基于SQP/GA混合优化算法的双容水箱非线性预测控制

为了计算控制序列，非线性模型预测控制可以转换为一个带约束的非线性优化过程．本文分析了三种约束处理方案，根据遗传算法的特点，将等式约束用于状态量计算，在搜索空间降维的同时消除遗传算法难以求解的等式约束．对双容水箱进行遗传算法和序列二次规划仿真试验和实际控制，结果表明遗传算法对控制量的优化效果优于序列二次规划．为克服遗传算法耗时较长、优化结果存在随机抖动的缺点，结合序列二次规划提出一种混合优化算法，仿真和实控结果表明其可行性和有效性．

Coupled-tank Nonlinear Predictive Control Based on GA/SQP Hybrid Optimization Algorithm

To calculate control sequence,nonlinear model predictive control(NMPC) can be tranformed into an optimization process of nonlinear programming problem with constraints.In this article,three strategies to consider constraints are analyzed.According to the features of genetic algorithm(GA),state vector are calculated by state(equation,) in which the dimension of search space is reduced as well as the equation constraints which are difficult to deal with by genetic algorithm are eliminated.The results of both simulation and practice to a coupled-tank apparatus illustrate that NMPC based on GA outperforms which based on sequential quadratic programming(SQP).To avoid much time consumptions of GA and randomicity of optimization results,a hybrid method is proposed by incorporating SQP.The results of both simulation and practice verify the feasibility and efficiency of proposed method.