基于H∞最优控制理论的粒子群优化算法在造纸定量控制中的应用

A H∞ Optimal Control Based PSO Method for Basis Weight Control in Paper Manufacturing Processes

关键词:  H∞最优控制  PID参数优化  粒子群算法  定量控制

Key Words:H∞optimal control theory  PID parameter tuning  particle swarm optimization  quantitative control

摘要:针对造纸定量控制系统具有非线性、时滞、多干扰等控制难点，本课题提出一种基于H∞最优控制理论的粒子群优化算法（PSO）优化PID参数。改进的PSO具有对控制系统过程模型的依赖性小、参数整定简单、鲁棒性和抗干扰性强的特点。与传统算法相比，基于H∞最优控制理论的PSO可以高效地找出符合设计要求的PID调节参数，不会陷入局部最优,且使系统性能指标达到最优或次最优。并且，仿真结果也验证了该算法的有效性和实用性。

Abstract:Basis weight control system in paper manufacturing process is a high order non-linear system with time delay and complicated interference. According to the characteristics of basis weight control system， this paper proposed a PSO-PID parameters tuning method based on H∞ optimal control theory. By introducing the liner decreasing inertia weight ω to optimize the PSO′s global and local searching ability. Simulation results verified that the proposed strategy could find a group of PID tuning parameters efficiently， thereby reducing the searching scope. Furthermore， compared to conventional PID parameter tuning methods， this strategy had a better convergence rate and computation precision; robustness and response speed of the system were improved as well．