基于VCGA 2-DOF PID控制器优化设计

遗传算法提供了一种复杂系统优化问题求解的通用框架，它通过对生物遗传和进化过程的模仿，来实现对问题的最优解的自适应搜索。针对基本遗传算法应用中早熟和慢收敛问题，应用改进的遗传算法，将适应度引入对操作因子的自适应调整。并给出了基于Matlab鳊程的实例。在此基础上，针对二自由PID的控制器优化设计问题，运用改进的遗传算法，在Matlab上进行了控制器参数的设计和仿真。结果表明，改进的遗传算法具有更快的收敛速度、更高的效率及全局收敛性，是一种适于工程应用的参数寻优方法。

VCGA Based Optimal Design for 2-DOF PID Controller

The genetic algorithms(GA) provide a universal frame to solve complex optimal problems.By imitating the mechanism of heredity and evolution of biology,the algorithm fulfills the adaptive search of the optimized solution.By the adoption of variant canonical GA(VCGA),in which the operators in Gas can be adaptively tuned by the fitness,the defects of premature and slow convergence in basic Gas are effectively overcome.The optimal design of the controller for 2-DOF PID with Matlab is realized.The results of the simulation show that the VCGA possesses higher convergent speed and global convergence,and is a good method to engineering application.