【摘要】 提出了一种基于人工免疫多目标寻优算法(AIMOA)的PID参数自适应整定的设计方法。利用生物免疫系统的免疫机理设计系统响应的目标函数,再通过AIMOA算法搜索PID控制器的优化参数组,最后将基于AIMOA算法同基于遗传算法(GA)和齐格勒—尼柯尔斯(Zi-Ni)方法的PID自整定进行了仿真比较。结果表明:AIMOA算法具有快速收敛性,能够较快地搜索到PID参数自适应整定的最优或者次最优解,体现了算法的优越性、实用性和有效性。更多还原

【Abstract】 A novel artificial immune multi-objective optimization algorithm(AIMOA) is presented,which is applied successfully to self-tuning of PID controller.Firstly,natural immunological mechanisms are used to design the optimum objective function of control system.Then,the global optimum parameters combination of PID self-tuning is located by AIMOA algorithm.Finally,the advantages of AIMOA algorithm for PID self-tuning are further highlighted through the comparison between the classical Ziegler-Nichols and GA method.AIMOA algorithm shows fast convergence,and it can be utilized to quickly locate the optimal or sub-optimal parameters of PID controller.Experiment results demonstrate that the proposed algorithm is valid,superior and effective.更多还原