基于PSO优化的非线性系统无模型控制方法  

Model Free Control Method Based on Particle Swarm Optimization for Nonlinear Systems

作　　者：李秀英[1] 韩志刚[1] 

机构地区：[1]黑龙江大学电子工程重点实验室,黑龙江哈尔滨150080

出　　处：《控制工程》2011年第6期861-863,965,共4页Control Engineering of China

基　　金：黑龙江省普通高等学校电子工程重点实验室基金项目(DZZD20100023)

摘　　要：针对一类非线性离散时间动态系统,提出了基于改进泛模型的非线性控制方法并对该控制律作用下系统的BIBO稳定性及收敛性进行了分析。该方法在改进泛模型的基础之上,根据二次型性能指标设计最优控制律,其中,时变特征参量建立AR模型进行预报,控制律中的未知参数采用粒子群优化(PSO)算法进行优化。经过优化后的控制律作用于该非线性对象,可以收到良好的控制效果。该方法的优势在于简单而且易于实现。仿真结果表明了算法的有效性。A nonlinear control method is proposed based on improved universal model for a class of nonlinear discrete time dynamic systems, and the BIBO stability and convergence of the controlled system are analyzed. On the basis of the improved universal model, the optimal control law is designed according to quadratic type performance target, in which the time-varying characteristic parameter is predicted by establishing the AR model. The unknown parameters in the control law are optimized by particle swarm optimization （PSO）. The better control effect can be obtained by using the control law optimized. This method has the advantage of simplisity and is easy to implement. Simulation results show the effectiveness of the method.

关 键 词：改进泛模型 粒子群优化 特征参量 收敛性 

分 类 号：TP27[自动化与计算机技术—检测技术与自动化装置]