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.     

实现输出反馈极点配置的数值方法

本文讨论了用数值方法实现输出反馈极点配置的问题.求解反馈阵的矩阵方程被等效成 非线性向量方程,用牛顿迭代法可求得反馈阵.本文推导了牛顿迭代法所需的导数公式,并给 出有关算例.还可将非线性向量方程化作性能指标,用寻优的方法求得所需的输出反馈阵.     

线性离散不确定系统区域极点配置的状态反馈实现方法

研究利用状态反馈对线性离散不确定系统进行区域极点配置的问题。导出了一个由离散代数Ｒｉｃａｔｉ方程表示的对线性离散不确定系统进行区域极点配置的充分条件,并给出了一个通过求解该方程来确定状态反馈增益矩阵的算法。     

输入多采样率数字控制系统的同时极点配置

在利用提升(lifting)技术所构造出来的多采样率数字控制系统的线性时不变状态空间模型的基础上, 讨论l个被控对象通过输入多采样率数字控制系统的同时极点配置问题. 分别引入了解决这一问题的状态空间方法和多项式矩阵插值方法. 通过适当的变换, 将同时极点配置问题归结为一系列线性方程组的求解问题. 指出, 当系统的输入采样率满足一定条件时, 可以利用输入多采样率的输出静态反馈控制系统, 实现对l个被控对象的同时极点配置.     

基于BMI方法的扇形极点配置输出反馈控制

研究一类线性系统在有界静态输出反馈下的区域极点配置问题, 给出了问题可解的双线性矩阵不等式(Bilinear matrix inequality, BMI)条件. 利用摄动线性化方法给出了求解期望输出反馈的迭代线性矩阵不等式(Linear matrix inequality, LMI)算法, 并用算例说明了所提算法的有效性.     

具有H2／H∞混合性能约束的离散系统的极点配置

本文主要研究具有H_2/H_∞混合性能约束的线性离散系统的极点配置问题,首先将这一问题转化为一个具有H_∞性能和系统闭环极点位置约束的系统H_2性能优化问题,进而通过引入一个辅助性能函数,进一步将其转化成有一个矩阵方程约束的辅助性能函数的最小化优化问题,并给出这个问题静态输出反馈和状态反馈控制器的解的表达式。     

一种抗参数变化的最优控制器设计方法

本文描述了一种抗参数扰动的最优控制器设计方法。它从解 Sylvester 矩阵方程入手,求取状态反馈增益 F,来配置期望的闭环极点。另一方面,又充分利用了多输入状态反馈配置闭环极点以外的自由度,使控制系统设计达到多目标最优。实例及仿真结果表明:由最优控制器构成的闭环系统,既能获得满意的瞬态响应,又具有较强的抗参数变化的能力。     

双率系统极点配置自校正控制算法

针对控制输入频率是输出采样频率整数倍的双率系统,研究了极点配置自校正控制方法.由于双率采样数据系统存在未知的采样间输出(即损失输出),所以传统输入输出等周期单率系统极点配置自校正控制方法不适用于双率系统.为了解决这一困难,本文直接利用双率输入输出数据估算系统模型参数和采样间输出,进一步把估计的模型参数代入极点配置方程,通过求解多项式Diophantine方程.推导了被控系统控制律,给出了双率极点配置自校正控制算法.一个仿真例子说明双率系统极点配置算法的控制效果.     

线线离散不确定系统区域极点配置的状态反馈实现方法

研究利用状态反馈对线性离散不确定系统进行区域极点配置的问题。导出了一个由离散代数Ｒｉｃｃａｔｉ方程表示的对线性离散不确定系统进行区域极点配置的充分条件,并给出了一个通过求解该方法来确定状态反馈增益矩阵的算法。     

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。     

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.     

A new approach to eigenstructure assignment by output feedback

The eigenstructure assignment problem for a linear time invariant multi-input-multi-output system using output feedback is considered. A new approach is developed which identifies the eigenspaces for the desired set of all the closed-loop eigenvalues. For the assignment of this desired set, necessary and sufficient conditions are established. These conditions contain two coupled Sylvester matrix equations, one of which is proven to be a reduced-order square Sylvester matrix equation. This results in an efficient analytical procedure, numerically superior to known techniques, for the determination of the output feedback gain-matrix     

切换系统输出反馈镇定的特征结构配置方法

考虑由单输入--单输出线性子系统构成的切换系统, 通过解析方法设计输出反馈控制, 使闭环子系统具有公共二次Lyapunov函数. 基于可解Lie代数条件及广义Sylvester方程的通解, 利用特征结构配置方法建立了反馈控制的存在性准则, 并由此给出了控制器的设计形式. 仿真算例实现了设计过程并验证了方法的有效性.     

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.     

A recurrent neural network for solving Sylvester equation with time-varying coefficients

Presents a recurrent neural network for solving the Sylvester equation with time-varying coefficient matrices. The recurrent neural network with implicit dynamics is deliberately developed in the way that its trajectory is guaranteed to converge exponentially to the time-varying solution of a given Sylvester equation. Theoretical results of convergence and sensitivity analysis are presented to show the desirable properties of the recurrent neural network. Simulation results of time-varying matrix inversion and online nonlinear output regulation via pole assignment for the ball and beam system and the inverted pendulum on a cart system are also included to demonstrate the effectiveness and performance of the proposed neural network.     

Satisfactory control of discrete-time linear periodic systems

In this paper satisfactory control for discrete-time linear periodic systems is studied. Based on a suitable time-invariant state sampled reformulation, periodic state feedback controller has been designed such that desired requirements of steady state covariance, H-infinity rejection bound and regional pole assignment for the periodic system are met simultaneously. By using satisfactory control theory, the problem of satisfactory periodic controller can be transformed into a linear programming problem subject to a set of linear matrix inequalities （LMIs）, and a feasible designing approach is presented via LMI technique. Numeric example validates the obtained conclusion.     

Eigenstructure assignment by decentralized output feedback-acomplete parametric approach

The problem of eigenstructure assignment in multivariable linear systems by decentralized output feedback is considered. By using a complete parametric solution of a generalized Sylvester matrix equation, parametric representations of both the left and right closed-loop eigenvectors and generalized eigenvectors as well as the feedback gains with respect to the closed-loop eigenvalues and two series of partially free parameter vectors are established. The obtained result does not require any conditions on the closed-loop eigenvalues, and generalizes some previous results in this area. An example shows the effect of the proposed approach     

ESA in high‐order linear systems via output feedback

This paper considers eigenstructure assignment in high‐order linear systems via output feedback. Parametric expressions for the left and right closed‐loop eigenvectors associated with the finite closed‐loop eigenvalues and two simple and complete parametric solutions for the feedback gain matrices are obtained on the basis of the parametric solutions of the generalized high‐order Sylvester matrix equations. This approach does not impose any restrictions on the closed‐loop eigenvalues. An illustrative example shows the effect of the proposed approach. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Multiobjective controller synthesis via eigenstructure assignment with state feedback

A general parameter scheme for multiobjective controller synthesis via eigenstructure assignment with state feedback is proposed. The scheme provides total pole configurability, that is, pole assignment constraints, partial pole assignment constraints, generalised regional pole assignment constraints can be dealt with simultaneously without introducing essential conservatism. The scheme is derived from the pole assignment approach using Sylvester equations, and the parameter space is the Cartesian product of some subspaces characterising the free parameters. Under the scheme, the controller design problems are formulated as nonlinear optimisation problems with both objectives and constraints being differentiable and can be solved by derivative-based nonlinear programming technique. Numerical examples are given to illustrate the efficiency of the proposed method.