不确定非线性系统的鲁棒H∞控制分析与综合

讨论一类仿射非线性系统的鲁棒H∞控制问题.针对自由系统,外部干扰输入矩阵和控制输入矩阵都具有加法不确定性的系统,将鲁棒性能的分析和综合归结为求解一组Hamilton-Jacobi不等式,给出了确保非线性控制系统满足鲁棒干扰抑制性能的充分条件,获得了非线性鲁棒控制器的一种形式.一个仿真例子验证了所得结论的正确性.     

一类不确定非线性系统的鲁棒H∞控制

在一种工程应用背景之下, 考虑了一类非线性系统的鲁棒H_∞ 控制问题, 不确定性范数有界, 基于HJI不等式研究了状态反馈控制器设计问题, 使得闭环系统满足H_∞ 干扰抑制性能要求.     

不确定Delta算子系统的鲁棒H∞重构控制

讨论一类含有参数不确定和执行器故障的Delta算子系统鲁棒H_∞ 重构控制设计问题. 通过利用故障检测与隔离(FDI)技术, 在考虑不可检测故障执行器输入为能量有界的干扰信号情形下, 基于H_∞ 干扰抑制的思想, 给出了系统可鲁棒H_∞ 镇定的充分条件. 所设计的控制器可使闭环系统鲁棒稳定, 而且对可允许的不确定性和执行器故障具有一定的H_∞ 性能. 数值例子说明了本文设计方法的有效性.     

基于模糊模型的时滞不确定系统的模糊H∞鲁棒反馈控制

讨论了一类具有状态和控制时滞的不确定非线性系统的模糊H_∞ 状态反馈控制问题. 采用具有时滞的不确定Takagi-Sugeno(T-S)模糊模型对非线性系统进行建模, 提出了一套基于LMI的模糊鲁棒控制器的系统设计方法, 给出了模糊H_∞状态反馈控制器存在的充分条件, 以保证闭环模糊系统渐近稳定并满足从干扰输入到控制输出的H_∞范数界约束. 示例仿真表明了该方法的有效性.     

具有非线性扰动的广义系统的鲁棒H∞控制

研究具有非线性结构扰动广义系统的鲁棒H_∞控制和鲁棒H_∞保性能控制问题,该不确定性为时间和状态的函数,且满足Lipschitz条件.目的是分别设计系统的鲁棒H_∞控制器和鲁棒H_∞保性能控制器.应用线性矩阵不等式方法,分别给出了系统的鲁棒H_∞控制器和鲁棒H_∞保性能控制器存在的充分条件.当这些条件可解时,分别给出了鲁棒H_∞控制器和鲁棒H_∞保性能控制器的表达式.最后通过一个仿真算例说明了所给出方法的应用.

     

一类具有L∞ 范数有界扰动的非线性系统鲁棒控制

首先针对不确定非线性系统, 基于 L_∞ 范数定义了鲁棒稳定化和鲁棒跟踪控制问题. 然后利用反馈线性化技术和Lyapunov方法, 设计了相应的鲁棒控制器. 仿真结果验证了控制器设计的正确性.     

基于Kp = S1D1U1分解的多变量鲁棒模型参考自适应控制

针对具有噪声的多变量系统, 利用高频增益矩阵K_p = S₁D₁U₁分解, 提出了一种多变量鲁棒直接型模型参考自适应控制. 通过重新证明一些同单变量系统鲁棒自适应控制理论相似的性质, 及重新定义规范化信号, 找出了闭环系统的所有信号与规范化信号之间的关系, 严格地分析了闭环系统的稳定性和鲁棒性.     

一类不确定时滞系统的鲁棒几乎干扰解耦问题

讨论了一类不确定时滞系统的具有稳定性的鲁棒H_∞ 几乎干扰解耦问题 (RADDPS), 利用线性矩阵不等式和代数Riccati方程方法分别得到了RADDPS可解的充分条件, 并且相应给出鲁棒静态状态反馈控制器的设计.     

不确定模糊Delta算子系统的鲁棒H∞控制

研究了一类T-S模糊Delta算子系统的鲁棒H_∞控制问题.首先利用LMI形式给出了模糊Delta算子系统鲁棒镇定的充分条件,然后构造了可使闭环系统鲁棒稳定且对可允许的参数变化满足H_∞性能的状态反馈控制律.本文结果统一了连续与离散模糊系统的鲁棒H_∞镇定设计结论,数值算例说明了方法的可行性.     

不确定脉冲系统的鲁棒H∞控制

首次提出并研究了不确定脉冲系统的鲁棒H_∞控制问题. 基于代数Riccati方程正定矩阵解的存在性, 建立了不确定脉冲闭环系统具有鲁棒H_∞特性的充分性准则, 同时给出了相应的状态反馈控制设计方法, 并用数值例子说明了所得结果的有效性.     

Robust Optimal Control of Nonlinear Systems With System Disturbance During Feedback Disruption

In this paper, a robust optimal control problem of nonlinear systems with system disturbance during feedback disruption is considered. This is an extended work of previous time‐delay optimal control results, by adding external disturbance in the considered system. It is shown that there exists an optimal input signal which keeps the performance error within the specified bound for the longest time. Then, it is shown that such an optimal input signal can be approximated by an implementable bang‐bang input signal in terms of control performance. Two examples are given for illustration.     

一类具有非线性扰动的多重时滞不确定系统鲁棒预测控制

针对一类具有非线性扰动且同时存在多重状态和输入时滞的不确定系统, 提出 一种鲁棒预测控制器设计方法. 基于预测控制滚动优化原理, 运用Lyapunov稳定性 理论和线性矩阵不等式 (Linear matrix inequalities, LMIs)方法, 首先近似求解无限时域二次性能指标优化问题, 然后优化非 线性扰动项所应满足的最大上界, 定量地研究鲁棒预测控制在范数有界意义下的扰动抑制 问题, 并给出了鲁棒预测控制器存在的充分条件. 最后通过仿真验证了所提方法的有效性.     

Decentralized robust output feedback control for control affine nonlinear interconnected systems

In this paper, a scheme for decentralized robust control for control affine nonlinear interconnected systems using linear matrix inequalities (LMIs) is presented. Based on the Lyapunov theory, sufficient conditions for closed-loop stability of a nonlinear system, reference input tracking, and disturbance attenuation over its operating-range are obtained. Then, achieving these sufficient conditions are formulated as local LMI optimization problems. By solving the appropriately defined local problems, provided the obtained sufficient conditions are satisfied, the closed-loop stability, input tracking, and disturbance attenuation over the operating-range of the system are guaranteed. The designed controller is linear whose implementation is straightforward. An example is given to illustrate the proposed methodology.     

Reconfigurable control of Hammerstein systems after actuator failures: stability,tracking, and performance

A new method for the reconfigurable control of stable Hammerstein systems with sector-bounded static nonlinear input characteristics subject to actuator failures is described. It aims at the recovery of the nominal stability, setpoint tracking, disturbance rejection and performance properties by the reconfigured closed-loop system. This article extends the virtual actuator from linear systems to Hammerstein systems and provides sufficient linear matrix inequality conditions for closed-loop stability, and a corresponding synthesis algorithm. It is shown that the approach is robust against uncertainties of the static input nonlinearity in a small-gain sense, and universal in a certain sense. Feasible setpoints for the reconfigured closed-loop system are characterised, and infeasible setpoints are projected to feasible ones. An extension guarantees minimum performance loss. The method is successfully experimentally evaluated using a system of interconnected tanks.     

Robust Tracking Control of Uncertain MIMO Nonlinear Systems with Application to UAVs

In this paper, we consider the robust adaptive tracking control of uncertain multi-input and multi-output (MIMO) nonlinear systems with input saturation and unknown external disturbance. The nonlinear disturbance observer (NDO) is employed to tackle the system uncertainty as well as the external disturbance. To handle the input saturation, an auxiliary system is constructed as a saturation compensator. By using the backstepping technique and the dynamic surface method, a robust adaptive tracking control scheme is developed. The closed-loop system is proved to be uniformly ultimately bounded thorough Lyapunov stability analysis. Simulation results with application to an unmanned aerial vehicle (UAV) demonstrate the effectiveness of the proposed robust control scheme.      

Barrier function based finite-time tracking control for a class of uncertain nonlinear systems with input saturation

In this article, a novel robust finite-time tracking control scheme is proposed for a class of uncertain nonlinear systems subject to the model uncertainty, external disturbance, and input saturation. A barrier function based disturbance observer (BFDO) with finite-time convergence performance is developed to estimate the non-smooth nonlinear compound disturbance, which includes the uncertainty, disturbance of system and input saturation. In addition, an adaptive continuous nonsingular terminal sliding mode controller, based on the barrier function and the estimate of the BFDO is developed. The Lyapunov stability and finite-time convergence of the proposed control scheme are proved. The effectiveness and performance advantage of the proposed control scheme is demonstrated by numerical simulations and comparison with existing works.     

Robust neural network tracking controller using simultaneous perturbation stochastic approximation

This paper considers the design of robust neural network tracking controllers for nonlinear systems. The neural network is used in the closed-loop system to estimate the nonlinear system function. We introduce the conic sector theory to establish a robust neural control system, with guaranteed boundedness for both the input/output (I/O) signals and the weights of the neural network. The neural network is trained by the simultaneous perturbation stochastic approximation (SPSA) method instead of the standard backpropagation (BP) algorithm. The proposed neural control system guarantees closed-loop stability of the estimation system, and a good tracking performance. The performance improvement of the proposed system over existing systems can be quantified in terms of preventing weight shifts, fast convergence, and robustness against system disturbance.     

Robust H∞ control for Van de Vusse reactor via T–S fuzzy bilinear scheme

This paper proposes a fuzzy bilinear scheme including a fuzzy modeling method and a fuzzy controller for a class of uncertain nonlinear systems with an additive disturbance input. Firstly, this procedure of modeling describes how to transform a nonlinear system into a fuzzy bilinear system (FBS). For controller design problem, the parallel distributed compensation (PDC) method is adopted to design a fuzzy controller which ensures the robust asymptotic stability of the uncertain T–S FBS with an additive disturbance input and guarantees an H_∞ norm bound constraint on disturbance attenuation. Besides, some sufficient conditions are derived to guarantee the robust stabilization of the overall fuzzy control system via linear matrix inequalities (LMIs). Finally, the Van de Vusse reactor (Chen, Lin, Lin, & Tong, 2008; Chong & Zak, 1996; Kashiwagi & Rong, 2002; Li, Tsai, Lee, Hsiao, & Chao, 2008; Perez, Ogunnaike, & Devasia, 2000) with additive disturbance input is utilized to demonstrate the validity and feasibility of the proposed control scheme.     

Robustness design of nonlinear dynamic systems via fuzzy linearcontrol

This study introduces a fuzzy linear control design method for nonlinear systems with optimal H^∞ robustness performance. First, the Takagi and Sugeno fuzzy linear model (1985) is employed to approximate a nonlinear system. Next, based on the fuzzy linear model, a fuzzy controller is developed to stabilize the nonlinear system, and at the same time the effect of external disturbance on control performance is attenuated to a minimum level. Thus based on the fuzzy linear model, H^∞ performance design can be achieved in nonlinear control systems. In the proposed fuzzy linear control method, the fuzzy linear model provides rough control to approximate the nonlinear control system, while the H^∞ scheme provides precise control to achieve the optimal robustness performance. Linear matrix inequality (LMI) techniques are employed to solve this robust fuzzy control problem. In the case that state variables are unavailable, a fuzzy observer-based H^∞ control is also proposed to achieve a robust optimization design for nonlinear systems. A simulation example is given to illustrate the performance of the proposed design method     

Robust control approach for input–output linearizable nonlinear systems using high‐gain disturbance observer

This paper addresses a robust control approach for a class of input–output linearizable nonlinear systems with uncertainties and modeling errors considered as unknown inputs. As known, the exact feedback linearization method can be applied to control input–output linearizable nonlinear systems, if all the states are available and modeling errors are negligible. The mentioned two prerequisites denote important problems in the field of classical nonlinear control. The solution approach developed in this contribution is using disturbance rejection by applying feedback of the uncertainties and modeling errors estimated by a specific high‐gain disturbance observer as unknown inputs. At the same time, the nonmeasured states can be calculated from the estimation of the transformed system states. The feasibility and conditions for the application of the approach on mechanical systems are discussed. A nonlinear multi‐input multi‐output mechanical system is taken as a simulation example to illustrate the application. The results show the robustness of the control design and plausible estimations of full‐rank disturbances.Copyright © 2012 John Wiley & Sons, Ltd.