基于粒子群优化的非线性预测控制算法的特性分析与仿真研究

Analysis and Simulation Research on Nonlinear Predictive Control Based on Particle Swarm Optimization

介绍了基于粒子群优化的非线性预测控制算法(PSO-NPC)的基本原理和算法流程。通过仿真实验,分析了预测控制和粒子群算法参数对PSO-NPC控制性能的影响。针对基于预测误差的单目标优化的PSO-NPC常规算法不足之处,提出了粒子群多目标优化的非线性预测算法。仿真结果表明,提出的算法是正确有效的。

The basic principle and algorithm of nonlinear predictive control based on particle swarm optimization was introduced. The relationship between algorithm parameters and control performance was analyzed through simulations. Multi-objective optimization algorithm of PSO-NPC was proposed to improve control performance against shortage of conventional PSO-NPC based on single-objective optimization algorithm. The simulation results are given to demonstrate the correctness and effectiveness of the improved algorithm proposed herein.