基于粒子群优化的在线支持向量回归预测控制方法

Online Support Vector Regression Predictive Control Algorithm Based on Particle Swarm Optimization

针对非线性系统模型预测控制中,预测模型容易失配和目标函数难以求解的问题,提出了一种基于粒子群优化算法的非线性系统在线支持向量回归模型预测控制方法.该方法利用在线支持向量回归建立被控对象的非线性预测模型,并通过在线学习实现模型的在线自校正;同时采用粒子群优化算法求解目标函数,完成滚动优化.对非线性系统的仿真结果表明,该方法是有效的且具有良好的自适应性.

For the problems of model mismatch and difficulty in solving objective function in the predictive control of the nonlinear system model, an online support vector regression predictive control algorithm based on particle swarm optimiza- tion （PSO） is proposed. An nonlinear predictive model for the object is built based on the online support vector regression, and the object is identified and the identified model also can be self-adjusted through online learning. Meanwhile, the ob- jective function is solved by PSO, the rolling optimization is realized. The nonlinear system simulation results show the effectiveness and adaptability of the presented algorithm.