复合误差模型自适应船舶控制系统的应用研究
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摘要
研究船舶控制多过程特性及其相互作用和影响,应用自学习和自适应被控过程特性渐变的复合误差反馈控制器,提高船舶控制系统性能,具有重要现实意义。
分析广义误差特性及其蕴含的过程特征信息,应用于复合误差控制模型的研究。提出基于测度方法的结构在线学习和基于方向导数算法的参数在线学习,增加具有记忆功能的反馈连接,动态误差循环补偿,自整定参数少的模糊神经网络复合误差模型。
综合了作用在船舶上的环境干扰、船舶非线性动态过程、推进系统产生的推力及舵机速度对船舶操纵的影响,建立了船舶沿着给定航线运动的复合误差模型。在此基础上,研究了船舶-主机一体自适应学习误差模型控制的广义船速调节器,实现了航速闭环控制;集成了驾驶员的自学习、辨识和自适应能力,提出了人-船一体复合误差控制模型。
研究了船舶轴带发电-电力推进及其能量回馈的复杂控制系统,综合了自动电压调节器(AVR)的鲁棒滑模变结构误差自校正控制、并网发电机组动态特性误差状态空间、推进电机的滑模变结构-模糊神经网络复合误差控制以及废气透平发电机增广误差二次型最优控制,提出优化船舶电力推进系统的多级自动控制方法,建立复合误差控制模型,进行了Lyapunov稳定性分析。
实船安装调试了基于航向误差控制的船舶自动舵;完成了船舶-主机一体的广义调速器半实物仿真训练平台;应用Sinamics S120和Simotion D实现了船舶轴带发电-电力推进及能量回馈节能技术的半实物仿真系统,进行了复合误差控制方法的试验研究,结果表明,复合误差控制模型具有很好的自适应性、稳定性和鲁棒性。
The multi-process characteristics and interaction effects of ship control systems are studied in this thesis.A hybrid error feedback controller is applied to controlling the ship multi-process systems.This controller has the abilities of self-learning and the adaptability of asymptotically convergent characteristics.These abilities enable to improve the performance of the ship control systems.These characteristics are important for practical application to ship controls systems.
In order to analyze the characteristics of generalized errors and their inherent behavior of the process information,a generalized error model is used to study hybrid error control systems.A fuzzy-neuro hybrid error model(FNHEM) is proposed for the ship multi-process systems.The structure learning of FNHEM is conduced with the degree measure and the parameter learning of the model is carried out with the ordered derivative algorithm.To increase memory abilities of FNHEM,the feedback connection elements are embedded in FNHEM,which has the advantage of dynamically recurrent error compensatory and needs few self-tuning parameters.
A hybrid error model is established under the situation that the ship goes along the desired trajectory.The hybrid error model integrates the influences of the ship's environmental disturbances,of ship nonlinearly dynamic process,of thrust's propulsion and of speed of rudder angle on ship manoeuvre.Based on the hybrid error model,a generalized speed regulator of integrated ship-diesel engine system using self-learning and adaptive error model is researched,by which the closed-loop ship speed control is achieved.The main feature of the hybrid error control model is that the abilities of learning,identification and adaptation of the ship pilots are all integrated into the seaman ship systems for ship movement control scheme.
A hardware-in-loop simulation system for marine propulsion-shaft electric generator is implemented.This system can feedback energy to the ship electrical network,so that the saving technology is realized.Integrated analysis of AVR using robust sliding mode self-tuning control method is carried out.Some intelligent control methods also are taken into consideration including the paralleling generators dynamic behavior error state-space,the hybrid error control of electric propulsion motor which consists of a parallel connected sliding mode controller and a fuzzy-neural controller, and the augmented linear quadratic Gaussian control scheme for exhaust turbine generator.Optimal control methods of multi-task automatic control for ship electric propulsion system is proposed,and its hybrid error control model is established and analyzed by Lyapunov stability Theory.
A benchmark system for marine autopilot training with,semi-physical simulator is established,of which the generalized speed regulator of integrated ship-diesel engine system is achieved.Siemens Sinamics S120 and Simotion D Scout are used for hardware-in-loop simulation system of marine propulsion-shaft electric generator and energy feedback saving technology being realized.The hybrid error control method is tested on the benchmark system.The results show that hybrid error control model can enhance the stability for ship control process,has good adaptability and robustness.
分析广义误差特性及其蕴含的过程特征信息,应用于复合误差控制模型的研究。提出基于测度方法的结构在线学习和基于方向导数算法的参数在线学习,增加具有记忆功能的反馈连接,动态误差循环补偿,自整定参数少的模糊神经网络复合误差模型。
综合了作用在船舶上的环境干扰、船舶非线性动态过程、推进系统产生的推力及舵机速度对船舶操纵的影响,建立了船舶沿着给定航线运动的复合误差模型。在此基础上,研究了船舶-主机一体自适应学习误差模型控制的广义船速调节器,实现了航速闭环控制;集成了驾驶员的自学习、辨识和自适应能力,提出了人-船一体复合误差控制模型。
研究了船舶轴带发电-电力推进及其能量回馈的复杂控制系统,综合了自动电压调节器(AVR)的鲁棒滑模变结构误差自校正控制、并网发电机组动态特性误差状态空间、推进电机的滑模变结构-模糊神经网络复合误差控制以及废气透平发电机增广误差二次型最优控制,提出优化船舶电力推进系统的多级自动控制方法,建立复合误差控制模型,进行了Lyapunov稳定性分析。
实船安装调试了基于航向误差控制的船舶自动舵;完成了船舶-主机一体的广义调速器半实物仿真训练平台;应用Sinamics S120和Simotion D实现了船舶轴带发电-电力推进及能量回馈节能技术的半实物仿真系统,进行了复合误差控制方法的试验研究,结果表明,复合误差控制模型具有很好的自适应性、稳定性和鲁棒性。
The multi-process characteristics and interaction effects of ship control systems are studied in this thesis.A hybrid error feedback controller is applied to controlling the ship multi-process systems.This controller has the abilities of self-learning and the adaptability of asymptotically convergent characteristics.These abilities enable to improve the performance of the ship control systems.These characteristics are important for practical application to ship controls systems.
In order to analyze the characteristics of generalized errors and their inherent behavior of the process information,a generalized error model is used to study hybrid error control systems.A fuzzy-neuro hybrid error model(FNHEM) is proposed for the ship multi-process systems.The structure learning of FNHEM is conduced with the degree measure and the parameter learning of the model is carried out with the ordered derivative algorithm.To increase memory abilities of FNHEM,the feedback connection elements are embedded in FNHEM,which has the advantage of dynamically recurrent error compensatory and needs few self-tuning parameters.
A hybrid error model is established under the situation that the ship goes along the desired trajectory.The hybrid error model integrates the influences of the ship's environmental disturbances,of ship nonlinearly dynamic process,of thrust's propulsion and of speed of rudder angle on ship manoeuvre.Based on the hybrid error model,a generalized speed regulator of integrated ship-diesel engine system using self-learning and adaptive error model is researched,by which the closed-loop ship speed control is achieved.The main feature of the hybrid error control model is that the abilities of learning,identification and adaptation of the ship pilots are all integrated into the seaman ship systems for ship movement control scheme.
A hardware-in-loop simulation system for marine propulsion-shaft electric generator is implemented.This system can feedback energy to the ship electrical network,so that the saving technology is realized.Integrated analysis of AVR using robust sliding mode self-tuning control method is carried out.Some intelligent control methods also are taken into consideration including the paralleling generators dynamic behavior error state-space,the hybrid error control of electric propulsion motor which consists of a parallel connected sliding mode controller and a fuzzy-neural controller, and the augmented linear quadratic Gaussian control scheme for exhaust turbine generator.Optimal control methods of multi-task automatic control for ship electric propulsion system is proposed,and its hybrid error control model is established and analyzed by Lyapunov stability Theory.
A benchmark system for marine autopilot training with,semi-physical simulator is established,of which the generalized speed regulator of integrated ship-diesel engine system is achieved.Siemens Sinamics S120 and Simotion D Scout are used for hardware-in-loop simulation system of marine propulsion-shaft electric generator and energy feedback saving technology being realized.The hybrid error control method is tested on the benchmark system.The results show that hybrid error control model can enhance the stability for ship control process,has good adaptability and robustness.
引文
[1]滕毓发,张庆灵,张明学等.广义大系统的分散鲁棒镇定。东北大学学报(自然科学版),2008,29(2):178-180.
[2]王元放,周宏仁,敬忠良.“系统的系统”综述.系统仿真学报,2007,19(6):1182-1185.
[3]Asgeir J S.Structural issues in the design and operation of marine control system.Annual Reviews in Control,2005,29(1):125-149.
[4]George G D,Areitotelis V K,Christos A F.Synthesis,design and operation optimization of a marine energy system.Energy,33(2008):180-188.
[5]Amerongen J V.Adaptive steering of ships-a model reference approach.Automatica,1984,20(1):3-14.
[6]Kallstrom C G.Adaptive autopilots for tankers.Automatica,1979,15(2):241-254.
[7]Yang Y S.Neural network adaptive control for ship automatic steering.Proceedings of International Conference of Young Investigators on Information,Computer and Control,Beijing,1994:231-236.
[8]Layne J R,Passino K M.Fuzzy model reference learning control for cargo ship steering.IEEE Transactions on Control Systems Magazine,1993,13(6):23-34.
[9]Yang Y S,Zhou C J,Jia X.Robust adaptive fuzzy control and its application to ship roll stabilization.Information Sciences,2002,142(1):177-194.
[10]林叶锦.船舶运动模糊神经网络控制系统的研究:(博士学位论文).大连:大连海事大学,2007.
[11]王先洲.船舶及潜艇操纵中的鲁棒控制研究:(博士学位论文).武汉:华中科技大学,2008.
[12]Do K D,Jiang Z P.Robust global stabilization of underactuated ships on a linear course:state and output feedback.International Journal of Control,2003,76(1):1-17.
[13]Yoon H K,Rhee K P.Identification of hydrodynamic coefficients in ship maneuvering equations of motion by estimation-before-modeling technique.Ocean Engineering,30(2003):2379-2404.
[14]Jiang Z P.Global tracking control of underactuated ships by Lyapunov's direct method.Automatica,2002,38(2):301-309.
[15]Pettersen K Y,Nijmeijer H.Underactuated ship tracking control:Theory and experiments.International Journal of Control,2001,74(14):1435-1446.
[16]Selvam R P,Bhattaeharyya S K,Haddara M R.A frequency domain system identification method for linear ship manoeuvring.International Shipbuilding Progress,52(2005):5-27.
[17]Ivar-Andr F I,Irme J,Thor I F.Formation control of marine surface craft:A Lagrangian approach.Oceanic Engineering,2006,31(4):922-934.
[18]Cimen T,Banks S E Nonlinear optimal tracking control with application to super-tankers for autopilot design.Atuomatica,2004,40(11):1845-1863.
[19]Shim D K,Park J H,Pramod P,et al.Reducing automotive engine speed fluctuation at idle.IEEE Transactions on Control System Technology,1996,4(4):404-409.
[20]Carlucci A P,Ficarella A,Laforgia D.Control of the combustion behaviour in a diesel engine using early injection and gas addition.Applied Thermal Engineering,26(2006):2279-2286.
[21]Jankovic M,Jankovic M,Kolmanovsky I.Constructive Lyapunov control design for turbocharged diesel engine.IEEE Transactions on Control System Technology,2002,8(2):288-299.
[22]Gimitrios T H.Prediction of marine diesel engine performance under fault conditions.Applied Thermal Engineering,20(2000):1753-1783.
[23]Zhang H,Li Z G,Chen Z N.Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines.Tribology International,36(2003):753-756.
[24]黄曼磊,王常虹.船舶电站柴油机双脉冲H∞调速器的研究.控制理论与应用,2007,24(2):283-288.
[25]Ericsen T,Hingorani N,Khersonsky Y.Power electronics and future marine electrical system.IEEE Transactions on Industry Applications,2006,42(1):155-163.
[26]Mendes J C,Saavedra O R,Feitosa S A.A parallel complete method for real-time security analysis in power system.Electric Power System Research,2000,56(1):27-34.
[27]Zivi E.Design of robust shipboard power automation systems.Annual Review in Control,2005,29(2):261-272.
[28]Burden R L,Faires J D.Numerical analysis.Boston:PWS-Kent Pub.Co.,1993.
[29]Draper N R,Smith H.Applied regression analysis.New York:John Wiley & Sons,1981.
[30]Shah S,Palmieri F,Datum M.Optimal filtering algorithms for fast learning in feed-forward neural networks.Neural Networks,1992,5(5):779-787.
[31]shinskey F G著.萧德云,吕伯明译.过程控制系统一应用、设计与整定.北京:清华大学出版社,2004.
[32]Gawthrop P J.Self-tuning PID controller:Algorithms and implementation.IEEE Transactions on Automatic Control,1986,31(3):201-209.
[33]Gyongy I J,Clarke D W.On the automatic tuning and adaptation of PID controllers.Control Engineering Practice,2006,14(2):149-163.
[34]Hang C C,Astrom K J,Wang Q G..Relay feedback auto-tuning of process controllers-a tutorial review.Journal of Process Control,2002,12(1):143-162.
[35]Ho W K,Hong Y,Hansson Aet al.Relay auto-tuning of PID controllers using iterative feedback tuning.Automatica,2003,39(1):149-157.
[36]Astrom K J,Hagglund T.Automatic tuning of simple regulators with specifications on phase and amplitude margins.Automatica,20(1984):645-651.
[37]Ho W K,Hang C C,Cao L S.Tuning of PID controllers based on gain and phase margin specifications. Automatica,1995,31(3):497-502.
[38]Astrom K J,Hagglind T.Industrial adaptive controllers based on frequency response techniques.Automatica,1991,27(4):599-609.
[39]Lee T H,Hang C C,Ho W K et al.Implementation of a knowledge-based PID auto-tuner.Automatica,1993,29(4):1107-1113.
[40]Kim S M,Han W Y.Induction motor servo drive using robust PID-like neuron-fuzzy controller.Control Engineering Practice,2006,14(5):481-487.
[41]Lin F J,Hwang W J,Wai R J.A supervisory fuzzy neural network control system for tracking periodic inputs.IEEE Transactions on Fuzzy Systems,1999,7(1):41-52.
[42]Chen C T,Chang W D.A feedforward neural network with function shape auto-tuning.Neural Networks,1996,9(4):627-641.
[43]Omatu S,Khalid M,Yusof R.Neuro-control and its applications.London:Springer,1995.
[44]马建伟.多指标满意PID控制设计研究:(博士学位论文).南京:南京理工大学,2005.
[45]周晓兵.基于TCP/IP网络的延时建模及网络先进PID控制器研究:(博士学位论文).上海:上海大学,2008.
[46]李银伢.满意PID控制器设计理论:(博士学位论文).南京:南京理工大学,2007.
[47]Koivo H N,Tanttu J T.Tuning of PID controller-survey of SISO and MIMO.Preprints of IFAC International Symposium on Intelligent Tuning and Adaptive Control,Singapore,1991.
[48]Pentirmen J,Koivo H N.Multivarable tuning regulators for unknown systems.Automatica,1997,33(4):393-398.
[49]Yusof R,Omatu S.A multivariable self-tuning PID controller.International Journal of Control,1993,57(6):1387-1403.
[50]靳其兵,吴斌多指标相容下的多变量PID控制器设计.北京化工大学学报,2008,35(3):89-92.
[51]Gaing Z L.A particle swarm optimization approach for optimum design of PID controller in AVR system.IEEE Transactions on Energy Conversion,2004,19(2):384-391.
[52]Mukherjee V,Ghoshal S P.Intelligent particle swarm optimized fuzzy PIDcontroller for AVR system.Electric Power System Research,77(2007):1689-1698.
[53]Ghoshal S P.Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control.Electric Power System Research,27(2004):203-212.
[54]薛亚丽,李东海,吕崇德.汽轮发电机组多变量PID控制器的优化设计.动力工程,2005,25(5):668-741.
[55]廖少明,汪敏,侯学渊.盾构近距离施工的IMC-PID控制模型研究.岩石力学与工程学报,2006,25(S2):4132-4138.
[56]綦守荣,王东风,韩璞等.基于鲁棒整定的球磨机系统多变量PID控制,系统仿真学报,2005,17(12):3001-3003.
[57]曹健,王俊凯,吴盛林等.动态矩阵(DMC)-PID串级预测控制策略在新型叶片连续回转马达位置伺服系统中的应用.宇航学报,2006,27(4):625-629.
[58]彭辉,彭晓燕.广义预测补偿-自校正PID串级控制算法.中国有色金属学报,1995,5(4):158-162.
[59]李林欢,苏宏业,褚健.一类多输入多输出系统的预测PID控制算法仿真.系统仿真学报,2004,16(3):495-503.
[60]刘红军,韩璞,王东风等.灰色预测模糊PID控制在汽温控制系统中的应用.系统仿真学报,2004,16(8):1839-1848.
[61]彭道刚,张浩,杨平等.基于灰色预测的汽温模糊免疫PID控制.动力工程,2007,27(1):72-75.
[62]韩敏,郭伟,王金城.基于RBF网络的大滞后系统自适应预测PID控制器.仪器仪表学报,2005,26(10):1039-1043.
[63]陶文华,李平,穆玲.基于神经元的自适应预测PID控制.抚顺石油学院学报,2002,22(2):67-69.
[64]杨智,高靖.时变大时滞神经元自适应预测PID控制器.仪器仪表学报,2000,21(3):300-303.
[65]牛玉刚,杨成梧,赵建丛.基于多步预测的PID型神经网络控制.南京理工大学学报,2000,24(3):199-202.
[66]明学星,王建国,吕震中等.基于混沌理论的预测PID控制器参数优化研究.热能动力工程,2008,23(2):178-182.
[67]牛培峰,张君,关新平.基于遗传算法的混沌系统二自由度比例-积分-微分控制研究.物理学报,2007,56(7):3759-3765.
[68]丁丰平,张华强,苏振.基于预测控制的Fuzzy-PID控制器算法研究.电子器件,2007,30(6):2152-2158.
[69]任正云,邵惠鹤,张立群.几种不稳定滞后对象的预测PID控制.控制与决策,2004,19(6):671-674.
[70]张燕,陈增强,袁著祉.基于Taylor逼近的非线性系统PID型多步预测控制.控制与决策,2004,19(4):448-451.
[71]李林欢,刘斌,苏宏业等.基于输出误差预测的模糊预测PID控制及应用.浙江大学学报(工学版),2004,38(7):826-830.
[72]沈国江,孙优贤,马婷芳.基于误差性能指标的强时变时滞系统鲁棒PID继电自整定控制技术.中国造纸学报,2002,17(1):93-95.
[73]刘金琨.先进PID控制MATLAB仿真(第2版).北京:电子工业出版社,2004.
[74]Chang W D,Hwang R C,Hsieh J G.A self-tuning PID control for a class of nonlinear system based on the Lyapunov approach.Journal of Process Control,12(2002):233-242.
[75]Chang W D,Yan J J.Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems.Chaos,Solitons and Fractals,26(2005):167-175.
[76]张晓宇,王子才,高伟巍.基于ITAE准则的质量矩拦截弹鲁棒控制研究.系统工程与电子技术,2007,29(12):2101-2105.
[77]王曦,林永霖,吴永康.H∞控制在飞行/推进综合控制系统中的应用.航空动力学报,2004,19(5):695-702.
[78]王应明,傅国伟.基于不同误差准则和范数的组合预测方法研究.控制与决策,1994,9(1):20-28.
[79]茅健.基于数学定义的公差建模与误差评定技术的研究:(博士学位论文).杭州:浙江大学,2007.
[80]丁瑞强.非线性误差增长理论与可预报性研究:(博士学位论文).北京:中国科学院研究生院,2007.
[81]Klein A,Kaleh G K,Baier P W.Zero forcing and minimum mean square error equalization for multiuser detection in code-division multiple-access channels.IEEE Trans.On Vehicular Technologu,1996,45(2);276-287.
[82]高松,贺仁睦,马进等.电力系统动态仿真误差评定准则研究.电力系统自动化,2006,30(4):6-10.
[83]杨新刚,黄玉美,李艳等.三维测头探测误差的评定准则及高精度评定方法研究.计量学报,2008,29(3):207-210.
[84]Hou H,Yang J H.An electro-acoustics impedance error criterion and its application to active noise control.Applied Acoustics,65(2004):485-499.
[85]Li X,Fang R W.Error criteria analysis and robust data fusion.IEEE ICASSP,Australia,1994,37-39.
[86]唐颖莉,郑时雄,刘桂雄等.基于熵概念的机器人动态误差理论的研究.机械科学与技术,2001,20(5):646-648.
[87]Qian W M,Cai G X.Strong approximability of wavelet estimate in semiparamtric regression mode.Science in China(series A),1999,29(3):233-240.
[88]Qian W M,Cai G X,Jiang F Y.Error variance of wavelet estimate in semiparamtric regression.Chinese Journal of Annual of Maths,2000,21(A 3):341-350.
[89]Yan Z Z,Wu W H,Nie Z K.Near neighbour estimate in semiparamtric Regression model:The martingale difference error sequence case.Chinese Journal of Applied Probability and Statistics,2001,17(1):44-50.
[90]胡宏昌,孙海燕.半参数回归模型小波估计的稳定地依分布收敛性-误差为鞅差序列情形.武汉大学学报(理学版),2003,49(5):571-574.
[91]Baeza-Baeza J J,Ramis-Ramos G.Analysis of the sensitivity to the systematic error in least-squares regression models.Analytica Chimica Acta,515(2004):15-21.
[92]曾六川.非一致光滑的Banach空间中强增生型变分包含问题解的带误差的Ishikawa迭代逼近.工程数学学报,2002,19(2):98-102.
[93]何昌.关于Banach空间中渐进非扩张型映像具混合误差的迭代序列的收敛问题.工程数学学报.2003,20(3):75-81.
[94]高中喜,黄廷祝,王转德.AOR迭代法的误差估计.电子科技大学学报.电子科技大学学报,2007,36(2):334-336.
[95]Chernov A,Maischak M,Stephan E P.A priori error estimates for hp penalty BEM for contact problems in elasticity.Computer Methods in Applied Mechanics and Engineering,(196)2007:3871-3880.
[96]Rodolfo A,Frederic V.A multiscale a posteriori error estimate.Computer Methods in Applied Mechanics and engineering,(194)2005:2077-2094.
[97]Ding J,Jin C M,Zhou A H.A posteriori error estimates for Markov approximations of Frobenius-Perron operators.Nonlinear Analysis,(67)2007:763-772
[98]Cao Y,Petzold L.An error estimate for matrix equations.Applied Numerical Mathematics,50(2004):395-407.
[99]Hodgson D J.Adaptive estimation of cointegrating regressions with ARMA errors.Journal of Econometrics,1998,85(2):231-267.
[100]Bravo J M,Alamo T,Redondo M J et al.An algorithm for bounded-error identification of nonlinear systems based on DC functions.Automatica,44(2008):437-444.
[101]Ovtchinnikov E.Cluster robust error estimates for the Rayleigh-Ritz approximation Ⅱ:Estimates for eigenvalues.Linear Algebra and its Applications,415(2006):188-209.
[102]李瑞遐.边界积分方程解的一个后验误差估计.华东理工大学学报,2002,28(4):426-428.
[103]Verma S P,Jorge A,Santoyo E.Application of the error propagation theory in estimates of static formation temperatures in geothermal and pertroleum boreholes.Energy Conversion and Management,47(2006):3659-3671.
[104]Hauser E B,Pazos R P,Vilhena M T.An error bound estimate and convergence of the Nodal-LTSN solution in a rectangle.Annals of Nuclear Energy,32(2005):1146-1156.
[105]Zhan Y Q,Shen D G.An adaptive error penalization method for training an efficient and generalized SVM.Pattern Recognition,(39)2006:342-350.
[106]王兆清,李淑萍.多边形单元平均值插值的误差估计及应用.计算物理,2007,24(2):217-221.
[107]葛志强,黄培康.非线性递推最小模型误差估计.宇航学报,2001,22(3):12-19.
[108]Hong M,Torsten S,Zheng W X.Accuracy analysis of bias-eliminating least squares estimates for errors-in-variable systems.Automatica,(43)2007:1590-1596.
[109]Singh S N,Zhang R.Adaptive output feedback control of spacecraft with flexible appendages by modeling error compensation.Acta Astronautica,(54)2004:229-243.
[110]赵前程,罗晓莉,邓善熙.基于特征模型的形状误差估计新方法.仪器仪表学报,2007,28(9):1629-1634.
[111]张雪松,何奔腾.基于误差估计的变压器励磁涌流识别原理.中国电机工程学报,2005,25(3):94-99.
[112]高建波,胡鑫尧,胡东成.基于误差估计的非线性红外光谱波长选择法.清华大学学报(自然科学版),2002,42(1):118-120.
[113]龚国庆,范子杰,刘寒冰.基于应力超收敛恢复技术的广义特征值问题后验误差估计.工程力学,2004,21(3):111-117.
[114]张礼勇,王学伟,周海波等.加窗插值FFT谐波分析算法的误差估计.计量学报,2004,25(4):353-356.
[115]Efromovich S.Adaptive estimation of error density in nonparametric regression with small sample size.Journal of Statistical Planning and Inference,(137)2007:363-378.
[116]Kuzmin D,Hannukainen A,Korotov S.A new a posteriori error estimate for convection-reaction-diffusion problems.Journal of Computational and Applied Mathematics,2008,218(1):70-78.
[117]Javier F,Bosco G A,Novo J.A posteriori error estimates for fully discrete nonlinear parabolic problems.Computer Methods in Applied Mechanics and Engineering,(196)2007:3462-3474.
[118]杨日杰,何友,田宝国.双基地航空声呐搜潜距离误差估计.兵工学报,2004,25(5):540-543.
[119]Hur J,Kim J W.A hybrid classification method using error pattern modeling.Expert Systems with Applications,(34)2008:231-241
[120]丁士俊,陶本藻.自然样条半参数模型与系统误差估计.武汉大学学报(信息科学版),2004,29(11):964-967.
[121]马永开,唐小我.基于跟踪误差的证券组合投资决策模型研究.系统工程理论与实践,2001,12:11-16.
[122]Puebla H,Alvarez-Ramirez J.Suppression of stick-slip in drillstrings:A control approach based on modeling error compensation.Journal of Sound and Vibration,(310)2008:881-901.
[123]Somo S,Hong H P.Modeling error analysis of shear predicting models for RC beams.Structural Safety,(28)2006:217-230.
[124]Duffey R B.Predicting tragedies,accidents,errors and failures using a learning environment.Science and Technology of Advanced Materials,2005,6(8):878-882.
[125]夏新涛,王中宇,朱坚民等.制造系统的非统计调整与误差预测.机械工程学报2005,41(1):135-139.
[126]张红梅,邓正隆,林玉荣.一种基于模型误差预测的UKF方法.航空学报,2004,25(6):598-601.
[127]李骥,张洪钺.用神经网络估计模型误差的预测滤波算法.控制与决策.2005,20(2):183-186.
[128]Javaux D.A method for predicting errors when interacting with finite state system.Reliability Engineering & System Safety,(75)2002:147-165.
[129]王晟,杨树兴,张成.基于误差模型和扰动量辨识的射程修正方法.弹道学报,2006,18(1):42-44.
[130]赵建东.仿人机器人行走误差自整定模糊控制研究:(博士学位论文).北京:清华大学,2005.
[131]朱家强,郭锁凤.一种在线神经网络在补偿飞机模型不确定性误差中的应用.南京航空航天大学学报,2003,35(1):86-89.
[132]Nikolaou M.Model predictive controllers:A critical synthesis of theory and industrial needs.Advances in Chemical Engineering,(26)2001:131-204.
[133]Qin S J,Badgwell T A.A survey of industrial model predictive control technology.Control Engineering Practice,2003,11(7):733-764.
[134]王稼祥,何信.误差补偿和时滞辨识预测控制算法.电子科技大学学报,2005,34(6):817-820.
[135]Mahata K.An improved bias-compensation approach for errors-in-variables model identification.Automatica,2007,43(8):1339-1354.
[136]唐杰,张福炎.一种基于误差控制的网格多分辨模型生成算法.计算机学报,2005,28(9):1534-1539.
[137]Stove J,Jin Y C,Farrell J.Adaptive control for output feedback nonlinear systems in the presence of modeling errors.Automatica,38(2002):1761-1767.
[138]徐宏,胡自化,张平等.基于冗余误差控制的非均匀有理B样条曲线插补算法研究.计算机集成制造系统,2007,13(5):961-966.
[139]YEH S S,HSU P L.Adaptive-feedrate interpolation for parametric curves with a confined chord error.Computer-Aided Design,2002,34(3):229-237.
[140]滕宇,段广仁.矩阵二阶系统误差反馈调节问题的解.哈尔滨工业大学,2007,39(5):691-695.
[141]Chen Z M,Ricardo H N,Schmidt A.A characteristic Galerkin method with adaptive error control for the continuous casting problem.Computer Methods in Applied Mechanics and Engineering,(189)2000:249-276.
[142]Ludwig K,Speiser B.An object-oriented problem solving environment for electrochemistry.Part 5.A differential-algebraic approach to the error control of adaptive algorithms.Journal of Electroanalytical Chemistry,(608)2007:91-101.
[143]Muramatsu E,Watanabe K.Feedback error learning control without recourse to positive realness.IEEE Transactions on Automatic Control,2004,49(10):1762-1767.
[144]Nakanishi J,Schaal S.Feedback error learning and nonlinear adaptive control.Neural Network,2004,17(10):1453-1465.
[145]Liuzzo S,Marino R,Tomei P.Adaptive learning control of linear systems by output error feedback.Automatica,(43)2007:669-676.
[146]Ruan X G,Ding M X,Gong D X et al.On-line adaptive control for inverted pendulum balancing based on feedback-error-learning.Neurocomputing 70(2007):770-776.
[147]吴振顺,肖原,赖海江.复合误差反馈δ-MRAC控制器及其在电液伺服系统中的应用研究.机械工程学报2004,40(2):21-24.
[148]邵诚,顾兴源.一种带有模型误差反馈的鲁棒自校正控制器.控制理论与应用,1994,11(5):604-609.
[149]孙克辉,张泰山.超混沌系统的多变量驱动误差反馈控制同步方法.中南大学学报(自然科学版),2005,36(4):653-657.
[150]李士勇编著.模糊控制·神经控制和智能控制论.哈尔滨:哈尔滨工业大学,1998,9.
[151]Cai X D,Zhang N,Venayagamoorthy G K et al.Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm.Neurocomputing,70(2007)2342-2353.
[152]Hassan K.K著.朱义胜,董辉,李作洲译.非线性系统(第3版).北京:电子工业出版社,2005.
[153]Lain H K,Lakmal D S.BMI-based stability and performance design for fuzzy-model-based control systems subject to parameter uncertainties.IEEE Trans.On Systems Man and Cybernetics-Part B:Cybernetics,2007,37(3):502-514.
[154]Tseng C S,Chen B S,Uang H J.Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model.IEEE Trans.Fuzzy Systems.2001,9(3):381-392.
[155]Boulkroune A,Tadjine M,M'Saad Met al.How to design a fuzzy adaptive controller based on observers for uncertain affine nonlinear systems.Fuzzy Sets and Systems,2008,159(8):926-948.
[156]Wang L X,Mendel J M.Fuzzy basis functions,universal approximation,and orthogonal least square learning.IEEE Trans.Neural Networks,1992,3(5):807-814.
[157]王立新著.王迎军译.模糊系统与模糊控制教程.北京:清华大学出版社,2003,6.
[158]Purwar S,Kar I N,Jha A N.Adaptive control of robot manipulations using fuzzy logic systems under actuator constraints.Fuzzy Sets and Systems,2005,152(3):651-664.
[159]Zergeroglu E,Dixon W,Haste D et al.A composite adaptive output feedback tracking controller for robotic manipulators.Robotica,1999,17(6):591-600
[160]Farza M,M'saad M,Rossignol L.Observer design for a class of MIMO nonlinear systems.Automatica,2004,40(1):135-143.
[161]Xu A,Zhang Q.Nonlinear system fault diagnostic based on adaptive estimation.Automatica,40(2004):1181-1193.
[162]Lin C J,Chen C H.Nonlinear system control using compensatory neuro-fuzzy networks.IEICE Transactions on Fundamentals of Electronics,Communications and Computer Sciences.2003,E86(A9): 2309-2316.
[163]Lin C J,Chen C H.Identification and prediction using recurrent compensatory neuron-fuzzy systems.Fuzzy Sets and Systems,150(2005):307-330.
[164]liguni Y,Sakai H,Tokumaru H.A real-time learning algorithm for a multi-layered neural network based on the extended Kalman filter.IEEE Transactions on Signal Processing,1992,40(4):959-966.
[165]Ljung L,Soderstrom T.Theory and practice ofrecursive identification.Cambridge,MA:MIT Press,1983.
[166]Zhang G C,Ren G.Ship track adaptive control using error estimator.The 5th International Conference on Fuzzy Systems and Knowledge Discovery,Jinan,China,FSKD 2008:639-644.
[167]张桂臣,任光.基于航迹误差预测模型的船舶自适应控制.大连海事大学学报,2007,33(4):37-41.
[168]Ayman B M,Hussein W E-T.On the use of the capability polar plots program for dynamic positioning systems for marine vessels.Ocean Engineering,33(2006):1070-1089.
[169]Hung D N.Multitask automatic manoeuvring systems using recursive optimal control algorithms.The 2nd International Conference on Communications and Electronics,Hoian,ICCE2008:54-59.
[170]Fossen T I.Marine control system:guidance,navigation,and control of ships,rigs and underwater vehicles.Trongheim,Norway:Marine Cybernetics,2002.
[171]Nguyen H D.Recursive optimal manoeuvring systems for maritime search and rescue mission.Proceeding of OTO'04,Kobe JAPAN,2004,Vol.2:911-918.
[172]Fossen T.I.Guidance and control of ocean vehicles.New York:John Wiley & Sons,1994.
[173]Wang L X.Adaptive fuzzy systems and control:design and stability analysis.New Jersey:Prentice-Hall,1994.
[174]Iracleous D P,Alexandridis A T.A multi-task automatic generation control for power regulation.Electric Power Systems Research,2005,73(3):275-285.
[175]Machowski J,Bialek J,Bumby J.Power system dynamics and stability.New York:John Wiley &Sons,1997.
[176]张桂臣,任光.人船一体系统模型复合控制的研究,大连海事大学学报,2008,34(2):122-125.
[177]张桂臣,任光.船舶航迹复合预测控制模型.交通运输工程学报,2007,12,7(6):41-45.
[178]张桂臣,任光.基于误差预报模型的船舶航迹自适应控制.哈尔滨工程大学学报,2007,28(增刊):27-32.
[179]张桂臣,任光.在线自整定PID船舶自动舵的设计与实现.中国造船,2007,48(3):44-49.
[180]张桂臣,任光.在线自适应误差模型船速调节器的研究.内燃机工程.2009,30(1).
[181]Slotine J J,Sastry S S.Tracking control of nonlinear systems using sliding surfaces with application to robot manipulations.International Journal of Control,1982,36(5):833-843.
[182]Lee H,Kim E,Kang H J et al.A new sliding -mode control with fuzzy boundary layer.Fuzzy Sets and Systems,2001,120(1):135-143.
[183]Huang Y J,Kuo T C.Robust output tracking control for nonlinear time-varying robotic manipulators.Electrical Engineering,87(2005):47-55.
[184]Thierry,V C,Costas V著.王奔译.电力系统电压稳定性.北京:电子工业出版社,2008.
[185]Chen J,Tang P C.A sliding mode current control scheme for PWM brushless DC motor drives.IEEE Transactions on Power Electronics,1999,14(3):541-551.
[186]Baik I C,Kim K H,Youn M J.Robust nonlinear speed control of PM synchronous motor using boundary layer integral sliding mode control technique.IEEE Transactions on Control Systems Technology,2000,8(1):47-54.
[187]Lin F J,Wal R J,Chen H P.A PM synchronous motor drive with an on-line trained fuzzy neural network controller.IEEE Transactions on Energy Conversion,1998,13(4):319-325.
[188]Burton T,Sharpe D,Jenkins Net al.Wind energy handbook.New York:Wiley,2001.
[189]Heir S.Grid integration of wind energy conversion systems.New York:Wiley,1998.
[190]Maalawi K Y,Badr M A.A practical approach for selecting optimum wind rotors.Renew Energy,28(2003):803-822.
[191]Murdoch A,Winkelman J R,Javid S H et al.Control design and performance ananlysis of a 6MW wind turbine generator.IEEE Transactions Power Apparatus Systems,1983,PAS-102(6):1340-1347.
[192]Lahiri S K,Ghanta K C.Development of an artificial neural network correlation for prediction of hold-up of slurry transport in pipelines.Chemical Engineering Science,2008,63(6):1497-1509.
[2]王元放,周宏仁,敬忠良.“系统的系统”综述.系统仿真学报,2007,19(6):1182-1185.
[3]Asgeir J S.Structural issues in the design and operation of marine control system.Annual Reviews in Control,2005,29(1):125-149.
[4]George G D,Areitotelis V K,Christos A F.Synthesis,design and operation optimization of a marine energy system.Energy,33(2008):180-188.
[5]Amerongen J V.Adaptive steering of ships-a model reference approach.Automatica,1984,20(1):3-14.
[6]Kallstrom C G.Adaptive autopilots for tankers.Automatica,1979,15(2):241-254.
[7]Yang Y S.Neural network adaptive control for ship automatic steering.Proceedings of International Conference of Young Investigators on Information,Computer and Control,Beijing,1994:231-236.
[8]Layne J R,Passino K M.Fuzzy model reference learning control for cargo ship steering.IEEE Transactions on Control Systems Magazine,1993,13(6):23-34.
[9]Yang Y S,Zhou C J,Jia X.Robust adaptive fuzzy control and its application to ship roll stabilization.Information Sciences,2002,142(1):177-194.
[10]林叶锦.船舶运动模糊神经网络控制系统的研究:(博士学位论文).大连:大连海事大学,2007.
[11]王先洲.船舶及潜艇操纵中的鲁棒控制研究:(博士学位论文).武汉:华中科技大学,2008.
[12]Do K D,Jiang Z P.Robust global stabilization of underactuated ships on a linear course:state and output feedback.International Journal of Control,2003,76(1):1-17.
[13]Yoon H K,Rhee K P.Identification of hydrodynamic coefficients in ship maneuvering equations of motion by estimation-before-modeling technique.Ocean Engineering,30(2003):2379-2404.
[14]Jiang Z P.Global tracking control of underactuated ships by Lyapunov's direct method.Automatica,2002,38(2):301-309.
[15]Pettersen K Y,Nijmeijer H.Underactuated ship tracking control:Theory and experiments.International Journal of Control,2001,74(14):1435-1446.
[16]Selvam R P,Bhattaeharyya S K,Haddara M R.A frequency domain system identification method for linear ship manoeuvring.International Shipbuilding Progress,52(2005):5-27.
[17]Ivar-Andr F I,Irme J,Thor I F.Formation control of marine surface craft:A Lagrangian approach.Oceanic Engineering,2006,31(4):922-934.
[18]Cimen T,Banks S E Nonlinear optimal tracking control with application to super-tankers for autopilot design.Atuomatica,2004,40(11):1845-1863.
[19]Shim D K,Park J H,Pramod P,et al.Reducing automotive engine speed fluctuation at idle.IEEE Transactions on Control System Technology,1996,4(4):404-409.
[20]Carlucci A P,Ficarella A,Laforgia D.Control of the combustion behaviour in a diesel engine using early injection and gas addition.Applied Thermal Engineering,26(2006):2279-2286.
[21]Jankovic M,Jankovic M,Kolmanovsky I.Constructive Lyapunov control design for turbocharged diesel engine.IEEE Transactions on Control System Technology,2002,8(2):288-299.
[22]Gimitrios T H.Prediction of marine diesel engine performance under fault conditions.Applied Thermal Engineering,20(2000):1753-1783.
[23]Zhang H,Li Z G,Chen Z N.Application of grey modeling method to fitting and forecasting wear trend of marine diesel engines.Tribology International,36(2003):753-756.
[24]黄曼磊,王常虹.船舶电站柴油机双脉冲H∞调速器的研究.控制理论与应用,2007,24(2):283-288.
[25]Ericsen T,Hingorani N,Khersonsky Y.Power electronics and future marine electrical system.IEEE Transactions on Industry Applications,2006,42(1):155-163.
[26]Mendes J C,Saavedra O R,Feitosa S A.A parallel complete method for real-time security analysis in power system.Electric Power System Research,2000,56(1):27-34.
[27]Zivi E.Design of robust shipboard power automation systems.Annual Review in Control,2005,29(2):261-272.
[28]Burden R L,Faires J D.Numerical analysis.Boston:PWS-Kent Pub.Co.,1993.
[29]Draper N R,Smith H.Applied regression analysis.New York:John Wiley & Sons,1981.
[30]Shah S,Palmieri F,Datum M.Optimal filtering algorithms for fast learning in feed-forward neural networks.Neural Networks,1992,5(5):779-787.
[31]shinskey F G著.萧德云,吕伯明译.过程控制系统一应用、设计与整定.北京:清华大学出版社,2004.
[32]Gawthrop P J.Self-tuning PID controller:Algorithms and implementation.IEEE Transactions on Automatic Control,1986,31(3):201-209.
[33]Gyongy I J,Clarke D W.On the automatic tuning and adaptation of PID controllers.Control Engineering Practice,2006,14(2):149-163.
[34]Hang C C,Astrom K J,Wang Q G..Relay feedback auto-tuning of process controllers-a tutorial review.Journal of Process Control,2002,12(1):143-162.
[35]Ho W K,Hong Y,Hansson Aet al.Relay auto-tuning of PID controllers using iterative feedback tuning.Automatica,2003,39(1):149-157.
[36]Astrom K J,Hagglund T.Automatic tuning of simple regulators with specifications on phase and amplitude margins.Automatica,20(1984):645-651.
[37]Ho W K,Hang C C,Cao L S.Tuning of PID controllers based on gain and phase margin specifications. Automatica,1995,31(3):497-502.
[38]Astrom K J,Hagglind T.Industrial adaptive controllers based on frequency response techniques.Automatica,1991,27(4):599-609.
[39]Lee T H,Hang C C,Ho W K et al.Implementation of a knowledge-based PID auto-tuner.Automatica,1993,29(4):1107-1113.
[40]Kim S M,Han W Y.Induction motor servo drive using robust PID-like neuron-fuzzy controller.Control Engineering Practice,2006,14(5):481-487.
[41]Lin F J,Hwang W J,Wai R J.A supervisory fuzzy neural network control system for tracking periodic inputs.IEEE Transactions on Fuzzy Systems,1999,7(1):41-52.
[42]Chen C T,Chang W D.A feedforward neural network with function shape auto-tuning.Neural Networks,1996,9(4):627-641.
[43]Omatu S,Khalid M,Yusof R.Neuro-control and its applications.London:Springer,1995.
[44]马建伟.多指标满意PID控制设计研究:(博士学位论文).南京:南京理工大学,2005.
[45]周晓兵.基于TCP/IP网络的延时建模及网络先进PID控制器研究:(博士学位论文).上海:上海大学,2008.
[46]李银伢.满意PID控制器设计理论:(博士学位论文).南京:南京理工大学,2007.
[47]Koivo H N,Tanttu J T.Tuning of PID controller-survey of SISO and MIMO.Preprints of IFAC International Symposium on Intelligent Tuning and Adaptive Control,Singapore,1991.
[48]Pentirmen J,Koivo H N.Multivarable tuning regulators for unknown systems.Automatica,1997,33(4):393-398.
[49]Yusof R,Omatu S.A multivariable self-tuning PID controller.International Journal of Control,1993,57(6):1387-1403.
[50]靳其兵,吴斌多指标相容下的多变量PID控制器设计.北京化工大学学报,2008,35(3):89-92.
[51]Gaing Z L.A particle swarm optimization approach for optimum design of PID controller in AVR system.IEEE Transactions on Energy Conversion,2004,19(2):384-391.
[52]Mukherjee V,Ghoshal S P.Intelligent particle swarm optimized fuzzy PIDcontroller for AVR system.Electric Power System Research,77(2007):1689-1698.
[53]Ghoshal S P.Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control.Electric Power System Research,27(2004):203-212.
[54]薛亚丽,李东海,吕崇德.汽轮发电机组多变量PID控制器的优化设计.动力工程,2005,25(5):668-741.
[55]廖少明,汪敏,侯学渊.盾构近距离施工的IMC-PID控制模型研究.岩石力学与工程学报,2006,25(S2):4132-4138.
[56]綦守荣,王东风,韩璞等.基于鲁棒整定的球磨机系统多变量PID控制,系统仿真学报,2005,17(12):3001-3003.
[57]曹健,王俊凯,吴盛林等.动态矩阵(DMC)-PID串级预测控制策略在新型叶片连续回转马达位置伺服系统中的应用.宇航学报,2006,27(4):625-629.
[58]彭辉,彭晓燕.广义预测补偿-自校正PID串级控制算法.中国有色金属学报,1995,5(4):158-162.
[59]李林欢,苏宏业,褚健.一类多输入多输出系统的预测PID控制算法仿真.系统仿真学报,2004,16(3):495-503.
[60]刘红军,韩璞,王东风等.灰色预测模糊PID控制在汽温控制系统中的应用.系统仿真学报,2004,16(8):1839-1848.
[61]彭道刚,张浩,杨平等.基于灰色预测的汽温模糊免疫PID控制.动力工程,2007,27(1):72-75.
[62]韩敏,郭伟,王金城.基于RBF网络的大滞后系统自适应预测PID控制器.仪器仪表学报,2005,26(10):1039-1043.
[63]陶文华,李平,穆玲.基于神经元的自适应预测PID控制.抚顺石油学院学报,2002,22(2):67-69.
[64]杨智,高靖.时变大时滞神经元自适应预测PID控制器.仪器仪表学报,2000,21(3):300-303.
[65]牛玉刚,杨成梧,赵建丛.基于多步预测的PID型神经网络控制.南京理工大学学报,2000,24(3):199-202.
[66]明学星,王建国,吕震中等.基于混沌理论的预测PID控制器参数优化研究.热能动力工程,2008,23(2):178-182.
[67]牛培峰,张君,关新平.基于遗传算法的混沌系统二自由度比例-积分-微分控制研究.物理学报,2007,56(7):3759-3765.
[68]丁丰平,张华强,苏振.基于预测控制的Fuzzy-PID控制器算法研究.电子器件,2007,30(6):2152-2158.
[69]任正云,邵惠鹤,张立群.几种不稳定滞后对象的预测PID控制.控制与决策,2004,19(6):671-674.
[70]张燕,陈增强,袁著祉.基于Taylor逼近的非线性系统PID型多步预测控制.控制与决策,2004,19(4):448-451.
[71]李林欢,刘斌,苏宏业等.基于输出误差预测的模糊预测PID控制及应用.浙江大学学报(工学版),2004,38(7):826-830.
[72]沈国江,孙优贤,马婷芳.基于误差性能指标的强时变时滞系统鲁棒PID继电自整定控制技术.中国造纸学报,2002,17(1):93-95.
[73]刘金琨.先进PID控制MATLAB仿真(第2版).北京:电子工业出版社,2004.
[74]Chang W D,Hwang R C,Hsieh J G.A self-tuning PID control for a class of nonlinear system based on the Lyapunov approach.Journal of Process Control,12(2002):233-242.
[75]Chang W D,Yan J J.Adaptive robust PID controller design based on a sliding mode for uncertain chaotic systems.Chaos,Solitons and Fractals,26(2005):167-175.
[76]张晓宇,王子才,高伟巍.基于ITAE准则的质量矩拦截弹鲁棒控制研究.系统工程与电子技术,2007,29(12):2101-2105.
[77]王曦,林永霖,吴永康.H∞控制在飞行/推进综合控制系统中的应用.航空动力学报,2004,19(5):695-702.
[78]王应明,傅国伟.基于不同误差准则和范数的组合预测方法研究.控制与决策,1994,9(1):20-28.
[79]茅健.基于数学定义的公差建模与误差评定技术的研究:(博士学位论文).杭州:浙江大学,2007.
[80]丁瑞强.非线性误差增长理论与可预报性研究:(博士学位论文).北京:中国科学院研究生院,2007.
[81]Klein A,Kaleh G K,Baier P W.Zero forcing and minimum mean square error equalization for multiuser detection in code-division multiple-access channels.IEEE Trans.On Vehicular Technologu,1996,45(2);276-287.
[82]高松,贺仁睦,马进等.电力系统动态仿真误差评定准则研究.电力系统自动化,2006,30(4):6-10.
[83]杨新刚,黄玉美,李艳等.三维测头探测误差的评定准则及高精度评定方法研究.计量学报,2008,29(3):207-210.
[84]Hou H,Yang J H.An electro-acoustics impedance error criterion and its application to active noise control.Applied Acoustics,65(2004):485-499.
[85]Li X,Fang R W.Error criteria analysis and robust data fusion.IEEE ICASSP,Australia,1994,37-39.
[86]唐颖莉,郑时雄,刘桂雄等.基于熵概念的机器人动态误差理论的研究.机械科学与技术,2001,20(5):646-648.
[87]Qian W M,Cai G X.Strong approximability of wavelet estimate in semiparamtric regression mode.Science in China(series A),1999,29(3):233-240.
[88]Qian W M,Cai G X,Jiang F Y.Error variance of wavelet estimate in semiparamtric regression.Chinese Journal of Annual of Maths,2000,21(A 3):341-350.
[89]Yan Z Z,Wu W H,Nie Z K.Near neighbour estimate in semiparamtric Regression model:The martingale difference error sequence case.Chinese Journal of Applied Probability and Statistics,2001,17(1):44-50.
[90]胡宏昌,孙海燕.半参数回归模型小波估计的稳定地依分布收敛性-误差为鞅差序列情形.武汉大学学报(理学版),2003,49(5):571-574.
[91]Baeza-Baeza J J,Ramis-Ramos G.Analysis of the sensitivity to the systematic error in least-squares regression models.Analytica Chimica Acta,515(2004):15-21.
[92]曾六川.非一致光滑的Banach空间中强增生型变分包含问题解的带误差的Ishikawa迭代逼近.工程数学学报,2002,19(2):98-102.
[93]何昌.关于Banach空间中渐进非扩张型映像具混合误差的迭代序列的收敛问题.工程数学学报.2003,20(3):75-81.
[94]高中喜,黄廷祝,王转德.AOR迭代法的误差估计.电子科技大学学报.电子科技大学学报,2007,36(2):334-336.
[95]Chernov A,Maischak M,Stephan E P.A priori error estimates for hp penalty BEM for contact problems in elasticity.Computer Methods in Applied Mechanics and Engineering,(196)2007:3871-3880.
[96]Rodolfo A,Frederic V.A multiscale a posteriori error estimate.Computer Methods in Applied Mechanics and engineering,(194)2005:2077-2094.
[97]Ding J,Jin C M,Zhou A H.A posteriori error estimates for Markov approximations of Frobenius-Perron operators.Nonlinear Analysis,(67)2007:763-772
[98]Cao Y,Petzold L.An error estimate for matrix equations.Applied Numerical Mathematics,50(2004):395-407.
[99]Hodgson D J.Adaptive estimation of cointegrating regressions with ARMA errors.Journal of Econometrics,1998,85(2):231-267.
[100]Bravo J M,Alamo T,Redondo M J et al.An algorithm for bounded-error identification of nonlinear systems based on DC functions.Automatica,44(2008):437-444.
[101]Ovtchinnikov E.Cluster robust error estimates for the Rayleigh-Ritz approximation Ⅱ:Estimates for eigenvalues.Linear Algebra and its Applications,415(2006):188-209.
[102]李瑞遐.边界积分方程解的一个后验误差估计.华东理工大学学报,2002,28(4):426-428.
[103]Verma S P,Jorge A,Santoyo E.Application of the error propagation theory in estimates of static formation temperatures in geothermal and pertroleum boreholes.Energy Conversion and Management,47(2006):3659-3671.
[104]Hauser E B,Pazos R P,Vilhena M T.An error bound estimate and convergence of the Nodal-LTSN solution in a rectangle.Annals of Nuclear Energy,32(2005):1146-1156.
[105]Zhan Y Q,Shen D G.An adaptive error penalization method for training an efficient and generalized SVM.Pattern Recognition,(39)2006:342-350.
[106]王兆清,李淑萍.多边形单元平均值插值的误差估计及应用.计算物理,2007,24(2):217-221.
[107]葛志强,黄培康.非线性递推最小模型误差估计.宇航学报,2001,22(3):12-19.
[108]Hong M,Torsten S,Zheng W X.Accuracy analysis of bias-eliminating least squares estimates for errors-in-variable systems.Automatica,(43)2007:1590-1596.
[109]Singh S N,Zhang R.Adaptive output feedback control of spacecraft with flexible appendages by modeling error compensation.Acta Astronautica,(54)2004:229-243.
[110]赵前程,罗晓莉,邓善熙.基于特征模型的形状误差估计新方法.仪器仪表学报,2007,28(9):1629-1634.
[111]张雪松,何奔腾.基于误差估计的变压器励磁涌流识别原理.中国电机工程学报,2005,25(3):94-99.
[112]高建波,胡鑫尧,胡东成.基于误差估计的非线性红外光谱波长选择法.清华大学学报(自然科学版),2002,42(1):118-120.
[113]龚国庆,范子杰,刘寒冰.基于应力超收敛恢复技术的广义特征值问题后验误差估计.工程力学,2004,21(3):111-117.
[114]张礼勇,王学伟,周海波等.加窗插值FFT谐波分析算法的误差估计.计量学报,2004,25(4):353-356.
[115]Efromovich S.Adaptive estimation of error density in nonparametric regression with small sample size.Journal of Statistical Planning and Inference,(137)2007:363-378.
[116]Kuzmin D,Hannukainen A,Korotov S.A new a posteriori error estimate for convection-reaction-diffusion problems.Journal of Computational and Applied Mathematics,2008,218(1):70-78.
[117]Javier F,Bosco G A,Novo J.A posteriori error estimates for fully discrete nonlinear parabolic problems.Computer Methods in Applied Mechanics and Engineering,(196)2007:3462-3474.
[118]杨日杰,何友,田宝国.双基地航空声呐搜潜距离误差估计.兵工学报,2004,25(5):540-543.
[119]Hur J,Kim J W.A hybrid classification method using error pattern modeling.Expert Systems with Applications,(34)2008:231-241
[120]丁士俊,陶本藻.自然样条半参数模型与系统误差估计.武汉大学学报(信息科学版),2004,29(11):964-967.
[121]马永开,唐小我.基于跟踪误差的证券组合投资决策模型研究.系统工程理论与实践,2001,12:11-16.
[122]Puebla H,Alvarez-Ramirez J.Suppression of stick-slip in drillstrings:A control approach based on modeling error compensation.Journal of Sound and Vibration,(310)2008:881-901.
[123]Somo S,Hong H P.Modeling error analysis of shear predicting models for RC beams.Structural Safety,(28)2006:217-230.
[124]Duffey R B.Predicting tragedies,accidents,errors and failures using a learning environment.Science and Technology of Advanced Materials,2005,6(8):878-882.
[125]夏新涛,王中宇,朱坚民等.制造系统的非统计调整与误差预测.机械工程学报2005,41(1):135-139.
[126]张红梅,邓正隆,林玉荣.一种基于模型误差预测的UKF方法.航空学报,2004,25(6):598-601.
[127]李骥,张洪钺.用神经网络估计模型误差的预测滤波算法.控制与决策.2005,20(2):183-186.
[128]Javaux D.A method for predicting errors when interacting with finite state system.Reliability Engineering & System Safety,(75)2002:147-165.
[129]王晟,杨树兴,张成.基于误差模型和扰动量辨识的射程修正方法.弹道学报,2006,18(1):42-44.
[130]赵建东.仿人机器人行走误差自整定模糊控制研究:(博士学位论文).北京:清华大学,2005.
[131]朱家强,郭锁凤.一种在线神经网络在补偿飞机模型不确定性误差中的应用.南京航空航天大学学报,2003,35(1):86-89.
[132]Nikolaou M.Model predictive controllers:A critical synthesis of theory and industrial needs.Advances in Chemical Engineering,(26)2001:131-204.
[133]Qin S J,Badgwell T A.A survey of industrial model predictive control technology.Control Engineering Practice,2003,11(7):733-764.
[134]王稼祥,何信.误差补偿和时滞辨识预测控制算法.电子科技大学学报,2005,34(6):817-820.
[135]Mahata K.An improved bias-compensation approach for errors-in-variables model identification.Automatica,2007,43(8):1339-1354.
[136]唐杰,张福炎.一种基于误差控制的网格多分辨模型生成算法.计算机学报,2005,28(9):1534-1539.
[137]Stove J,Jin Y C,Farrell J.Adaptive control for output feedback nonlinear systems in the presence of modeling errors.Automatica,38(2002):1761-1767.
[138]徐宏,胡自化,张平等.基于冗余误差控制的非均匀有理B样条曲线插补算法研究.计算机集成制造系统,2007,13(5):961-966.
[139]YEH S S,HSU P L.Adaptive-feedrate interpolation for parametric curves with a confined chord error.Computer-Aided Design,2002,34(3):229-237.
[140]滕宇,段广仁.矩阵二阶系统误差反馈调节问题的解.哈尔滨工业大学,2007,39(5):691-695.
[141]Chen Z M,Ricardo H N,Schmidt A.A characteristic Galerkin method with adaptive error control for the continuous casting problem.Computer Methods in Applied Mechanics and Engineering,(189)2000:249-276.
[142]Ludwig K,Speiser B.An object-oriented problem solving environment for electrochemistry.Part 5.A differential-algebraic approach to the error control of adaptive algorithms.Journal of Electroanalytical Chemistry,(608)2007:91-101.
[143]Muramatsu E,Watanabe K.Feedback error learning control without recourse to positive realness.IEEE Transactions on Automatic Control,2004,49(10):1762-1767.
[144]Nakanishi J,Schaal S.Feedback error learning and nonlinear adaptive control.Neural Network,2004,17(10):1453-1465.
[145]Liuzzo S,Marino R,Tomei P.Adaptive learning control of linear systems by output error feedback.Automatica,(43)2007:669-676.
[146]Ruan X G,Ding M X,Gong D X et al.On-line adaptive control for inverted pendulum balancing based on feedback-error-learning.Neurocomputing 70(2007):770-776.
[147]吴振顺,肖原,赖海江.复合误差反馈δ-MRAC控制器及其在电液伺服系统中的应用研究.机械工程学报2004,40(2):21-24.
[148]邵诚,顾兴源.一种带有模型误差反馈的鲁棒自校正控制器.控制理论与应用,1994,11(5):604-609.
[149]孙克辉,张泰山.超混沌系统的多变量驱动误差反馈控制同步方法.中南大学学报(自然科学版),2005,36(4):653-657.
[150]李士勇编著.模糊控制·神经控制和智能控制论.哈尔滨:哈尔滨工业大学,1998,9.
[151]Cai X D,Zhang N,Venayagamoorthy G K et al.Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm.Neurocomputing,70(2007)2342-2353.
[152]Hassan K.K著.朱义胜,董辉,李作洲译.非线性系统(第3版).北京:电子工业出版社,2005.
[153]Lain H K,Lakmal D S.BMI-based stability and performance design for fuzzy-model-based control systems subject to parameter uncertainties.IEEE Trans.On Systems Man and Cybernetics-Part B:Cybernetics,2007,37(3):502-514.
[154]Tseng C S,Chen B S,Uang H J.Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model.IEEE Trans.Fuzzy Systems.2001,9(3):381-392.
[155]Boulkroune A,Tadjine M,M'Saad Met al.How to design a fuzzy adaptive controller based on observers for uncertain affine nonlinear systems.Fuzzy Sets and Systems,2008,159(8):926-948.
[156]Wang L X,Mendel J M.Fuzzy basis functions,universal approximation,and orthogonal least square learning.IEEE Trans.Neural Networks,1992,3(5):807-814.
[157]王立新著.王迎军译.模糊系统与模糊控制教程.北京:清华大学出版社,2003,6.
[158]Purwar S,Kar I N,Jha A N.Adaptive control of robot manipulations using fuzzy logic systems under actuator constraints.Fuzzy Sets and Systems,2005,152(3):651-664.
[159]Zergeroglu E,Dixon W,Haste D et al.A composite adaptive output feedback tracking controller for robotic manipulators.Robotica,1999,17(6):591-600
[160]Farza M,M'saad M,Rossignol L.Observer design for a class of MIMO nonlinear systems.Automatica,2004,40(1):135-143.
[161]Xu A,Zhang Q.Nonlinear system fault diagnostic based on adaptive estimation.Automatica,40(2004):1181-1193.
[162]Lin C J,Chen C H.Nonlinear system control using compensatory neuro-fuzzy networks.IEICE Transactions on Fundamentals of Electronics,Communications and Computer Sciences.2003,E86(A9): 2309-2316.
[163]Lin C J,Chen C H.Identification and prediction using recurrent compensatory neuron-fuzzy systems.Fuzzy Sets and Systems,150(2005):307-330.
[164]liguni Y,Sakai H,Tokumaru H.A real-time learning algorithm for a multi-layered neural network based on the extended Kalman filter.IEEE Transactions on Signal Processing,1992,40(4):959-966.
[165]Ljung L,Soderstrom T.Theory and practice ofrecursive identification.Cambridge,MA:MIT Press,1983.
[166]Zhang G C,Ren G.Ship track adaptive control using error estimator.The 5th International Conference on Fuzzy Systems and Knowledge Discovery,Jinan,China,FSKD 2008:639-644.
[167]张桂臣,任光.基于航迹误差预测模型的船舶自适应控制.大连海事大学学报,2007,33(4):37-41.
[168]Ayman B M,Hussein W E-T.On the use of the capability polar plots program for dynamic positioning systems for marine vessels.Ocean Engineering,33(2006):1070-1089.
[169]Hung D N.Multitask automatic manoeuvring systems using recursive optimal control algorithms.The 2nd International Conference on Communications and Electronics,Hoian,ICCE2008:54-59.
[170]Fossen T I.Marine control system:guidance,navigation,and control of ships,rigs and underwater vehicles.Trongheim,Norway:Marine Cybernetics,2002.
[171]Nguyen H D.Recursive optimal manoeuvring systems for maritime search and rescue mission.Proceeding of OTO'04,Kobe JAPAN,2004,Vol.2:911-918.
[172]Fossen T.I.Guidance and control of ocean vehicles.New York:John Wiley & Sons,1994.
[173]Wang L X.Adaptive fuzzy systems and control:design and stability analysis.New Jersey:Prentice-Hall,1994.
[174]Iracleous D P,Alexandridis A T.A multi-task automatic generation control for power regulation.Electric Power Systems Research,2005,73(3):275-285.
[175]Machowski J,Bialek J,Bumby J.Power system dynamics and stability.New York:John Wiley &Sons,1997.
[176]张桂臣,任光.人船一体系统模型复合控制的研究,大连海事大学学报,2008,34(2):122-125.
[177]张桂臣,任光.船舶航迹复合预测控制模型.交通运输工程学报,2007,12,7(6):41-45.
[178]张桂臣,任光.基于误差预报模型的船舶航迹自适应控制.哈尔滨工程大学学报,2007,28(增刊):27-32.
[179]张桂臣,任光.在线自整定PID船舶自动舵的设计与实现.中国造船,2007,48(3):44-49.
[180]张桂臣,任光.在线自适应误差模型船速调节器的研究.内燃机工程.2009,30(1).
[181]Slotine J J,Sastry S S.Tracking control of nonlinear systems using sliding surfaces with application to robot manipulations.International Journal of Control,1982,36(5):833-843.
[182]Lee H,Kim E,Kang H J et al.A new sliding -mode control with fuzzy boundary layer.Fuzzy Sets and Systems,2001,120(1):135-143.
[183]Huang Y J,Kuo T C.Robust output tracking control for nonlinear time-varying robotic manipulators.Electrical Engineering,87(2005):47-55.
[184]Thierry,V C,Costas V著.王奔译.电力系统电压稳定性.北京:电子工业出版社,2008.
[185]Chen J,Tang P C.A sliding mode current control scheme for PWM brushless DC motor drives.IEEE Transactions on Power Electronics,1999,14(3):541-551.
[186]Baik I C,Kim K H,Youn M J.Robust nonlinear speed control of PM synchronous motor using boundary layer integral sliding mode control technique.IEEE Transactions on Control Systems Technology,2000,8(1):47-54.
[187]Lin F J,Wal R J,Chen H P.A PM synchronous motor drive with an on-line trained fuzzy neural network controller.IEEE Transactions on Energy Conversion,1998,13(4):319-325.
[188]Burton T,Sharpe D,Jenkins Net al.Wind energy handbook.New York:Wiley,2001.
[189]Heir S.Grid integration of wind energy conversion systems.New York:Wiley,1998.
[190]Maalawi K Y,Badr M A.A practical approach for selecting optimum wind rotors.Renew Energy,28(2003):803-822.
[191]Murdoch A,Winkelman J R,Javid S H et al.Control design and performance ananlysis of a 6MW wind turbine generator.IEEE Transactions Power Apparatus Systems,1983,PAS-102(6):1340-1347.
[192]Lahiri S K,Ghanta K C.Development of an artificial neural network correlation for prediction of hold-up of slurry transport in pipelines.Chemical Engineering Science,2008,63(6):1497-1509.