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Nonlinear Control System Design Based on Stochastic Robustness Metric and its Application to Integrated Vehide Chassis Control

基于随机鲁棒性度量的非线性控制系统设计及其在车辆底盘集成控制中的应用

基本信息

批准号：
16560215
负责人：
HORIUCHI Shinichiro
金额：
$ 1.15万
依托单位：
Nihon University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2005
项目状态：
已结题

项目摘要

For the design of the nonlinear control systems, robustness is necessary to determine the possibility of instability or inadequate performance in the face of uncertain variation of system dynamics. From this point of view, several design method for nonlinear control system were proposed based on robust control theories such as H_∞ control and μ analysis/synthesis. These approaches assume that the dynamics of controlled system can be described by the linear-time-invariant model and using a singular-value as a metric, the robustness to system dynamics variations is treated as a deterministic way. However it is difficult to express real uncertainty in deterministic form that is required by the theories, and the relationship between the metric of robustness and parameter variations in the physical system is weak.This study investigates the feasibility of applying the stochastic method to the evaluation and design of nonlinear control systems. The controlled system dynamics is modeled by no … More nlinear dynamic equations containing uncertain system parameters. The system robustness is characterized by the probability of instability and probabilities of violation of prescribed performance indexes, subject to the variation of uncertain system parameters. These probabilities are estimated by applying Monte Carlo method to the results of a large number of simulations. To reduce the computational time, a parallel processing system composed of a master computer and nine slave computers is constructed. A performance index consists of weighted sum of the estimated probabilities is optimized by Genetic Algorithm.The proposed method is applied to the design of vehicle dynamics control system. Four types of vehicle control strategies are chosen to demonstrate the effectiveness of stochastic method to analyze the robustness of the control systems. Then the stochastic method is applied to the design of the nonlinear vehicle control systems. A stochastic cost function containing engineering design criterion is minimized by Genetic Algorithm, producing optimal controller parameters for given control structures. The stochastic approach improves the robustness of the vehicle control systems Less

对于非线性控制系统的设计，鲁棒性是必要的，以确定在面对系统动态的不确定性变化的不稳定或性能不足的可能性。从这一角度出发，基于H_∞控制和μ分析/综合等鲁棒控制理论，提出了几种非线性控制系统的设计方法。这些方法假定被控系统的动态特性可用线性时不变模型描述，并以奇异值作为度量，将系统对动态特性变化的鲁棒性视为确定性的。然而，由于理论上要求的真实的不确定性很难用确定性的形式表示，而且鲁棒性度量与物理系统中参数变化之间的关系也很弱，因此本文研究了将随机方法应用于非线性控制系统的评估和设计的可行性。被控系统的动力学模型，没有 ...更多信息含有不确定系统参数的非线性动力学方程。系统的鲁棒性是指在不确定系统参数变化的情况下，系统发生失稳的概率和违反预定性能指标的概率。这些概率是通过对大量模拟的结果应用蒙特卡罗方法来估计的。为了减少计算时间，构造了一个由一台主机和九台从机组成的并行处理系统。采用遗传算法对由估计概率加权和组成的性能指标进行优化，并将该方法应用于车辆动力学控制系统的设计。选取了四种不同的车辆控制策略，验证了随机方法分析控制系统鲁棒性的有效性。然后将随机方法应用于非线性车辆控制系统的设计。利用遗传算法对包含工程设计准则的随机代价函数进行最小化，得到给定控制结构的最优控制器参数。随机方法提高了车辆控制系统的鲁棒性