随机伺服系统自适应二次最优组合控制

ADAPTIVE AND QUADRATIC OPTIMAL COMBINED CONTROL OF STOCHASTIC SERVO SYSTEMS

本文基于极点在线优化原理和随机过程理论,针对缓时变随机伺服系统提出一种参数自适应和二次性能最优的组合控制。这种控制形式简单、运算量小,能较好地适应系统的时变特性,并保持系统在不同参数与工况下具有最佳跟踪性能。文章讨论了控制的收敛性,并通过仿真和应用实例显示这种控制的有效性及良好的鲁棒性。

Based on the pole on-line optimization principle and stochastic process theory, a parameter adaptive and quadratic performance optimal combined control for slowly time-varying stochastic servo systems is proposed. With simple form and modified computational effort, this approach can fairly adapt to the time-varying characteristic of the systems and maintain system's optimal tracking property under different parameters and various working conditions. In the paper, convergence of the control is. also discussed and the effectiveness and robustness of the control is shown by simulation and practical application.