基于IGHS算法的分段系统鲁棒极点配置优化

针对分段线性控制系统鲁棒极点配置问题,利用IGHS算法对特征向量矩阵条件数优化具有较好的收敛性,限制了特征向量选择的自由度.优化后的控制器使闭环系统矩阵允许有更大的摄动或不确定性.与已有方法相比,本文方法对条件数优化计算既不需要考虑梯度和二次可微信息,也不需要对条件数进行凸转化处理.最后,仿真实验结果验证了本方法的有效性.     

鲁棒极点配置的优化算法

本文研究了一类线性多变量系统的鲁棒极点配置问题，提出了一种基于目标函数优化的鲁棒极点配置算法，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∞范数作为极点配置寻优的准则函数，在这个准则下，通过解优化问题的途径确定极点配置问题中的自由参数，从而达到鲁棒极点配置的目的。     

一种鲁棒自适应极点配置预估控制器

本文提出一种鲁棒自适应极点配置预估控制新方法。它有效地克服了因对象模型与史密斯预估模型不同而引起的系统不稳定现象。     

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。     

鲁棒极点配置约束下的模糊控制系统设计

针对一类利用T-S模糊模型近似描述的不确定非线性系统,给出了一种具有鲁棒极点配置功能的模糊控制器和模糊状态观测器的设计方法.首先,利用并行分配补偿(PDC)设计思想和基于线性矩阵不等式(LMI)的鲁棒极点配置理论,得到了使整个闭环系统全局渐近稳定并满足希望的动态性能的充分条件.然后将这些条件转化为标准的LMI问题.最后将该设计方法应用于倒立摆的平衡控制中,验证了本方法的有效性.     

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.     

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。     

空气压伺服系统鲁棒极点配置控制

本文以文献[1]的理论为基础,对空气压驱动系统活塞移动速度的鲁棒控制进行了研究,并把控制结果与PID控制进行了比较。     

鲁棒极点配置控制系统的一种设计方法

本文提出了系统特征系数灵敏度的概念,导出了特征系数灵敏度与特征值灵敏度闻的关系.在此基础上,提出了一种以加权特征系数灵敏度为性能指标,结构化小参数摄动下的鲁棒极点配置控制系统的设计方法.特征系数灵敏度计算简单,目标函数的极小化采用标准的具有二次收敛性质的参数最优化方法.     

不确定广义系统的圆形区域极点配置

考虑不确定连续或离散广义系统的圆形区域极点配置问题, 目的是设计状态反 馈控制律, 使得闭环系统正则, 无脉冲(连续广义系统情形)或因果(离散广义系统情形), 且 闭环极点位于一给定的圆形区域内. 给出了所期望的状态反馈控制律存在的充分条件及其解 析表达式.     

On pole structure assignment in linear systems

The problem of pole structure assignment (PSA) by state feedback in implicit, linear and uncontrollable systems is discussed in the article. It is shown that the problem is solvable if the system is regularisable. Then necessary and sufficient conditions for characteristic polynomial assignment are established. In the case of PSA (invariant polynomials assignment) just necessary conditions have been obtained. But it turns out that these conditions are also sufficient in some special cases. This happens, for example, when the system does not possess any non-proper controllability indexes. A possible application of the achieved results to modelling a constrained movement of a robot arm is outlined, too.     

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.     

区域极点配置问题的研究方法

对区域极点配置的现有研究成果进行综述.将区域极点配置的基本方法归结为代数Riccati方程(ARE)方法和线性矩阵不等式(LMI)方法.列出了基于区域极点配置方法的主要研究成果,包括最优控制、鲁棒性、H2性能、H∞性能等方面.最后给出了几点研究展望.     

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.     

On pole assignment of linear systems by gain output feedback

In this paper, the Geometric Approach is used to derive in a straightforward way a sufficient condition for pole assignability by gain output feedback. This result leads to a pole assignment procedure which reduces to solving a system of min (n - m, n - p) polynomial equations where n is the number of states, m the number of inputs, p the number of outputs. In the case where m + p > n, this system clearly appears to be linear. The degrees of freedom related to the pole assignment problem are expressed in terms of (right or left) eigenvectors.     

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.     

Eigenvalue assignment via uncertain state feedback controllers

In this paper, we propose a method for eigenvalue assignment using linear control systems containing uncertain elements. Uncertain systems are systems described by state equations which depend on uncertain parameters. In this paper, uncertainty is modeled with interval numbers. The proposed method assigns prescribed eigenvalues to a state feedback control system. Also, we introduce two interval operations to be used in our method use them. Some numerical experiments are presented to illustrate the effectiveness of the proposed method.