【作者】 龚正锋； 李丽娟；

【Author】 GONG Zheng-Feng;College of Electrical Engineering and Control Science, Nanjing Tech University;

【机构】 南京工业大学电气工程与控制科学学院；

【摘要】 针对多变量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,提出了一种在得到性能评估结果后基于改进粒子群算法的控制器参数整定方法。该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作出改进,弥补了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。最后用Wood-Berry模型对其进行仿真验证,结果证明了该方法的有效性。更多还原

【Abstract】 Aiming at the problem that the controller parameters are no longer matched after the change of the set value, model mismatch and disturbance characteristics in the long-term operation of multivariable predictive control system, a controller parameter setting method based on improved particle swarm optimization(PSO) algorithm is proposed after the performance evaluation results are obtained. By analyzing the relationship between the optimal control law and the performance of the three systems, the method constructs the corresponding objective optimization function, improves the particle position and inertia factor in the iteration process of PSO, and makes up for the shortcoming that the algorithm is easy to fall into the local optimization and cannot optimize the integral parameter variables of the controller. Finally, the wood-berry model is used to simulate and verify the proposed method.更多还原