快速车辆动力学控制的鲁棒模型预测控制

T. Péni, J. Bokor
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引用次数: 3

摘要

针对动态速度较快的离散时间不确定系统,即计算下一个控制动作所需的时间为采样时间的倍数,提出了一种简单的鲁棒模型预测算法。该方法基于以下概念:在k时刻确定所有可能的k+N个状态的集合,并在接下来的N个时间步中构造适当的反馈增益,该增益能够使系统从k+N时刻开始鲁棒稳定。在时间k+N时,重复该过程。该方法源自Kothare等人(1996)提出的鲁棒MPC算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Model Predictive Control for Controlling Fast Vehicle Dynamics
This paper proposes a simple robust model predictive algorithm for discrete time uncertain systems having relatively fast dynamics, i.e. the time required to compute the next control action is the multiple of the sampling time. The method is based on the following concept: at time k the set of all possible k+N-th states is determined, and in the next N time steps an appropriate feedback gain is constructed, which is capable of robustly stabilizing the system from time k+N. At time k+N the procedure is then repeated. The method was derived from the robust MPC algorithm proposed by Kothare et al.,(1996)
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