糊滑模控制仿真研究.电子科技大学学报,39(3)：392-396.
187.张彩虹,刘云龙,高存臣,等.2012.Delta算子不确定系统的滑模变结构控制.控制与决策,27(2)：237-242.
188. O.Barambones,P.Alkorta.2010.vector control for induction motor drives based on adaptive variable structure control algorithm.asian journal of control,12(5):640-649.
189. E.Mirzaee,M.Eghtesad,S.A.Fazelzadeh.2010.maneuver control and active vibration suppression of a two-link flexible arm using a hybrid variable structure/Lyapunov control design.acta astronautica, 67:1218-1232.
190. Fabricio Garelli,Pablo Camocardi,Ricardo J.Mantz.2010.variable structure strategy to avoid amplitude and rate saturation in pitch control of a wind turbine.international journal of hydrogen energy, 35:5869-5875.
191.陈刚,柴毅,丁宝苍,等.2009.电液位置伺服系统的多滑模神经网络控制.控制与决策,24(2)：221-225.
192. Saeed Balochian,Ali Khaki Sedigh,Asef Zare.2011.variable structure control of linear time invariant fractional order systems using a finite number of state feedback law[J].commun nonlinear sci numer simulat,16:1433-1442.
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