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。该方法首先将非线性系统动态线性化为带误差修正的改进泛模型,对其中的时变特征参量建立AR模型进行预报,然后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,控制律中的未知参数即为AR模型中的参数以及泛模型中的误差修正系数,将其作为粒子向量,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 system control method is proposed based on improved universal model for a class of nonlinear discrete time dynamic systems.Firstly,a nonlinear system is linearized dynamically as the improved universal model with error amending,in which the time-varying characteristic parameter is predicted by establishing the AR model.Then,on the basis of the improved universal model,the optimal control law is designed according to quadratic type performance target.The unknown parameters in the control law are the parameters in AR model and the error amending coefficient in the improved universal model.Particle Swarm Optimization （PSO） can be adopted by taking them as a particle vector.It can obtain good control effect by using the control law optimized.The advantage of this method is simple and easy to implement.Several simulation results show the effectiveness of the method.
出处
《黑龙江大学自然科学学报》
CAS
北大核心
2010年第4期478-481,共4页
Journal of Natural Science of Heilongjiang University
基金
黑龙江省普通高等学校电子工程重点实验室基金资助项目(DZZD20100023)
关键词
非线性系统控制
改进泛模型
粒子群优化
特征参量
nonlinear system control
improved universial model
particle swarm optimization
characteristic parameter
