基于适应性遗传算法的滑模控制感应电机伺服驱动系统研究

根据感应电机伺服系统高精度、快响应的要求,以及传统的滑模变结构控制器涉及较多的参数和逻辑判断次数等缺点,设计了一种简化的滑模控制律,并用Lyapunov稳定性理论证明了控制系统的稳定性,然后利用自适应遗传算法优化滑模控制律中涉及的参数,得到控制器最佳的参数组合.试验结果表明：该控制策略不仅有效地减小了滑模控制的抖振,且大大提高了系统的快速响应能力,系统具有较好的动、静态性能以及抗干扰能力.控制策略具有设计过程简单、意义清晰等优点,对于高精度、快响应的感应电机伺服系统,它是一种有效的实时控制策略.

SLIDING-MODE CONTROLLED INDUCTION MOTOR SERVO DRIVE SYSTEM VIA AGA OPTIMIZATION

Considering the requirement of high performance of induction motor servo system, more parameters and more time of logic determine are the major drawback in the variable structure control, this paper design such a system with a simple sliding-mode position controller based on adaptive genetic algorithms optimization. The novel control rue can reduce the time of logic determine. The analysis and proposed methods were verified by simulation and experimentation. For AC system in practice, the ranger of parameters can be chosen correctly with applying matlab design. The adaptive genetic algorithms can quickly search the optimal parameters in our design. The results of simulations and experimentation show, both dynamic and steady performance are improved evidently and the results are satisfactory.