文献类型：会议论文

英文题名：A gradient-based stochastic search approach for optimal harvesting strategy in shrimp culture

作者：Xiang, Wu Qiaodan, Liu Bangjun, Lei Kanjian, Zhang

第一作者：Xiang, Wu

机构：[1] School of Mathematical Sciences, Guizhou Normal University, Guiyang, 550001, China; [2] School of Electrical Engineering, Southeast University, Nanjing, 210096, China; [3] School of Electrical and Information Engineering, Guizhou Institute of Technology, Guiyang, 550003, China; [4] School of Automation, Southeast University, Nanjing, 210096, China

第一机构：School of Mathematical Sciences, Guizhou Normal University, Guiyang, 550001, China

会议论文集：Proceedings of the 36th Chinese Control Conference, CCC 2017

会议日期：July 26, 2017 - July 28, 2017

会议地点：Dalian, China

语种：英文

外文关键词：Binary novel variable; Nonlinear impulsive system; Optimal control; Penalty function; Shrimp culture

年份：2017

摘要：This paper considers an optimal harvesting strategy problem arising in shrimp culture. The problem is formulated as an optimal control problem of nonlinear impulsive system. Since the impulsive switching constraints is very complex, the impulsive switching instants are unknown, and the objective function is not continuously differentiable, it is difficult to solve this problem by standard optimization methods. To overcome the difficulty, by introducing a novel binary variable for each sale price of shrimp, relaxing the binary variable, and imposing a penalty function on the relaxation term, the nonlinear impulsive system optimal control problem is transformed into a parameter optimization problem, which can be solved efficiently using any gradient-based optimization technique. Then, a gradient-based stochastic search approach is proposed for solving this problem. Finally, a harvesting strategy problem is presented to illustrate the efficiency of the approach proposed. ? 2017 Technical Committee on Control Theory, CAA.