基于SOA-MC算法的二自由度PID控制器优化设计

摘要

针对传统方法整定二自由度PID控制器参数难以避免外界扰动或系统参数摄动的问题,提出了一种人群搜索算法与膜计算耦合的混合算法(SOA-MC算法),将二自由度PID的控制参数编码成SOA-MC算法优化的对象,经过膜与膜之间的相互作用和交流传递信息找出复杂空间中的最优区域,引入自适应权重和精英策略提高全局搜索能力和收敛速度.并分别用传统方法和SOA-MC算法对隧道式加热炉温度控制系统进行MATLAB仿真.仿真结果表明,SOA-MC算法能够更好地实现二自由度PID控制器参数的调节,使系统具有优异的干扰抑制特性和设定值跟随特性.%In order to solve the problem that the two-degree freedom PID controller is difficult to avoid the external disturbance and the system parameter perturbation,a hybrid algorithm(SOA-MC algorithm) which combines the seeker optimization algorithm with the membrane computing is proposed.The control parameters of the two-degree -of-freedom PID were encoded into the optimized object of the SOA-MC algorithm,and the optimal region in the complex space was determined by the interaction and communication between the membranes.The global search ability and convergence speed were improved by introducing adaptive weight and elitist strategy.The experiments of traditional method and the SOA-MC algorithm used respectively in the temperature control system of tunnel stove were carried out based on MATLAB.The simulation results show that the SOA-MC algorithm can adjust the parameters of the two-degree freedom PID controller better,which enables the system to have the characteristics of interference suppression and settings following.