Data-Based Iterative DHP Optimal Tracking Control with a Wastewater Treatment Application

被引:0
|
作者
Zhao, Huiling [1 ,2 ,3 ]
Wang, Ding [1 ,2 ,3 ]
Zhao, Mingming [1 ,2 ,3 ]
Ren, Jin [1 ,2 ,3 ]
机构
[1] Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
[2] Beijing Univ Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China
[3] Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Adaptive dynamic programming; Discount factor; Neural networks; Optimal tracking control; Wastewater treatment; TIME NONLINEAR-SYSTEMS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In order to implement the tracking control design towards concentrations of dissolved oxygen and nitrate nitrogen in wastewater treatment, a data-based iterative dual heuristic dynamic programming (DHP) method is established in this paper. First, the optimal tracking control problem is transformed into the optimal regulation problem. Then, the iterative adaptive dynamic programming strategy is introduced to solve the optimal control problem of the new system with the discount factor in the cost function, and the convergence analysis of the iterative algorithm is given. Furthermore, a new training approach is used to adjust the weights of the action and critic networks. Finally, the experimental simulation for a wastewater treatment plant is presented to verify the applicability of the proposed iterative DHP optimal tracking control method.
引用
收藏
页码:2161 / 2166
页数:6
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