一类非线性耗散系统的逆最优控制

首先研究一类单输入非仿射非线性系统的逆最优控制问题, 其代价泛函为非线性-非二次型, 设计出一族参数化的状态反馈逆最优控制器;然后讨论当该系统为耗散系统时, 在供给率为二次型的耗散性理论框架下,给出使系统渐近稳定的李雅普诺夫函数和镇定控制律, 并通过适当选取代价泛函中的参数,使得李雅普诺夫函数也是最优值函数,进而揭示出耗散系统在线性输出反馈意义下稳定性与最优性之间的等价关系.     

基于神经网络的非仿射块控非线性系统动态反演控制

即使已知非仿射非线性系统的逆存在,利用隐函数定理求解该显式逆仍然非常困难.为此,针对一类不确定块控非仿射系统,将动态反馈、反演、神经网络和反馈线性化技术相结合,提出一种自适应鲁棒控制器的设计方法.利用神经网络来逼近和消除未知函数,并证明了整个闭环系统在李雅普诺夫意义下是稳定的.仿真结果表明了所提出方法的有效性.     

Markov跳跃非线性系统逆最优增益设计

证明了一类严格反馈Markov跳跃系统是依概率输入–状态可稳定的.其次,证明了逆最优增益设计问题可解的一个充分条件是存在一组满足小控制量的依概率输入–状态稳定控制李雅普诺夫函数.最后,利用积分反推方法,给出了严格反馈Markov跳跃系统逆最优增益设计问题的一个构造性解.其中,为了克服由于Markov跳跃引起的耦合项所带来的困难,所设计的李雅普诺夫函数以及控制器是与模态无关的.     

不确定离散时滞模糊系统的广义H2控制

针对一类利用Takagi-Sugeno（T-S）模糊模型,构建了具有状态和输入时滞的不确定离散时间非线性系统,研究了其广义H2稳定和控制器的设计问题。基于分段二次李雅普诺夫（Lyapunov）函数稳定性分析理论,设计出了分段静态输出反馈控制器,使闭环系统对于允许的不确定参数广义H2稳定。数值仿真例子验证了这种控制器的设计方法的有效性和其理论结果的正确性。     

基于积分反步法的轧机速度系统控制器设计

本文给出了基于积分反步法的控制器设计方法，该方法通过逐步修正算法设计镇定控制器，实现系统的全局调节或跟踪。每一步把状态坐标变换、一个给定的李雅普诺夫函数和虚拟控制联系起来，最终得到一个控制李雅普诺夫函数(clf)。基于上述方法，对直流电机驱动的轧机速度系统进行了反馈控制器设计。仿真研究结果表明，本文所设计的反馈控制器使闭环系统稳定，系统具有良好的跟踪性能。     

一类离散时间切换混杂系统鲁棒控制

由于切换规则的存在使得切换混杂控制系统的稳定性研究变得极为复杂,如何针对给定的系统设计适当的控制器和切换规则没有统一的方法.本文考虑一类线性不确定离散时间切换混杂系统的鲁棒二次镇定和渐近镇定问题.利用公共李雅普诺夫函数方法和多李雅普诺夫函数方法,分别设计了切换混杂系统鲁棒状态反馈控制器和鲁棒输出反馈控制器,保证了切换混杂系统的二次稳定性和渐近稳定性.仿真结果验证了所提算法的正确有效性.     

不确定串联非线性系统H∞鲁棒自适应控制

针对一类含有未知参数和干扰的非最小相位串联非线性系统,结合H∞控制和自适应控制方法并利用李雅普诺夫函数递推设计方法设计了状态反馈H∞自适应控制器,避免了求解Hamilton-Jacobi-Isaacs不等式设计控制器的困难.该控制器不仅保证闭环系统ISS(input-to-state)稳定,而且使得系统对于所有允许的参数不确定从干扰输入到可控输出的 L 2增益不大于给定的值.最后,给出了一个仿真例子,仿真结果充分表明了所设计的控制器的可行性和有效性.     

基于滤波器估计的正交函数神经网络非线性系统H∞控制

针对含有多个未知非线性项的非线性系统难于控制的问题,提出利用Chebyshev正交函数构建基于神经网络滤波器的控制器,并在权值学习误差有界和跟踪误差有界条件下,通过李雅普诺夫稳定性定理确定控制器的权值,保证了非线性系统的H_∞鲁棒控制.最后,利用所提出算法对非线性系统的滤波器和控制器进行确定,仿真结果验证了该方法的有效性.     

新型Lyapunov函数方法的模糊控制器设计

研究了在新型Lyapunov方法下的带有不确定性的T—S模糊模型稳定性及控制器的设计,给出了输入为零时系统稳定的充分条件,并验证了该条件比常用李雅普诺夫函数具有更大的松弛性。基于新型李雅普诺夫函数,对带有不确定性模糊模型设计了线性矩阵不等式形式的模糊控制器,该方法不必知道某一时刻被激活的规则数,同时把一个公共矩阵的寻找分解为p个矩阵的寻找。仿真实验证明,通过应用改进的李雅普诺夫函数设计的模糊控制器,具有良好的鲁棒性,控制效果良好。     

通过控制器切换实现线性系统输出反馈鲁棒镇定

研究了带有不确定性的线性系统的输出反馈镇定问题. 假定事先给定有限个备选的输出反馈控制器, 分别利用单李雅普诺夫函数和多李雅普诺夫函数方法给出了两种切换律的设计方案. 仿真实例说明本文所给方法的有效性.     

基于反步法非线性纯反馈系统的控制器设计

针对由于非线性纯反馈系统存在非仿射性结构使得用以往的坐标变换难以设计出控制器的问题,提出了一种新的坐标变换,并引入了一阶控制输入的辅助系统来处理非线性纯反馈系统。首先,结合新提出的坐标变换,计算出新状态方程;然后,基于反步法在每一步中设计出正定的Lyapunov函数;最后,通过设计虚拟控制器和实际的辅助控制器使得Lyapunov的导数负定,这样从理论上解决了非线性纯反馈系统的跟踪问题。仿真实验表明所设计的辅助控制器能使得纯反馈闭环系统所有状态信号有界,控制输出能跟踪到给定信号,跟踪误差渐近地趋于稳定,从而达到要求。     

Adaptive practical preassigned finite‐time stability for a class of pure‐feedback systems with full state constraints

This paper focuses on an adaptive practical preassigned finite‐time control problem for a class of unknown pure‐feedback nonlinear systems with full state constraints. Two new concepts, called preassigned finite‐time function and practical preassigned finite‐time stability, are defined. In order to achieve the main result, the pure‐feedback system is first transformed into an affine strict‐feedback nonlinear system based on the mean value theorem. Then, an adaptive preassigned finite‐time controller is obtained based on a modified barrier Lyapunov function and backstepping technique. Finally, simulation examples are exhibited to demonstrate the effectiveness of the proposed scheme.     

Global output feedback control of nonlinear time-delay systems with input matching uncertainty and unknown output function

This paper studies the problem of global output feedback control for nonlinear time-delay systems with input matching uncertainty and the unknown output function, whose nonlinearities are bounded by lower triangular linear unmeasured states multiplying the unknown constant, polynomial-of-output and polynomial-of-input growth rates. By constructing a new extended state observer and skillfully combining the dynamic gain method, backstepping method and Lyapunov–Krasovskii theorem, a delay-independent output feedback controller can be developed with only one dynamic gain. It is proved that all the signals of the closed-loop system are bounded, the states of the original system and the corresponding observer converge to zero, and the estimation of input matching uncertainty converges to its actual value. Two examples demonstrate the effectiveness of the control scheme.     

基于性能指标约束的一类输入死区非线性系统最优控制

针对一类考虑指定性能和带有输入死区约束的严格反馈非线性系统,本文提出了一种自适应模糊最优控制方法.采用模糊逻辑系统逼近系统的未知非线性函数及代价函数,利用backstepping方法及命令滤波技术,设计前馈控制器.针对仿射形式的误差系统,结合自适应动态规划技术,设计最优反馈控制器.采用指定性能控制方法,将系统跟踪误差约束在指定范围内.利用死区斜率信息解决具有死区输入的非线性系统的控制问题.基于Lyapunov稳定性理论,证明闭环系统内所有信号是一致最终有界的.最后仿真结果验证了本文方法的可行性和有效性.     

Observer‐based decentralized adaptive control for large‐scale pure‐feedback systems with unknown time‐delayed nonlinear interactions

This paper presents an approximation design for a decentralized adaptive output‐feedback control of large‐scale pure‐feedback nonlinear systems with unknown time‐varying delayed interconnections. The interaction terms are bounded by unknown nonlinear bounding functions including unmeasurable state variables of subsystems. These bounding functions together with the algebraic loop problem of virtual and actual control inputs in the pure‐feedback form make the output‐feedback controller design difficult and challenging. To overcome the design difficulties, the observer‐based dynamic surface memoryless local controller for each subsystem is designed using appropriate Lyapunov‐Krasovskii functionals, the function approximation technique based on neural networks, and the additional first‐order low‐pass filter for the actual control input. It is shown that all signals in the total controlled closed‐loop system are semiglobally uniformly bounded and control errors converge to an adjustable neighborhood of the origin. Finally, simulation examples are provided to illustrate the effectiveness of the proposed decentralized control scheme. Copyright © 2013 John Wiley & Sons, Ltd.     

A new decentralised controller design method for a class of strongly interconnected systems

In this paper, two interconnected structures are first discussed, under which some closed-loop subsystems must be unstable to make the whole interconnected system stable, which can be viewed as a kind of strongly interconnected systems. Then, comparisons with small gain theorem are discussed and large gain interconnected characteristics are shown. A new approach for the design of decentralised controllers is presented by determining the Lyapunov function structure previously, which allows the existence of unstable subsystems. By fully utilising the orthogonal space information of input matrix, some new understandings are presented for the construction of Lyapunov matrix. This new method can deal with decentralised state feedback, static output feedback and dynamic output feedback controllers in a unified framework. Furthermore, in order to reduce the design conservativeness and deal with robustness, a new robust decentralised controller design method is given by combining with the parameter-dependent Lyapunov function method. Some basic rules are provided for the choice of initial variables in Lyapunov matrix or new introduced slack matrices. As byproducts, some linear matrix inequality based sufficient conditions are established for centralised static output feedback stabilisation. Effects of unstable subsystems in nonlinear Lur'e systems are further discussed. The corresponding decentralised controller design method is presented for absolute stability. The examples illustrate that the new method is significantly effective.     

MIMO纯反馈受限系统无模型非线性比例反演控制

针对模型未知的MIMO纯反馈系统,提出一种新的控制设计方案.该方案基于预设性能控制思想设计非线性比例控制器,并将其引入反演设计的每一步,以构建非线性比例反演控制器,并融合考虑了模型未知、状态受限、输入受限以及预设性能的需求,且无需引入任何逼近理论和自适应控制等技术即可保证系统具有良好的抗扰性和鲁棒自适应性,控制器结构极为简单.最后,基于Lyapunov稳定性定理证明了闭环系统所有信号一致有界,仿真结果验证了所提出设计方案的可行性和有效性.     

具有PID反馈增益的自主水下航行器反步法变深控制

本文针对海底地形测绘时自主水下航行器(autonomous underwater vehicle,AUV)的变深控制问题,提出具有PID增益调节的AUV深度控制方法,基于反馈增益的反步法设计控制器,避免了采用传统反步法导致控制器中存在虚拟控制量的高阶导数问题;基于李雅普诺夫稳定性理论设计控制器参数消除了部分非线性项,得到的控制器的线性部分为状态变量的线性组合,具有PID控制器参数调节的形式;针对存在建模不精确、外界干扰和测量噪声时的闭环系统鲁棒性进行分析,保证了误差系统在扰动作用时的一致最终有界性.最后通过仿真实验验证了本文设计的控制器的有效性.     

On the stability and control of nonlinear dynamical systems via vector Lyapunov functions

Vector Lyapunov theory has been developed to weaken the hypothesis of standard Lyapunov theory in order to enlarge the class of Lyapunov functions that can be used for analyzing system stability. In this paper, we extend the theory of vector Lyapunov functions by constructing a generalized comparison system whose vector field can be a function of the comparison system states as well as the nonlinear dynamical system states. Furthermore, we present a generalized convergence result which, in the case of a scalar comparison system, specializes to the classical Krasovskii-LaSalle invariant set theorem. In addition, we introduce the notion of a control vector Lyapunov function as a generalization of control Lyapunov functions, and show that asymptotic stabilizability of a nonlinear dynamical system is equivalent to the existence of a control vector Lyapunov function. Moreover, using control vector Lyapunov functions, we construct a universal decentralized feedback control law for a decentralized nonlinear dynamical system that possesses guaranteed gain and sector margins in each decentralized input channel. Furthermore, we establish connections between the recently developed notion of vector dissipativity and optimality of the proposed decentralized feedback control law. Finally, the proposed control framework is used to construct decentralized controllers for large-scale nonlinear systems with robustness guarantees against full modeling uncertainty.     

Parallel Control for Optimal Tracking via Adaptive Dynamic Programming

This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear systems. Unlike existing optimal state feedback control, the control input of the optimal parallel control is introduced into the feedback system. However, due to the introduction of control input into the feedback system, the optimal state feedback control methods can not be applied directly. To address this problem, an augmented system and an augmented performance index function are proposed firstly. Thus, the general nonlinear system is transformed into an affine nonlinear system. The difference between the optimal parallel control and the optimal state feedback control is analyzed theoretically. It is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index function. Moreover, an adaptive dynamic programming (ADP) technique is utilized to implement the optimal parallel tracking control using a critic neural network (NN) to approximate the value function online. The stability analysis of the closed-loop system is performed using the Lyapunov theory, and the tracking error and NN weights errors are uniformly ultimately bounded (UUB). Also, the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference signals. Finally, the effectiveness of the developed optimal parallel control method is verified in two cases.