基于改进引力搜索算法的励磁控制PID参数优化  

PID parameter optimization of excitation control systems by using improved gravitational search algorithm

作　　者：李超顺[1] 周建中[1] 肖剑[1] 

机构地区：[1]华中科技大学水电与数字化工程学院,湖北武汉430074

出　　处：《华中科技大学学报（自然科学版）》2012年第10期119-122,共4页Journal of Huazhong University of Science and Technology(Natural Science Edition)

基　　金：国家自然科学基金资助项目(51109088);高等学校博士学科点专项科研基金新教师基金资助项目(20110142120020);中央高校基本科研业务费专项资金资助项目(2011QN066);华中科技大学水力机械过渡过程教育部重点实验室开放研究基金资助项目(SLJX2011006)

摘　　要：在引力搜索算法(GSA)基础上,结合PSO算法中粒子的运动特点,提出了改进引力搜索算法(IGSA),并将其应用到励磁控制系统PID参数优化.IGSA嵌入了引力搜索和粒子群搜索,使其在保留引力搜索特点的前提下增加了信息共享及记忆能力,进一步提高了搜索能力.定义了同时考虑ITAE指标和超调量指标的加权目标函数,提出了基于混沌引力搜索的参数优化策略.将IGSA与传统群体优化算法进行了充分对比试验,验证了提出的励磁控制系统PID参数优化方法的有效性.Based on the newly developed gravitational search algorithm （GSA） and chaotic optimiza- tion, the chaotic gravitational search algorithm （IGSA） was proposed, and applied in parameter opti- mization of proportional integration differential （PID） controller for power system. The IGSA was composed of coarse gravitational search and fine chaotic local search, while chaotic search seeks the optimal solution further, based on the current best solution found by the coarse gravitational search. In order to improve the performance of PID parameter optimization, a GSA based optimization strate- gy was proposed, in which a new objective function considering ITAE （integral of time absolute error） and overshoot of system response was defined, and the IGSA based parameter optimization strategy was developed. Comparative experiments of IGSA and traditional random search algorithms were con- ducted. The results show that IGSA has better search ability and higher stability, and can improve the control quality of excitation control system effectively.

关 键 词：电压控制 优化 粒子群优化 改进引力搜索算法 PID参数 励磁控制系统 

分 类 号：TM74[电气工程—电力系统及自动化]