摘要
实际控制问题中往往有多个控制目标需要兼顾,且多个目标通常情况下是冲突的。根据相邻控制步之间系统状态和控制输入的连续性,提出了一个基于NSGA-II的动态迭代多目标相容优化控制算法,并且这一算法有能力处理目标空间为非凸的控制问题和提高在线优化速度。考虑到IPMC驱动机器鱼在运行过程中能耗和速度两个关键且冲突的目标,建立IMPC驱动机器鱼的运动及能耗模型,将所提算法进行了应用。仿真结果表明了控制算法的有效性及其在慢复杂系统动态控制中的应用潜力。
It is popular that there exists multiple objectives in practical control system,and these objectives are usually competitive.Based on the tight relation between the system states of the neighboring sampling instants,a dynamic iterative multi-objective control algorithm based on NSGA-II was proposed,which could cope with nonconvex control problem as well as improve the computing speed.Considering the two key and conflicting objectives-speed and energy consumption,the robotic fish velocityand engery consumption model was established and the proposed algorithm was successfully applied.The simulation result shows the validity of the algorithm and its application potential for the multi-objective evolutionary algorithm to the slow complex varying system online control.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2011年第9期1925-1931,共7页
Journal of System Simulation
基金
上海市自然科学基金(11ZR1415600)
国家自然科学基金(60674070)
上海海洋大学博士启动基金(A-2400-09-0150)
上海市高校选拔培养优秀青年教师科研专项基金(ssc09011)
