基于性能诊断的预测控制器参数整定策略  

Predictive controller parameter tuning strategy based on performance diagnostics

作　　者：龚正锋 李丽娟 GONG Zheng-feng;LI Li-juan(College of Electrical Engineering and Control Science,Nanjing Tech University,Nanjing 211816,China)

机构地区：[1]南京工业大学电气工程与控制科学学院,江苏南京211816

出　　处：《计算机工程与设计》2022年第1期88-93,共6页Computer Engineering and Design

基　　金：国家自然科学基金面上基金项目(61873121);江苏省自然科学基金面上基金项目(BK20181376)。

摘　　要：针对多变量模型预测控制系统在长期运行中出现设定值变化、模型失配、扰动特性变化后控制器参数不再匹配的问题,提出一种在得到性能诊断结果后基于改进粒子群算法的控制器参数整定方法。通过分析最优控制律与三项系统性能的关系,构造出对应的目标优化函数,对粒子群算法迭代过程中粒子的位置和惯性因子做出改进,弥补该算法易于陷入局部最优以及无法优化控制器整型参数变量的不足。用Wood-Berry模型对其进行仿真仿真,结果验证了该方法的有效性。To address the problem that the controller parameters no longer match after the setpoint change,model mismatch and perturbation characteristics change in multivariate predictive control system in long-term operation,a controller parameter tuning method based on the improved particle swarm optimization(PSO)algorithm was proposed after the performance diagnosis results were obtained.By analyzing the relationship between the optimal control law and the performance of the three systems,the corresponding objective optimization function was constructed and the particle position and inertia factor were improved during the iteration of the swarm algorithm,which made up for the shortcomings that the algorithm is easy to fall into the local optimum and cannot optimize the controller integer parameter variables.The Wood-Berry model was used to validate the method,and the results verified the effectiveness of the method.

关 键 词：模型预测控制 性能诊断 粒子群算法 参数整定 动态仿真 

分 类 号：TP202[自动化与计算机技术—检测技术与自动化装置]