基于CSA-SQP的预测控制器参数整定研究

Tuning parameters for model predictive controller based on CSA-SQP

针对预测控制器参数整定困难,提出了一种基于克隆选择和序列二次规划的预测控制器参数整定算法,建立了一个基于免疫原理和序列二次规划算法进行控制器参数整定的机制,并给出了参数整定问题中的抗原、抗体及亲和力的定义.在此基础上,针对系统的不确定性干扰,构造了基于事件触发的参数调整框架.最后,将算法应用于仿真实验,通过与设定值控制结果的对比,证明所提出的预测控制器参数整定方法是有效的.

A hybrid algorithm is presented to solve the difficulty of tuning the parameters of a model predictivecontroller(MPC).The algorithm is based on both the immune clonal selection algorithm and sequentialquadratic programming.Antibodies,antigens,and affinity are also defined.The framework of tuning parametersbased on events trigger is introduced in case of uncertain disturbance.Finally,the simulation is conducted usingthe presented algorithm.Comparison with the results of set point control indicates that the proposed method ismore efficient than other tuning methods and can be used to solve the problems with the predictive controllerparameter tuning.