基于改进遗传算法的传感器优化配置  

Sensor Optimization Method Based on Improved Genetic Algorithm

作　　者：耿飞[1] 龙海辉[1] 赵健康[1] 丁鹏[1] 

机构地区：[1]上海交通大学电子信息与电气工程学院,上海200240

出　　处：《计算机仿真》2014年第5期56-59,97,共5页Computer Simulation

摘　　要：针对卫星太阳能帆板传感器的优化配置问题,为提高稳定性,提出了基于系统可观性的优化方法。通过可观性Gram阵的分块解析形式,避免了求解高阶Lyapunov矩阵方程。分析可观性的特殊性,提出了传感器的优化配置准则。为快速寻找到传感器的最优位置,针对传统遗传算法的局限性和不足,提出了自适应改进遗传算法。通过自适应调整交叉概率与变异概率和优秀个体保护,克服了传统遗传算法的早熟和发散现象的缺陷。实验结果表明,改进的遗传算法对于传感器的配置优化是有效的。In this paper, an optimization method based on system observability was proposed to the optimized configuration of satellite solar panels sensor. Block analytical form of the observability Gram array was used to avoid the solution of higher-order Lyapunov matrix equation. Sensor optimal allocation principle was proposed based on the analysis of particularity of observabihty. In order to quickly search for the optimal location and overcome the hmitation and insufficient of the traditional genetic algorithm, an improved adaptive genetic algorithm was presented. Adaptively adjusting crossover probability and mutation probability and excellent individual protection were addressed to overcome the traditional genetic algorithm premature and divergent phenomenon defects. Experimental results show that improved genetic algorithm is effective for sensor placement optimization.

关 键 词：太阳能帆板 可观性 传感器 遗传算法 自适应调整 

分 类 号：V411.8[航空宇航科学与技术—航空宇航推进理论与工程]