切换对称组合系统的稳定性

首次提出了切换对称组合系统的概念, 研究了此类系统在任意切换下渐近稳定的条件, 同时分别利用多李雅普诺夫函数方法和单李雅普诺夫函数方法, 给出使切换对称组合系统渐近稳定的切换律, 利用切换对称组合系统的结构特点, 使其切换律的设计条件得到简化.     

线性切换容错控制系统稳定性的新判据*

研究了线性切换容错控制系统的稳定性问题。利用分段李雅普诺夫函数方法,结合梅茨勒矩阵的性质和矩阵不等式的分析技巧,得到了基于李雅普诺夫—梅兹勒线性矩阵不等式判定系统稳定的新结果。设计依赖于状态的切换规则便于计算、易于检验。最后利用MATLAB工具箱得到的仿真实例验证了本结果的可行性。     

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。     

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.     

李雅普诺夫函数优化:正交矩阵构造方案EI北大核心CSCD

本文研究了李雅普诺夫函数的优化问题.提出了一种正交矩阵构造方案,用于求解黎卡提不等式中的最优李雅普诺夫函数.通过分析系统H_(∞)范数的几何特征,本文将黎卡提不等式转换为近似等式,进而给出了最优李雅普诺夫函数的存在条件.基于所给最优李雅普诺夫函数存在条件,所提正交矩阵构造方案利用旋转变换,将非线性方程组的求解问题转换为幅值和角度的线性优化问题,进而实现李雅普诺夫函数参数的优化.研究结果弥补了目前的研究无法求解最优李雅普诺夫函数的不足,对系统性能分析和非保守控制的设计具有建设性.算例验证了所提正交矩阵构造方案的有效性.     

关于Sontag-Type控制的注记

基于控制李雅普诺夫函数的Sontag-Type控制是仿射系统鲁棒镇定中的重要控制律.首先揭示该控制律本质上是一种变结构控制且闭环的切换面总可达,受此启发并为了相对容易地构造控制李雅普诺夫函数,运用零状态可检测概念定义弱控制李雅普诺夫函数,并证明了基于弱控制李雅普诺夫函数的Sontag-Type控制的优化镇定性.文中还证明,在温和条件下,基于弱控制李雅普诺夫函数的Sontag＿Type控制为仿射系统的输入到状态镇定控制.     

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。     

基于状态估计的摩擦模糊建模与鲁棒自适应控制

针对一类多自由度机械系统, 研究了基于状态估计的摩擦模糊建模与鲁棒自适应控制问题. 提出用模糊状态估计器估计摩擦模型中的不可测变量, 并用严格正实和李雅普诺夫稳定性理论证明了状态估计误差的一致最终有界性. 运用模糊状态估计结果设计了多变量鲁棒自适应控制器, 其中摩擦模糊模型中的自适应参数是基于李雅普诺夫稳定性理论设计的, 并证明了闭环系统跟踪误差的一致最终有界性. 本文对多自由度质量、弹簧和摩擦阻尼系统进行的仿真, 结果表明所提出的状态估计算法和自适应控制策略是有效的.     

切换系统基于反演递推法的鲁棒自适应控制

切换系统的稳定控制问题是一个重要的研究问题。基于李雅普诺夫函数的方法是研究切换系统稳定性的重要手段,但是有约束非线性系统的李亚普诺夫函数构造仍是一个难题(特别是对带有不确定性的非线性系统)。针对一类带有不确定性的严格反馈型切换非线性系统,利用反演递推法(backstepping)设计了子系统的基于李亚普诺夫函数的鲁棒自适应控制器,并证明了子闭环系统的稳定性,同时设计适当的切换律保证了整个闭环系统的稳定性。其中系统的未知不确定性及外界干扰不要求线性增长速度,并由模糊系统在线逼近。结果表明所提出方法的有效性。     

基于双线性滤波器的自适应有源消声算法的研究

利用双线性滤波器对非线性信号处理方面的优势,同时结合李雅普诺夫稳定性理论,提出BF-LMS算法。该算法首先定义李雅普诺夫函数,然后对双线性滤波器的权系数进行自适应调整,并且根据李雅普诺夫稳定性理论,使误差渐近趋近于零,从而达到能够避免传统噪声控制方法中对噪声信号统计特性的依赖性,最终使系统达到渐近稳定。     

Switching fuzzy controller design based on switching Lyapunov function for a class of nonlinear systems

This paper presents a switching fuzzy controller design for a class of nonlinear systems. A switching fuzzy model is employed to represent the dynamics of a nonlinear system. In our previous papers, we proposed the switching fuzzy model and a switching Lyapunov function and derived stability conditions for open-loop systems. In this paper, we design a switching fuzzy controller. We firstly show that switching fuzzy controller design conditions based on the switching Lyapunov function are given in terms of bilinear matrix inequalities, which is difficult to design the controller numerically. Then, we propose a new controller design approach utilizing an augmented system. By introducing the augmented system which consists of the switching fuzzy model and a stable linear system, the controller design conditions based on the switching Lyapunov function are given in terms of linear matrix inequalities (LMIs). Therefore, we can effectively design the switching fuzzy controller via LMI-based approach. A design example illustrates the utility of this approach. Moreover, we show that the approach proposed in this paper is available in the research area of piecewise linear control.     

Stabilisation of discrete-time polynomial fuzzy systems via a polynomial lyapunov approach

This paper deals with the problem of designing a controller for a class of discrete-time nonlinear systems which is represented by discrete-time polynomial fuzzy model. Most of the existing control design methods for discrete-time fuzzy polynomial systems cannot guarantee their Lyapunov function to be a radially unbounded polynomial function, hence the global stability cannot be assured. The proposed control design in this paper guarantees a radially unbounded polynomial Lyapunov functions which ensures global stability. In the proposed design, state feedback structure is considered and non-convexity problem is solved by incorporating an integrator into the controller. Sufficient conditions of stability are derived in terms of polynomial matrix inequalities which are solved via SOSTOOLS in MATLAB. A numerical example is presented to illustrate the effectiveness of the proposed controller.     

A Sum-of-Squares Approach to Modeling and Control of Nonlinear Dynamical Systems With Polynomial Fuzzy Systems

This paper presents a sum of squares (SOS) approach for modeling and control of nonlinear dynamical systems using polynomial fuzzy systems. The proposed SOS-based framework provides a number of innovations and improvements over the existing linear matrix inequality (LMI)-based approaches to Takagi--Sugeno (T--S) fuzzy modeling and control. First, we propose a polynomial fuzzy modeling and control framework that is more general and effective than the well-known T--S fuzzy modeling and control. Secondly, we obtain stability and stabilizability conditions of the polynomial fuzzy systems based on polynomial Lyapunov functions that contain quadratic Lyapunov functions as a special case. Hence, the stability and stabilizability conditions presented in this paper are more general and relaxed than those of the existing LMI-based approaches to T--S fuzzy modeling and control. Moreover, the derived stability and stabilizability conditions are represented in terms of SOS and can be numerically (partially symbolically) solved via the recently developed SOSTOOLS. To illustrate the validity and applicability of the proposed approach, a number of analysis and design examples are provided. The first example shows that the SOS approach renders more relaxed stability results than those of both the LMI-based approaches and a polynomial system approach. The second example presents an extensive application of the SOS approach in comparison with a piecewise Lyapunov function approach. The last example is a design exercise that demonstrates the viability of the SOS-based approach to synthesizing a stabilizing controller.      

Relaxed delay-dependent stabilization criteria for discrete-time fuzzy systems based on a switching fuzzy model and piecewise Lyapunov functions

This paper presents delay-dependent stability analysis and controller synthesis methods for discrete-time Takagi-Sugeno （T-S） fuzzy systems with time delays. The T-S fuzzy system is transformed to an equivalent switching fuzzy system. Consequently, the delay-dependent stabilization criteria are derived for the switching fuzzy system based on the piecewise Lyapunov function. The proposed conditions are given in terms of linear matrix inequalities （LMIs）. The interactions among the fuzzy subsystems are considered in each subregion, and accordingly the proposed conditions are less conservative than the previous results. Since only a set of LMIs is involved, the controller design is quite simple and numerically tractable. Finally, a design example is given to show the validity of the proposed method.     

Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm

In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi–Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.     

Stability analysis of discrete-time fuzzy dynamic systems based on piecewise Lyapunov functions

This paper presents a stability analysis method for discrete-time Takagi-Sugeno fuzzy dynamic systems based on a piecewise smooth Lyapunov function. It is shown that the stability of the fuzzy dynamic system can be established if a piecewise Lyapunov function can be constructed, and moreover, the function can be obtained by solving a set of linear matrix inequalities that is numerically feasible with commercially available software. It is also demonstrated via numerical examples that the stability result based on the piecewise quadratic Lyapunov functions is less conservative than that based on the common quadratic Lyapunov functions.     

GH2 Control for Uncertain Discrete-time-delay Fuzzy Systems Based on a Switching Fuzzy Model and Piecewise Lyapunov Function

Generalized H2 (GH2) stability analysis and controller design of the uncertain discrete-time Takagi-Sugeno (T-S) fuzzy systems with state delay are studied based on a switching fuzzy model and piecewise Lyapunov function. GH2 stability sufficient conditions are derived in terms of linear matrix inequalities (LMIs). The interactions among the fuzzy subsystems are considered. Therefore, the proposed conditions are less conservative than the previous results. Since only a set of LMIs is involved, the controller design is quite simple and numerically tractable. To illustrate the validity of the proposed method, a design example is provided.     

一类T-S模糊控制系统的稳定性分析及设计

研究了一类输入采用双交叠模糊分划的T-S模糊控制系统稳定性分析及控制器设计问题.基于分段模糊Lyapunov函数,提出了一个新的判定开环T-S模糊系统稳定性的充分条件,该方法只需在各个模糊区间里满足模糊Lyapunov方法中的条件,其保守性比公共Lyapunov函数法和分段Lyapunov函数法的保守性更低.运用并行分布补偿法(PDC)进一步探讨了闭环T-S模糊控制系统的稳定性分析问题并设计了模糊控制器.最后,一个仿真示例说明了本文方法的有效性.     

Stability analysis and H/sub /spl infin// controller design of fuzzy large-scale systems based on piecewise Lyapunov functions

This paper presents a novel approach to stability analysis of a fuzzy large-scale system in which the system is composed of a number of Takagi-Sugeno (T-S) fuzzy subsystems with interconnections. The stability analysis is based on Lyapunov functions that are continuous and piecewise quadratic. It is shown that the stability of the fuzzy large-scale systems can be established if a piecewise Lyapunov function can be constructed, and, moreover, the function can be obtained by solving a set of linear matrix inequalities (LMIs) that are numerically feasible. It is also demonstrated via a numerical example that the stability result based on the piecewise quadratic Lyapunov functions is less conservative than that based on the common quadratic Lyapunov functions. The H/sub /spl infin// controllers can also be designed by solving a set of LMIs based on these powerful piecewise quadratic Lyapunov functions.