基于观测器的参数不确定非线性系统的模糊鲁棒控制

对一类非线性系统进行模糊建模及其模糊观测器设计, 研究了在系统的状态不可测且存在参数不确定的模糊鲁棒控制问题, 以线性矩阵不等式的形式给出了模糊控制系统具有李雅普诺夫意义下稳定的充分条件, 最后把所提出的方法应用到倒立摆系统进行仿真, 仿真结果验证了该控制方法的有效性.     

基于观测器的不确定时滞系统的鲁棒控制

研究不确定线性时滞系统的状态观测器和基于观测器的鲁棒控制器设计问题,其中不确定性是时变的、不要求满足匹配条件。通过构造增广系统,利用Ｌｙａｐｕｎｏｖ稳定性理论,获得了该不确定系统存在状态观测器和基于观测器的鲁棒控制器的充分条件,同时给出了相应的状态观测器和基于观测器的鲁棒控制器。所得结论推广并改进了已知的一些结果,并通过实例说明了其有效性。     

基于观测器的非线性不确定离散系统的鲁棒模糊控制

研究了参数不确定及状态变量难以获取的非线性系统的鲁棒模糊控制问题.采用离散模糊T-S模型对离散非线性系统进行建模并建立了模糊观测器.用矩阵不等式的形式推导出了在Lyapunov意义下鲁棒镇定的充分条件.利用线性矩阵不等式(LMI)导出了模糊反馈增益和模糊观测器增益存在的充分条件.     

基于状态观测器的一类非线性系统的模糊鲁棒控制

利用T－S模型对一类非线性不确定系统进行模糊建模,在此基础上研究模糊鲁棒观测器及模糊状态鲁棒控制器的设计,并证明所设计的模糊鲁棒观测器和模糊状态鲁棒控制器具有全局渐近稳定性质。     

不确定时滞系统基于观测器的鲁棒控制器设计

研究了不确定线性时滞系统的状态观测器和基于观测器的鲁棒控制器设计问题，其中不确定性是时变的，通过构造增广系统，利用线性矩阵不等式方法，获得了该不确定系统存在状态观测器和基于观测器的鲁棒控制器的充分条件，同时给出了相应的状态观测器和基于观测器的鲁棒控制器，所给示例说明了本文方法的设计步骤和有效性。     

基于观测器的非线性不确定系统鲁棒故障检测新方法

针对非线性不确定系统的鲁棒故障检测问题,提出了一种采用统计理论的新方法.通过设计全阶故障观测器产生残差信号,将鲁棒故障检测观测器设计问题转化为H∞优化问题;利用H∞范数描述故障检测的鲁棒性,保证系统的抗干扰能力,同时引入H_范数,确保对故障信号的灵敏度;应用线性矩阵不等式技术给出了该设计问题解存在的条件和求解方法.将统计理论用于故障检测阈值的确定,充分考虑了残差信号的随机特性,使故障决策更加准确和可靠.最后通过仿真实例验证了本文方法的有效性.     

不确定T-S 模型的D -域极点约束鲁棒控制

对于具有两类不确定性的Takagi-Sugeno模糊非线性模型,运用二次稳定思想,提出使闭环系统的极点在各种允许的不确定性下始终在复平面上某个二次矩阵不等式区域D中的一个充分条件.基于这一条件和并行分布补偿技术,用线性矩阵不等式方法,设计全局鲁棒D-稳定控制器.最后通过质量弹簧阻尼系统给出了所述设计方法的仿真示例.     

含约束的非线性不确定系统的鲁棒控制

讨论一类含约束的非线性不确定系统的鲁棒控制问题（这里的不确定性并不要求满足匹配条件）。在一定的假设条件下给出了使该类问题可解的充分条件，构造出相应的鲁棒控制器，该控制器避免了利用微分几何方法所得控制器易产生过度控制的缺点。     

基于LMI的不确定离散模糊时滞系统鲁棒控制

利用T-S模糊模型,讨论了一类具有状态时滞和控制输入时滞的不确定离散非线性系统鲁棒控制问题,基于Lyapunov稳定性理论,导出了系统采用线性矩阵不等式表示的时滞相关型鲁棒镇定充分条件,并设计了相应的状态反馈模糊控制器．仿真结果证明了所提出方法的有效性和可行性.     

基于观测器的非线性系统H_∞模糊可靠控制

研究了基于观测器的非线性系统H∞模糊可靠控制问题.采用T-S模糊模型对非线性系统进行建模,用模糊观测器重构系统状态.在系统发生故障时满足给定H∞性能的约束下.最小化正常情况下的H∞性能,实现次优H∞模糊可靠控制.提出了两种应用线性矩阵不等式(LMI)的H∞模糊可靠控制器设计方法.分别采用两步法和相似变换法将双线性矩阵不等式问题转化为LMI问题.仿真示例验证了所提出方法的有效性.     

Observer-based adaptive fuzzy backstepping control of uncertain nonlinear pure-feedback systems

In this paper,a new fuzzy adaptive control approach is developed for a class of SISO uncertain pure-feedback nonlinear systems with immeasurable states.Fuzzy logic systems are utilized to approximate the unknown nonlinear functions;and the filtered signals are introduced to circumvent algebraic loop systems encountered in the implementation of the controller,and a fuzzy state adaptive observer is designed to estimate the immeasurable states.By combining the adaptive backstepping technique,an adaptive fuzzy output feedback control scheme is developed.It is proven that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded(SGUUB),and the observer and tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Simulation studies are included to illustrate the efectiveness of the proposed approach.     

Robust fuzzy tracking control for nonlinear networked control systems with integral quadratic constraints

This paper investigates the robust tracking control problem for a class of nonlinear networked control systems (NCSs) using the Takagi-Sugeno (T-S) fuzzy model approach. Based on a time-varying delay system transformed from the NCSs, an augmented Lyapunov function containing more useful information is constructed. A less conservative sufficient condition is established such that the closed-loop systems stability and time-domain integral quadratic constraints (IQCs) are satisfied while both time-varying network-induced delays and packet losses are taken into account. The fuzzy tracking controllers design scheme is derived in terms of linear matrix inequalities (LMIs) and parallel distributed compensation (PDC). Furthermore, robust stabilization criterion for nonlinear NCSs is given as an extension of the tracking control result. Finally, numerical simulations are provided to illustrate the effectiveness and merits of the proposed method.     

Exponential stability of time-delay systems with nonlinear uncertainties

The global exponential stability and the exponential convergence rate for time-delay systems with nonlinear uncertainties are investigated. A novel exponential stability criterion for the system is derived using the Lyapunov method. These stability conditions are formulated as linear matrix inequalities (LMIs), which can be easily solved by various convex optimization algorithms. The issue of exponential stability for time-delay systems with nonlinear uncertainties using generalized eigen value problem (GEVP) approach remains open, which motivates this paper. Numerical examples are given to illustrate the usefulness of our proposed method.     

Robust stability of impulsive Takagi-Sugeno fuzzy systems with parametric uncertainties

This paper presents a kind of time-varying impulsive Takagi-Sugeno (T-S) fuzzy model with parametric uncertainties in which each subsystem of the model is time-varying. Several robust stabilities of time-varying systems with parametric uncertainties, such as general robust stability, robustly asymptotical stability and exponential stability, are studied using uniformly positive definite matrix functions and the Lyapunov method. Specifically, robust stability conditions of time-invariant impulsive T-S fuzzy systems are also derived in the formulation of quasi-linear matrix inequalities (QLMIs) and an iterative LMIs algorithm is designed for solving QLMIs. Finally, a unified chaotic system with continuous periodic switch and a unified time-invariant chaotic system are used for demonstrating the effectiveness of our respective results.     

Design of robust output-feedback repetitive controller for class of linear systems with uncertainties

Repetitive control, which adds a human-like learning capability to a control system, is widely used in many fields. This paper deals with the problem of designing a robust repetitive-control system based on output feedback for a class of plants with time-varying structured uncertainties. A continuous-discrete two-dimensional hybrid model is established that accurately describes the features of repetitive control so as to enable independent adjustment of the control and learning actions. A sufficient conditi...     

Robust stability analysis of linear systems with parametric uncertainty

This article is concerned with the problem of robust stability analysis of linear systems with uncertain parameters. By constructing an equivalent system with positive uncertain parameters and using the properties of these parameters, a new stability analysis condition is derived. Due to making use of the properties of uncertain parameters, the new proposed method has potential to give less conservative results than the existing approaches. A numerical example is given to illustrate the effectiveness of the proposed method.     

Observer-based adaptive sliding mode control for nonlinear uncertain state-delayed systems

This paper presents a methodological approach to design observer-based adaptive sliding mode control for a class of nonlinear uncertain state-delayed systems with immeasurable states. A novel switching surface is proposed and a state observer is employed to reconstruct the sliding mode control action. The proposed method does not need a priori knowledge of upper bounds on the norm of the uncertainties, but estimates them by using the adaptation technique so that the reaching condition can be satisfied. Based on Lyapunov stability theorem and linear matrix inequality (LMI) technique, the stability of the overall closed-loop nonlinear uncertain state-delayed system is guaranteed for the proposed control scheme under certain conditions. Furthermore, the state observer and control law can be constructed from the positive-definite solutions of two LMIs, and the design technique is simple and efficient. The validity of the proposed control methodology is demonstrated by simulation results. Recommended by Editorial Board member Ju Hyun Park under the direction of Editor Young IL Lee. Ming-Chang Pai received the M.S. and Ph.D. degrees in mechanical engineering in 1994 and 1998 from Pennsylvania State University, State College, P.A.. He is currently an Associate Professor in the Department of Automation Engineering at Nan Kai University of Technology. His research interests are in mechatronics, robots, robust control and nonlinear control.     

Delay-dependent robust stability criteria for delay neural networks with linear fractional uncertainties

This article investigates the problem of robust stability for neural networks with time-varying delays and parameter uncertainties of linear fractional form. By introducing a new Lyapunov-Krasovskii functional and a tighter inequality, delay-dependent stability criteria are established in term of linear matrix inequalities (LMIs). It is shown that the obtained criteria can provide less conservative results than some existing ones. Numerical examples are given to demonstrate the applicability of the proposed approach. Recommended by Editorial Board member Naira Hovakimyan under the direction of Editor Young-Hoon Joo. This work was supported by the National Science foundation of China under Grant no. 60774013 and Key Laboratory of Education Ministry for Image Processing and Intelligent Control under grant no. 200805. Tao Li received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor in Department of Information and Communication, Nanjing University of Information Science and Technology. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Lei Guo received the Ph.D. degree in the Research Institute of Automation Southeast University, China. From 1999 to 2004, he has worked at Hong Kong University, IRCCyN (France), Glasgow University, Loughborough University and UMIST, UK. Now He is a Professor in School of Instrument Science and Opto-Electronics Engineering, Beihang University. His current research interests include robust control, fault detection and diagnosis. Lingyao Wu received the Ph.D. degree in The Research Institute of Automation Southeast University, China. Now He is an Assistant Professor in the Research Institute of Automation Southeast University. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Changyin Sun received the Ph.D. degree in the Research Institute of Automation Southeast University, China. Now He is a Professor in the Research Institute of Automation Southeast University. His current research interests include timedelay systems, neural networks.     

Observer-based adaptive fuzzy control for a class of nonlinear time-delay systems

An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach.