基于粒子群优化的分数阶PID滑模控制参数整定

为了提高系统的控制性能,解决单一控制方法不足,将分数阶PID算法与滑模变结构算法相结合,同时为了规避分数阶PID的滑模变结构算法手动调节参数的复杂性以及不确定性,采用粒子群算法对其参数进行优化,完善分数阶PID的滑模变结构控制器,提高其控制精度.并将新型算法应用于单相全桥逆变器,通过Matlab仿真并与分数阶PID滑模变结构控制函数(PID-SMC)及滑模变结构控制(SMC)方法相比较,研究结果表明,粒子群算法整定参数收敛速度快,较短时间内可以找出最优解,整定后的算法静态误差小,上升速度快,抑制系统抖振能力强,具有较强的鲁棒性.

Parameter Tuning of Fractional-Order PID Sliding Mode Control Based on Particle Swarm Optimization

In order to improve the control performance of the system and solve the problem of single control method,the fractional order PID algorithm and the sliding mode algorithm are combined.At the same time,the parameters are optimized by particle swarm optimization(PSO) to improve the fractional order PID sliding mode controller,the precision of control is improved,which can avoid complexity and uncertainty of tuning parameters in fractional-order PID sliding mode control(SMC) by manual regulation.The new design method is applied to single-phase full-bridge inverter.After simulation in Matlab,compared with fractional-order PID sliding mode control function (PID-SMC) and SMC,the results show that the convergence speed is fast and the time is short to find the optimum of tuning parameter by PSO.The tuning algorithm has advantages of small steady state error,fast rising speed,strong ability to restrain system chattering and stronger robustness.