基于量子遗传算法的PID控制器参数自整定

提出了一种基于量子遗传算法（QGA）的PID控制器参数整定方法。首先定义一个包含表示系统超调量、上升时间和稳态误差指标项的适应度函数，并根据实际系统的性能要求对指标项进行适当加权。之后采用具有量子比特个体表示形式和量子旋转门实现种群进化的量子遗传算法，对PID进行多目标寻优，从而实现PID参数的自动整定。仿真结果表明，该方法优化得到PID控制器的综合性能优于常规方法和一般遗传算法得到的PID控制器。

Parameter self-tuning of PID controllers based on quantum Genetic Algorithms

A novel parameter tuning method of PID controllers based on quantum genetic algorithms is proposed.First,a fitness function which includes some terms represent overshoot,rise time and steady error of the system is defined,and the terms are weighted properly according to the demand of the actual system.Then a quantum genetic algorithm,which represents chromosomes with quantum bits and realizes population evolution with the quantum rotation gate,is used for multi-objective optimization of PID.So the parameter self-tuning of PID controllers can be achieved.Simulation results show that the comprehensive performance of PID controllers obtained by the proposed method superior to that by conventional methods and genetic algorithms.