Trajectory optimization of a reentry vehicle based on artificial emotion memory optimization

• 作者: FU Shengnan WANG Liang XIA Qunli
• 来源期刊: 系统工程与电子技术（英文版）
• 年，卷（期）: 2021,（3）
• 所属期刊栏目: CONTROL THEORY AND APPLICATION
• 页码范围: 668-680
• 页数: 13页
• 语种: 英文
• DOI: 10.23919/JSEE.2021.000057

摘要

The trajectory optimization of an unpowered reentry vehicle via artificial emotion memory optimization(AEMO)is dis-cussed.Firstly,reentry dynamics are established based on mul-tiple constraints and parameterized control variables with finite dimensions are designed.If the constraint is not satisfied,a dis-tance measure and an adaptive penalty function are used to ad-dress this scenario.Secondly,AEMO is introduced to solve the trajectory optimization problem.Based on the theories of bio-logy and cognition,the trial solutions based on emotional memory are established.Three search strategies are designed for realizing the random search of trial solutions and for avoiding becoming trapped in a local minimum.The states of the trial solutions are determined according to the rules of memory en-hancement and forgetting.As the iterations proceed,the trial solutions with poor quality will gradually be forgotten.Therefore,the number of trial solutions is decreased,and the convergence of the algorithm is accelerated.Finally,a numerical simulation is conducted,and the results demonstrate that the path and ter-minal constraints are satisfied and the method can realize satis-factory performance.