基于改进粒子群算法的主汽温控制系统PID参数优化  

PID Controller Parameters Optimization for Main Steam Temperature Control System Based on Improved Particle Swarm Optimization

作　　者：焦嵩鸣[1] 谭雨林[1] 桑士杰[1] 

机构地区：[1]华北电力大学控制与计算机工程学院,河北保定071003

出　　处：《电力科学与工程》2012年第12期9-13,共5页Electric Power Science and Engineering

基　　金：中央高校基本科研业务费专项基金资助项目(12MS118)

摘　　要：介绍了一种基于改进的粒子群优化(PSO)算法的PID控制器参数优化方法。通过将PSO基本算法中的惯性权重进行线性递减,很好地协调了PSO的全局与局部寻优能力。将改进的粒子群PID控制器参数优化方法应用于多扰动、大惯性的电厂主汽温控制系统,仿真结果表明,该方法在保证控制系统稳定性的基础上极大地提高控制系统的精度和快速性。The improved particle swarm optimization （PSO） is used to optimize the PID controller parameters in this paper. By using of the linear degression of inertia weight approach to modified the basic particle swarm optimization, the improved particle swarm optimization coordinates the global and local searching capability. The modified algorithm is applied to main steam temperature control system in power plant whose controlled objects are multidisturbance and large inertia. Simulation results show that the improved PSO can enhance the control accuracy and rapidity as well as ensure the control stability.

关 键 词：粒子群算法 主汽温系统 PID 优化 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]