网络控制系统的预测控制研究
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摘要
随着计算机、网络、通信技术和控制理论的发展,网络控制系统在工业控制领域得到越来越广泛的应用,由于闭环控制中引入了网络,所以网络控制系统中也存在许多问题需要研究。网络随机延时的存在使得系统的分析和综合变得困难,如果延时足够大则会造成系统不稳定。因为预测控制采用了多步预测、滚动优化和反馈校正等控制策略,因此能够克服过程模型的不确定性,具有控制效果好、鲁棒性强等优点,从而得到了广泛的研究和应用。本文围绕具有短延时和长延时的网络控制系统,把预测控制引入到网络控制系统的分析和设计中,提出了几种新的控制策略,并分析了系统的稳定性。本文的主要研究内容是:
针对传感器为时间驱动、控制器和执行器为事件驱动,延时小于一个采样周期的网络控制系统提出了延时预测内模控制策略。该策略包含时间戳BP神经网络延时预测方法,利用历史延时数据来预测下一个时刻延时值。根据得到的延时预测值,结合内模控制原理进行网络控制系统控制器的设计。其中延时环节采用Pade一阶展开近似表达法,并分析了延时预测对系统性能的影响。仿真结果表明,延时预测精度有保证,系统性能仅受内模控制器滤波系数α和延时预测精度的影响,网络控制系统性能有了很大的提高。
在实际的工程系统中,采样频率的选择取决于系统中信号的最高频率,网络传输延时取决于网络本身的传输特性,由此可见网络传输延时不一定小于一个采样周期。为此,本文对延时大于一个采样周期的网络控制系统开展研究,首先对一类长延时网络控制系统进行了建模,然后对长延时网络控制系统提出了两种新的预测控制策略。一种是长延时NCS预测函数控制算法,该算法在长延时网络控制系统模型的基础上利用预测函数控制原理推导出了长延时网络控制系统的预测控制律;仿真实验和加热炉实时控制实验结果均验证了对一类长延时网络控制系统的控制采用预测函数控制方法是可行的。另一种是长延时NCS动态矩阵控制方法,该方法利用算法比较简单、计算量较小、鲁棒性较强的动态矩阵控制理论对长延时网络控制系统进行控制器的设计,获得了系统的预测控制律。仿真结果表明对一类长延时网络控制系统采用动态矩阵进行控制是有效的。
网络控制系统中随机延时的存在使系统的性能变差,如果延时足够大甚至会使系统不稳定,所以本文分析了内模网络控制系统中存在的延时对系统性能的影响。由于广义预测控制、模型预测控制、动态矩阵控制等预测控制算法可以等效归结为广义内模控制,分别研究了连续内模网络控制系统和离散内模网络控制系统的稳定性问题。利用劳斯稳定性判据、李亚普诺夫方法和离散系统Z平面分析方法(朱雷稳定判据)判断内模网络控制系统的稳定性,给出了保持内模网络控制系统稳定的最大允许延时阈值τ_(MATD)。为了使内模网络控制系统获得良好的性能,在内模网络控制系统中加入延时预测环节,并分析了延时预测对系统稳定性的影响。仿真结果表明所提方法是有效的可行。
With the development of computer, network, communication and control theory, networked control systems (NCS) are getting more applications in industry control field. There are a lot of questions to be studied because of the introduction of network in the closed-loop system. It makes the system analysis and synthesis difficult due to the existence of stochastic delay in the NCS, the system performance goes to bad and unstable if the delay long enough. Based on mechanism of multiple-step prediction, rolling optimization and feedback correction, predictive control can overcome the model uncertainty and have good control performance, strong robustness, so it is widely applied and studied. Based on short delay and long delay of the NCS using predictive control in systems analysis and design, sereral new control strategies are proposed, the system stability is also investigated in this dissertation. The main research contents of this paper are as follows:
Delay prediction internal model control strategy is proposed in NCS which sensor is time-drived, controller and actuator are event-driven and the delay is less than one smpling period. This method is comprised of time-stamped BP neural network delay predictor, the historical measured delay data was used to predict the next period delay value, according to which the NCS with internal model control is designed. The delay loop is described by one-order Pade expended method approximately. The delay prediction value effect on the system is also analyzed. Simulation results illustrate that the precision of delay prediction is guaranteed, the system performance are affected by the filter coefficientαand delay prediction precision, the performance of NCS is greatly improved.
In the practical engineering system, the choice of sampling frequency is decided by the system signal's top frequency and the network communication delays rely on the network structure. Consequently, there is no corresponding relation between the network transmitted delay and sampling period, nevertheless most papers about NCS usually assume the network delay is less than a sampling period. To avoid the illogical premise, we firstly eatabilished a model of a class of long delay NCS, then two novel predictive control strategies of long delay NCS are put forword. The first one is long delay NCS predivtive functional control algorithm by this algorithm derives the predictive control law of the long delay NCS based on the model of long delay NCS. The simulation results and experiment of an electrical-resistance stove realtime control illustrate that the proposed scheme is effective for a class of long delay NCS. The other one is long delay NCS dynamic matrix control algorithm, this method derives the long delay NCS's control law by using dynamic matrix control theory which contains properties of simple algorithm, less calculation, strong robustness. The simulation results illustrate that the proposed method is effective for a class of long delay NCS.
Because of the stochastic delay in the NCS, the system performance goes to bad and even unstable if the delay long enough, the effect of delay on internal model networked control systems (IMNCS) performance is analyzed. The predictive control algorithms include generalized predictive control, model predictive control, dynamic matrix control etc can be equivalently turn over to generalized internal model control, stabilities of continuous IMNCS and discrete IMNCS are studied respectively. The IMNCS stability was discussed by using Routh criterion, state space Lyapunov stability theory and Z plane synthesis (Jury stability criterion) , therefor the maximum allowed time-delay that keep IMNCS stable was presented. In order to make better performance of IMNCS, the delay prediction loop was added and the system stability influenced by prediction was pointed. Simulation results are illustrated that the proposed scheme is very effective.
针对传感器为时间驱动、控制器和执行器为事件驱动,延时小于一个采样周期的网络控制系统提出了延时预测内模控制策略。该策略包含时间戳BP神经网络延时预测方法,利用历史延时数据来预测下一个时刻延时值。根据得到的延时预测值,结合内模控制原理进行网络控制系统控制器的设计。其中延时环节采用Pade一阶展开近似表达法,并分析了延时预测对系统性能的影响。仿真结果表明,延时预测精度有保证,系统性能仅受内模控制器滤波系数α和延时预测精度的影响,网络控制系统性能有了很大的提高。
在实际的工程系统中,采样频率的选择取决于系统中信号的最高频率,网络传输延时取决于网络本身的传输特性,由此可见网络传输延时不一定小于一个采样周期。为此,本文对延时大于一个采样周期的网络控制系统开展研究,首先对一类长延时网络控制系统进行了建模,然后对长延时网络控制系统提出了两种新的预测控制策略。一种是长延时NCS预测函数控制算法,该算法在长延时网络控制系统模型的基础上利用预测函数控制原理推导出了长延时网络控制系统的预测控制律;仿真实验和加热炉实时控制实验结果均验证了对一类长延时网络控制系统的控制采用预测函数控制方法是可行的。另一种是长延时NCS动态矩阵控制方法,该方法利用算法比较简单、计算量较小、鲁棒性较强的动态矩阵控制理论对长延时网络控制系统进行控制器的设计,获得了系统的预测控制律。仿真结果表明对一类长延时网络控制系统采用动态矩阵进行控制是有效的。
网络控制系统中随机延时的存在使系统的性能变差,如果延时足够大甚至会使系统不稳定,所以本文分析了内模网络控制系统中存在的延时对系统性能的影响。由于广义预测控制、模型预测控制、动态矩阵控制等预测控制算法可以等效归结为广义内模控制,分别研究了连续内模网络控制系统和离散内模网络控制系统的稳定性问题。利用劳斯稳定性判据、李亚普诺夫方法和离散系统Z平面分析方法(朱雷稳定判据)判断内模网络控制系统的稳定性,给出了保持内模网络控制系统稳定的最大允许延时阈值τ_(MATD)。为了使内模网络控制系统获得良好的性能,在内模网络控制系统中加入延时预测环节,并分析了延时预测对系统稳定性的影响。仿真结果表明所提方法是有效的可行。
With the development of computer, network, communication and control theory, networked control systems (NCS) are getting more applications in industry control field. There are a lot of questions to be studied because of the introduction of network in the closed-loop system. It makes the system analysis and synthesis difficult due to the existence of stochastic delay in the NCS, the system performance goes to bad and unstable if the delay long enough. Based on mechanism of multiple-step prediction, rolling optimization and feedback correction, predictive control can overcome the model uncertainty and have good control performance, strong robustness, so it is widely applied and studied. Based on short delay and long delay of the NCS using predictive control in systems analysis and design, sereral new control strategies are proposed, the system stability is also investigated in this dissertation. The main research contents of this paper are as follows:
Delay prediction internal model control strategy is proposed in NCS which sensor is time-drived, controller and actuator are event-driven and the delay is less than one smpling period. This method is comprised of time-stamped BP neural network delay predictor, the historical measured delay data was used to predict the next period delay value, according to which the NCS with internal model control is designed. The delay loop is described by one-order Pade expended method approximately. The delay prediction value effect on the system is also analyzed. Simulation results illustrate that the precision of delay prediction is guaranteed, the system performance are affected by the filter coefficientαand delay prediction precision, the performance of NCS is greatly improved.
In the practical engineering system, the choice of sampling frequency is decided by the system signal's top frequency and the network communication delays rely on the network structure. Consequently, there is no corresponding relation between the network transmitted delay and sampling period, nevertheless most papers about NCS usually assume the network delay is less than a sampling period. To avoid the illogical premise, we firstly eatabilished a model of a class of long delay NCS, then two novel predictive control strategies of long delay NCS are put forword. The first one is long delay NCS predivtive functional control algorithm by this algorithm derives the predictive control law of the long delay NCS based on the model of long delay NCS. The simulation results and experiment of an electrical-resistance stove realtime control illustrate that the proposed scheme is effective for a class of long delay NCS. The other one is long delay NCS dynamic matrix control algorithm, this method derives the long delay NCS's control law by using dynamic matrix control theory which contains properties of simple algorithm, less calculation, strong robustness. The simulation results illustrate that the proposed method is effective for a class of long delay NCS.
Because of the stochastic delay in the NCS, the system performance goes to bad and even unstable if the delay long enough, the effect of delay on internal model networked control systems (IMNCS) performance is analyzed. The predictive control algorithms include generalized predictive control, model predictive control, dynamic matrix control etc can be equivalently turn over to generalized internal model control, stabilities of continuous IMNCS and discrete IMNCS are studied respectively. The IMNCS stability was discussed by using Routh criterion, state space Lyapunov stability theory and Z plane synthesis (Jury stability criterion) , therefor the maximum allowed time-delay that keep IMNCS stable was presented. In order to make better performance of IMNCS, the delay prediction loop was added and the system stability influenced by prediction was pointed. Simulation results are illustrated that the proposed scheme is very effective.
引文
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