积分过程的PID控制器智能优化设计

针对积分时滞过程,采用微粒群优化(PSO)算法对比例-积分-微分(PID)控制器的参数进行优化设计.通过将PID控制器的参数设置为群体微粒在参数空间中的位置,模拟群体智能和动物觅食的动态行为来对PID参数寻优,使代表PID控制器参数的微粒逐渐向最优区域移动,获得最佳的PID参数.在优化过程中采用了偏差平方积分(ISE)的优化指标.实例仿真结果表明,基于微粒群算法优化得到的PID控制器不仅响应速度快、超调量小、抗干扰能力强,而且对过程时滞的变化具有较强的鲁棒性.

Intelligent optimization design of PID controller for integrating processes

Particle swarm optimization (PSO) algorithm was used to find the optimum parameters of proportional-integral-derivative (PID) controller for integrator plus time delay processes. The positions of each particle in the parameter spaces were set as the parameters of PID controller. The optimization strategy deduced from the simulation of swarm intelligence and dynamic behavior of animal forging was introduced to drive the current parameters of PID controller to the optimal area. Then the optimal PID controller was obtained. During the optimization process, the index with the integral of the squared error (ISE) was adopted. The simulation results for a integrator plus time delay process show that the optimal PID controller based on PSO is superior in set time and overshoot to other several PID controllers based on the conventional tuning methods.