基于PSO的变结构变时滞自校正控制

PSO-Based Self-Tuning Control for Time-Varying Delay and Variable Structure System

针对变结构、变时滞被控对象,将粒子群优化(PSO)算法与广义最小方差相结合,采用实时自校正过程对其进行控制,提出基于 PSO 自校正控制器算法.该算法应用隐式辨识方式,可减少辨识计算量,通过跟踪误差来改变辨识精度.以工业上典型的一阶、二阶和三阶系统的结构变化并伴随着有时滞突变的复杂被控对象进行仿真,并和基于最小二乘的传统自校正控制方法比较得知,在运用 PSO 自校正控制器的控制下,系统输出量与期望输出之间的方差趋于更小,控制跟随性和鲁棒性均较好.仿真结果表明该自校正控制器的有效性与应用价值.

A design method is presented for the self-tuning control algorithm in a time-varying delay and variable structure system. A self-tuning regulator is optimized by the particle swarm optimization （PSO） algorithm, combined with generalized minimum variance. Using an implicit identification, the method can track the errors of the system to increase the precision and decrease the computational burden. It is adaptable for the typical industrial process control, especially for time-varying and large time-delay models. Results of simulation and comparison show its advantages in robust and tracing precision.