Development of stochastic optimal controller for Itô uncertain model of active suspension system

Alireza Ramezani Moghadam, H. Kebriaei
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引用次数: 1

Abstract

In this paper, Itô-type stochastic optimal control approach for uncertain model of vehicle suspension is developed. The model of quarter-car is constructed using linear characteristics of damping and springs. In order to elicit Itô stochastic dynamic of vehicle, parametric perturbations of sprung damping and spring characteristics are taken into account. Furthermore, the road disturbance is considered as a Gaussian white noise process. By using stochastic Hamilton-Jacobi-Bellman method, the stochastic optimal linear quadratic regulator controller for active suspension system is designed. Based on the concept of stochastic stability and using extension of Lyapunov method for Itô uncertain models, it is proven that the optimal control law, stochastically stabilizes the active perturbed suspension system. Moreover, it is shown that the well-known linear quadratic Gaussian controller cannot stabilize the perturbed system in certain conditions given by a linear matrix inequality. A simulation study is performed to evaluate the effectiveness of proposed stochastic control approach.
主动悬架系统Itô不确定模型随机最优控制器的研制
本文提出了汽车悬架不确定模型的Itô-type随机最优控制方法。利用阻尼和弹簧的线性特性建立了四分之一小车的模型。为了得到车辆的Itô随机动力学,考虑了弹簧阻尼和弹簧特性的参数摄动。进一步,将路面扰动视为高斯白噪声过程。采用随机Hamilton-Jacobi-Bellman方法,设计了主动悬架系统的随机最优线性二次型调节器控制器。基于随机稳定性的概念,利用Itô不确定模型的Lyapunov方法的推广,证明了最优控制律能使主动摄动悬架系统随机稳定。此外,在由线性矩阵不等式给出的一定条件下,证明了众所周知的线性二次高斯控制器不能使摄动系统稳定。通过仿真研究来评价所提出的随机控制方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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