【作者】 王巍； 彭力；

【Author】 WANG Wei PENG Li School of Communication and Control Engineering,Southern Yangtze University,Wuxi 214122,China.

【机构】 江南大学 通信与控制工程学院；

【摘要】 微粒群算法是一种高效的并行搜索算法,但易于收敛到局部极值点．对此,采用非线性的 S 函数对算法中的参数进行自适应调整．通过 Shaffer’s F6函数的测试表明,这种非线性调整参数的微粒群算法相比于线性调整参数的算法,更易收敛到全局最优解．采用这种改进型的微粒群算法对二自由度 PID 的参数进行整定,仿真结果表明了该方法的有效性,可使控制器具有更好的性能．更多还原

【Abstract】 Particle swarm optimization(PSO)is a kind of effective and parallel search algorithm,but it is easy to fall into local optimization.For these disadvantages of PSO,adjusting adaptively and nonlinearly method of parameters in PSO is presented by using S-function.The improved method tested by function Shaffer’s F6 has better performance in global searching comparing with the method using linearly adjusting parameters.Then,the parameters of 2-degree-of- freedom PID(2-DOF PID)controller are tuned.The results show the effectiveness of the method in improving the controller performance.更多还原