参数化鲁棒极点配置方法

研究了一类线性多变量系统鲁棒控制器的设计问题，提出了一种基于极点配置和目标函数优化的鲁棒极点配置方法。解决问题的基本思想是，利用极点配置的参数化表示结果，以系统输出的Ｌ∝范数作为极点配置的鲁棒性准则，给出鲁棒极点配置的优化命题。通过解这一优化命题确定极点配置问题中的自由参数，从而达到设计鲁棒控制器的目的。     

一种鲁棒极点配置方法

本文研究具有参数不确定性系统的鲁棒极点配置问题,根据对系统的各种性能指标要求给出综合性能指标，采用极点着色优化算法，给出了满足鲁棒极点配置的反馈K阵，研究了K阵选择的保守性问题，设计实例说明了本文所提算法的有效性。     

矩阵二阶系统的鲁棒极点配置

直接在矩阵二阶框架下,利用特征结构配置参数化方法,研究矩阵二阶线性系统的鲁棒极点配置问题.将两种测量闭环特征值灵敏度方法有机地结合起来,给出一个新的优化性能指标,此指标的优化过程完全依赖于特征结构配置中的设计自由度.为进一步提高闭环系统的鲁棒稳定性,闭环极点也作为设计自由度的一部分参与优化.数值例子分析结果表明了该方法的有效性.     

基于在线优化的线性系统状态反馈鲁棒镇定

建立关于Sylvester方程的鲁棒极点配置梯度流优化算法模型,在线求解相应的二次优化问题,并在线计算状态反馈增益矩阵.使得闭环系统矩阵的伞部特征值位于给定的区域中.对于一切满足条件的扰动,具有最小灵敏度,闭环系统人范围一致渐近稳定.仿真结果验证了该方法适用十非线性系统的鲁棒镇定问题和在线鲁棒极点配置问题.     

不确定连续系统的鲁棒H2/H∞滤波

研究凸多面体不确定连续系统的鲁棒H2／H∞滤波问题．为降低设计的保守性．提出一种新的具有参数依赖Lyapunov函数的鲁棒H2／H∞性能准则．基于该性能准则，推导出鲁棒H2／H∞滤波器存在的充分条件．并将滤波器设计问题转化为具有线性矩阵不等式（LMI）约束的参数优化问题．     

鲁棒极点配置控制器设计

采用多变量控制系统极点配置方法设计控制器时,往往有许多剩余的自由度.本文在极点配置方法的基础上,利用剩余自由度来优化一鲁棒性指标,提出了一种鲁棒极点配置控制器设计方法,推导了参数阵为鲁棒最优的必要条件,并给出了易于在计算机上实现的设计算法的计算步骤.     

圆形区域内鲁棒极点配置优化

本文基于和声搜索算法将精确极点配置的思想推广到圆形区域极点配置,通过对圆域内极点全局优化的方法,实现圆域内鲁棒极点配置问题.首先,基于几何原理描述极点在圆形区域内的位置信息,确定了在圆形区域内动态选择极点的规则,可以保证算法在圆形区域内动态选取极点.然后,对圆形区域内的极点,基于精确鲁棒极点配置的思想,利用和声搜索算法优化摄动或不确定性的谱范数上界,从而得到一组允许闭环系统具有更大摄动或不确定性的极点及相应的状态反馈控制器.最后,通过实例进行仿真,仿真结果表明本文采用和声搜索算法全局优化动态选择极点方法得到的闭环系统具有更好的鲁棒性.     

一类不确定参数系统鲁棒稳定界的解析分析与应用

研究一类具有不确定参数系统鲁棒性稳定界的解析分析方法，在定义了鲁棒稳定界的基础上，证明了鲁棒稳定只与标称系统的最小特征值有关，利用这一结论不仅可以方便地分析多项式的稳定性，而且可以根据系统的不确定性设计闭环控制系统的期望极点，并进行极点配置。     

基于输出反馈的鲁棒控制器优化设计及仿真

传统的控制系统,利用极点配置后所剩余的自由度来增强系统的鲁棒性,但解析算法复杂,在实际工程中难以应用.为优化算法,提高极点配置精度,提出了一种能满足工程实际要求的利用输出反馈来配置系统特征值和实现系统鲁棒性能最优的逼近算法.方法通过选定一种反应极点配置精度和表征系统鲁棒性的目标函数,利用最优化中的Powell算法,在实现期望特征值的近似任意配置的同时,提高了系统的鲁棒性能.方法具有易于实现和适用面广等特性.并以水翼艇纵向运动控制系统为例进行了仿真,取得了令人满意的结果.     

非线性系统具有圆盘极点约束的鲁棒模糊控制

针对一类具有范数有界时变参数不确定性的离散非线性系统,研究其具有圆盘极点约束的鲁棒模糊控制问题．采用T—S模糊模型逼近实际的离散非线性系统,结合并行分布补偿法和二次型性能指标,导出了保证闭环系统鲁棒稳定且所有极点配置在预先指定圆盘中的二次圆域稳定保性能控制器的存在条件,并将最优保性能控制器的设计问题可归结为求解一个线性矩阵不等式的凸优化问题．最后的仿真结果验证了设计方法的有效性．     

Design Of Robust Pole Assignment Based On Pareto‐Optimal Solutions

In this paper, a new design method for robust pole assignment based on Pareto‐optimal solutions for an uncertain plant is proposed. The proposed design method is defined as a two‐objective optimization problem in which optimization of the settling time and damping ratio is translated into a pole assignment problem. The uncertainties of the plant are represented as a polytope of polynomials, and the design cost is reduced by using the edge theorem. The genetic algorithm is applied to optimize this problem because of its multiple search property. In order to demonstrate the effectiveness of the proposed design method, we applied the proposed design method to a magnetic levitation system.     

Dominant pole and eigenstructure assignment for positive systems with state feedback

In this paper, the dominant pole assignment problem, the dominant eigenstructure assignment problem and the robust dominant pole assignment problem for linear time-invariant positive systems with state feedback are considered. The dominant pole assignment problem is formulated as a linear programming problem, and the dominant eigenstructure problem is formulated as a quasiconvex optimisation problem with linear constraints. The robust dominant pole assignment problem is formulated as a non-convex optimisation problem with non-linear constraints which is solved using particle swarm optimisation (PSO) with an efficient scheme which employs the dominant eigenstructure assignment technique to accelerate the convergence of the PSO procedure. Each of the three problems can be further constrained by requiring that the controller has a pre-specified structure, or the gain matrix have both elementwise upper and lower bounds. These constraints can be incorporated into the proposed scheme without increasing the complexity of the algorithms. Both the continuous-time case and the discrete-time case are treated in the paper.     

多变量系统鲁棒性复数极点配置的一种新方法*

本文对线性定常多变量系统的鲁棒性极点配置问题,给出了一种算法。这个算法对指定闭环极点中含共轭复极点的情形,用起来十分方便,它把一个带约束优化问题变成了一个无约束优化问题求解,本文末还给出了一个数值例子。     

A gradient flow approach to on-line robust pole assignment for synthesizing output feedback control systems

Pole assignment is a basic design method for synthesis of feedback control systems. In this paper, a gradient flow approach is presented for robust pole assignment in synthesizing output feedback control systems. The proposed approach is shown to be capable of synthesizing linear output feedback control systems via on-line robust pole assignment. Convergence of the gradient flow can be guaranteed. Moreover, with appropriate design parameters the gradient flow converges exponentially to an optimal solution to the robust pole assignment problem and the closed-loop control system based on the gradient flow is globally exponentially stable. These desired properties make it possible to apply the proposed approach to slowly time-varying linear control systems. Simulation results are shown to demonstrate the effectiveness and advantages of the proposed approach.     

Augmented gradient flows for on-line robust pole assignment via state and output feedback

This paper is concerned with robust pole assignment in synthesis of linear control systems via state and output feedbacks. First, both the pole assignment and robustness requirements are appropriately formulated as two optimization problems. Then, gradient flow models are developed for the on-line computation of feedback gain matrices that result in robust pole assignment by solving these two optimization problems. A technique is introduced to facilitate the real-time matrix inverse involved for realizing the gradient flow models. The resulting augmented gradient flows have desired convergence properties. Simulation results are included to show the effectiveness of the proposed approach.     

用输出反馈配置鲁棒极点*

本文讨论了线性定常多变量系统在时域上用输出反馈配置鲁棒极点的问题。用输出反馈配置极点时,有一些自由度,可以利用这些自由度指定特征向量。本文给出一种数值方法,它用于选择一组尽可能正交的特征向量,使闭环系统矩阵A+BKC尽可能接近正规,从而使闭环极点对于矩阵的系数变化是鲁棒的。     

Robust partial pole assignment problem for high order control systems

In this paper, we consider the partial pole assignment problem (PPAP) for high order control systems. It is shown that solving the PPAP is essentially solving a pole assignment for a linear system of a much lower order, and the robust PPAP is then concerning the robust pole assignment problem for this linear system. Based on this theory, a rather simple algorithm for solving the robust PPAP is proposed, and numerical examples show that this algorithm does lead to comparable results with earlier algorithms, but at much lower computational cost.     

Robust eigenstructure assignment with minimum subspace separation

A computation method for delivering a state feedback controller that assigns closed‐loop eigenstructure with a minimum subspace separation and is robust towards unstructured perturbations is presented. The subspace separation is measured via the difference between two subspace projections, while the eigenstructure robustness is achieved by maximizing an upper bound on the allowable perturbation size such that the closed‐loop system remains stable. By exploiting the Sylvester equation parametrization, the constraint of pole assignment can be satisfied intrinsically and the robust eigenstructure assignment design essentially becomes an unconstrained optimization task. Analytical gradient formulas of the objective functions to be handled are developed. The design approach is demonstrated through numerical examples. Copyright © 2004 John Wiley & Sons, Ltd.     

Robust pole assignment for systems with parameters

In this paper we investigate issues related to the control of linear multivariate systems which contain structured, parametric-type uncertainties. The objective is to construct parameter-independent proper compensators that provide ‘robust control’. Specifically, we consider the question of robust pole assignment. Systems are described by matrix fraction representations which involve a structured parametric form of uncertainty. We suggest conditions for robust pole assignability and demonstrate how to construct the required proper compensators. For the problem considered, we show that the class of systems which satisfy these conditions is quite large and we include results on generic solvability. The method is demonstrated by a physical example.     

The infinite time near optimal decentralized regulator problem for singularly perturbed systems: a convex optimization approach

This paper presents LQ decentralized pole location for singularly perturbed systems. The poles are located in a sector included in the left-half complex plane. The singular perturbation method is used to define reduced and well-behaved problems. It is shown that the LQ control problem with pole location in a sector can be solved using the LMI tool. The associated parametrical optimization problem involves a linear cost objective under LMI constraints. The decentralized control problem is then solved in the reduced slow system by just introducing structure constraints on the matrix variables, constraints that do not destroy the linearity and then the convexity of the problem.