非线性时滞系统自适应输出反馈跟踪控制

针对一类参数化非线性时滞输出反馈系统,提出了一种自适应输出跟踪控制器的设计方案。引入时滞滤波器估计未知系统状态,采用backstepping技术设计控制律和参数自适应律,运用占优方法处理非线性时滞项,从而放宽了对非线性时滞函数的要求,实现了对给定目标轨线的全局渐近跟踪,同时保证闭环系统所有信号一致有界。基于Lyapunov-Krasoviskii泛函方法证明了整个闭环系统的稳定性。实例仿真说明了该方案的可行性。     

New delay-dependent stability criteria and robust control of nonlinear time-delay systems

This paper investigates the stability analysis and H_∞ control for a class of nonlinear timedelay systems,and proposes a number of new results.Firstly,an equivalent form is given for this class of systems by means of coordinate transformation and orthogonal decomposition of vector fields.Then,based on the equivalent form,some delay-dependent results are derived for the stability analysis of the systems by constructing a novel Lyapunov functional.Thirdly,the authors use the equivalent form and the obtained stability results to investigate the H_∞ control problem for a class of nonhnear time-delay control systems,and present a control design procedure.Finally,an illustrative example is given to show the effectiveness of the results obtained in this paper.It is shown that the main results of this paper are easier to check than some existing ones,and have less conservatism.     

带有持续扰动非线性系统的最优跟踪控制

研究具有外界持续扰动的非线性系统的无静差最优跟踪控制问题。首先基于内模原理构造一扰动补偿器,将系统化为无扰动的增广系统。然后利用灵敏度法推导出了该系统的最优跟踪控制律。仿真实例表明了该设计方法的有效性。     

单边Lipschitz非线性多智能体系统一致性追踪控制

针对单边Lipschitz非线性多智能体系统,提出了一种分布式一致性控制方法.首先,构建了领导-跟随者动力学结构,用于实现单边Lipschitz多智能体系统的追踪控制.然后,设计了单边Lipschitz非线性多智能体系统的一致性控制协议,可根据智能体之间局部交互信息构建分布式反馈控制,并将系统的一致性追踪问题转化为系统...     

非线性不确定时滞系统观测器型鲁棒无源控制

将无源性概念引入到非线性不确定时滞系统中,研究了带有时滞和不确定性的非线性系统的鲁棒无源控制问题.首先,利用多层神经网络近似代替系统中的非线性部分,采用线性微分包含(LDI)技术来线性化该非线性环节.其次,基于LDI模型,构造适当的状态观测器和反馈控制器,利用Lyapunov稳定理论,通过一定的矩阵变换,将设计问题转化为线性矩阵不等式(LMI)的可行解问题.从而使控制器的设计简单易行.接着,引入无源化的损耗指标,给出具有指定损耗指标的鲁棒无源控制器设计方法.最后以Lo-gistic混沌系统为例进行仿真试验,结果表明该设计方法的有效性.     

Adaptive output-feedback control for MIMO nonlinear systems with time-varying delays using neural networks

An adaptive neural network output-feedback regulation approach is proposed for a class of multi-input-multi-output nonlinear time-varying delayed systems. Both the designed observer and controller are free from time delays. Different from the existing results, this paper need not the assumption that the upper bounding functions of time-delay terms are known, and only a neural network is employed to compensate for all the upper bounding functions of time-delay terms, so the designed controller procedure is more simplified. In addition, the resulting closed-loop system is proved to be semi-globally ultimately uniformly bounded, and the output regulation error converges to a small residual set around the origin. Two simulation examples are provided to verify the effectiveness of control scheme.     

Optimal tracking control for linear time-delay large-scale systems with persistent disturbances

An optimal tracking control (OTC) problem for linear time-delay large-scale systems affected by external persistent disturbances is investigated. Based on the internal model principle, a disturbance compensator is constructed. The system with persistent disturbances is transformed into an augmented system without persistent disturbances. The original OTC problem of linear time-delay system is transformed into a sequence of linear twopoint boundary value (TPBV) problems by introducing a sensitivity parameter and expanding Maclaurin series around it. By solving an OTC law of the augmented system, the OTC law of the original system is obtained. A numerical simulation is provided to illustrate the effectiveness of the proposed method.     

Adaptive neural network tracking control for a class of unknown nonlinear time-delay systems

1 .INTRODUCTIONNeural network (NN) control has made great pro-gress in past decades[1 ~4]. In Ref .[1] , adaptivebounding design technique was applied to adaptiveneural control for a class of strict-feedback nonlin-ear systems . The requirement of a known boundon the network reconstruction error was removed.By introducing an integral Lyapunov function,anadaptive NN control approach was proposed forunknown strict-feedback nonlinear systems[2],where the controller singularity problem was …     

基于神经网络的不确定非线性时滞系统保成本控制

保成本控制问题受到了人们的关注,并取得了很多的研究成果,但这些研究均未考虑提高系统动态特性的问题,且很少涉及非线性系统。为此,将神经网络和控制理论相结合,针对一类不确定非线性时滞系统,结合系统动态特性以及非线性扰动抑制问题,提出了新的控制算法。通过将稳定度引入保成本控制中,可以在保成本控制的基础上提高系统的动态特性;利用神经网络良好的非线性逼近能力,很好地解决了系统存在任意非线性扰动时的控制问题。     

State feedback stabilization for a class of nonlinear time-delay systems via dynamic linear controllers

The dynamic linear state feedback control problem is addressed for a class of nonlinear systems subject to time-delay. First, using the dynamic change of coordinates, the problem of global state feedback stabilization is solved for a class of time-delay systems under a type of nonhomogeneous growth conditions. With the aid of an appropriate Lyapunov-Krasovskii functional and the adaptive strategy used in coordinates, the closed-loop system can be globally asymptotically stabilized by the dynamic linear state feedback controller. The growth condition in perturbations are more general than that in the existing results. The correctness of the theoretical results are illustrated with an academic simulation example.     

反馈可线性化系统全局跟踪控制器的设计

研究反馈可线性化的非线性系统全局跟踪参考信号的问题,将全局跟踪问题转化为误差系统的全局镇定问题。由Riccati方程获得了反馈可线性化系统的控制Lyapunov函数,证明了所得到的控制Lyapunov函数正是误差系统的控制Lyapunov函数。应用Sontag的通用公式,设计了全局跟踪控制器,并应用于单关节机器手跟踪参考信号的控制,仿真说明了所提出方法的有效性。     

一类模糊时滞系统自适应跟踪控制与仿真

基于T-S模糊模型和变结构控制策略,研究了一类带有参数不确定项的模糊时滞系统自适应输出跟踪问题。首先利用变结构控制理论选择滑动模,根据李雅普诺夫方法,提出了一种自适应变结构控制策略。利用自适应策略的目的在于克服扰动的未知上界,使设计的控制器满足可达条件。该方法确保系统的运动轨迹在有限的时间内到达滑模面并一直保持在滑模面上。其次根据ISS理论和LMI方法研究了系统状态全局有界的充分条件。最后,通过仿真实例验证了所提方法的正确性和有效性。     

一类不确定时滞系统的滑模控制

考虑了一类同时存在状态不确定性和控制不确定性的时滞系统的滑模控制问题,通过采用李亚普诺夫方法和线性矩阵不等式(LMI)技术,给出了闭环系统渐近稳定的充分条件,而且滑模控制律和滑模面的设计可以利用线性矩阵不等式的解得到,证明了该滑模控制律能保证状态轨迹被驱动到指定的切换面上。仿真实验表明了算法的有效性。     

不确定时滞系统多目标约束下的满意容错控制

针对一类具有不确定参数、干扰输入和时滞特性的非线性系统,研究了当执行器发生故障时的满意容错控制问题。在更实际、更一般的执行器连续增益故障模型下,采用一种含有时滞记忆的状态反馈控制律,分析了鲁棒稳定性能与H∞指标的相容性,并在相容指标约束下,给出了鲁棒H∞满意容错控制器存在的充分条件和设计方法。仿真算例验证了该方法的有效性。     

基于观测器的一类不确定非线性系统自适应输出反馈控制

针对一类不确定非线性系统,基于非线性状态观测器采用回馈递推(Backstepping)设计方法提出了一种鲁棒自适应L2增益控制方案。该控制方案首先对系统的不可观测状态设计非线性状态观测器,在此基础上通过多步递推得到系统的控制律并设计了未知干扰的参数自适应律,使系统具有L2增益性能。同时把采用常规设计方法需要对过多参数进行辨识问题简化为只需对与未知干扰个数相同的参数进行辨识的问题,简化了控制器结构。最后通过仿真算例验证了所设计控制方案的有效性。     

PD-type iterative learning control for nonlinear time-delay system with external disturbance

1 .INTRODUCTIONTheiterativelearning control method was proposedby Ariomoto et al[1]for the control system, whichcan performthe same task repetitively . The basiclearning controller for generating the present con-trol input is based on the previous control historyand a learning mechanism.In the last two decadesiterative learning control has been extensivelystudied and achieved significant progress in boththeory and application,and becomes the one of themost active fields inintelligent cont…     

参数未知非线性混沌系统的自适应反演滑模控制

针对一类含有非匹配未知参数和非参数不确定性的混沌系统,基于自适应反演和滑模控制方法,研究自适应反演滑模控制策略,实现了不确定混沌系统的调节问题。与现有自适应控制相比,允许系统存在非匹配未知参数和非参数化的不确定性,增强了控制系统的鲁棒性。仿真算例证明了理论研究成果的正确性和鲁棒性。     

不确定非线性系统的鲁棒自适应跟踪简化算法

传统的Backstepping自适应控制方法需要对虚拟控制律进行求导,从而导致“计算复杂性膨胀”。动态平面控制技术能够克服这一缺陷。将这一技术扩展到一类具有参数严格反馈形式的不确定非线性系统输出跟踪,这类系统同时包含线性参数和未知非线性函数两种不确定性。所设计的控制算法比现有算法大大简化,解决了“计算复杂性膨胀”问题;运用Lyapunov理论证明了闭环系统一致最终有界,仿真结果表明了算法的有效性。     

Adaptive control method for nonlinear time-delay processes

Two complex properties,varying time-delay and block-oriented nonlinearity,are very common in chemical engineering processes and not easy to be controlled by routine control methods.Aimed at these two complex properties,a novel adaptive control algorithm the basis of nonlinear OFS(orthonormal functional series) model is proposed.First,the hybrid model which combines OFS and Volterra series is introduced.Then,a stable state feedback strategy is used to construct a nonlinear adaptive control algorithm that can guarantee the closed-loop stability and can track the set point curve without steady-state errors.Finally,control simulations and experiments on a nonlinear process with varying time-delay are presented.A number of experimental results validate the efficiency and superiority of this algorithm.     

Adaptive control for a class of discrete-time time-delay systems with regard to delay parameter

The memory state feedback control problem for a class of discrete-time systems with input delay and unknown state delay is addressed based on LMIs and Lyapunov-Krasovskii functional method. Under the action of our designed adaptive control law, the unknown time-delay parameter is included in memory state feedback controller. Using LMI technique, delay-dependent sufficient conditions for the existence of the feedback controller are obtained. Finally, the effectiveness of the proposed design method is demonstrated by a numerical example.