遗传模拟退火算法在传感器/作动器位置优化问题中的应用  

Application of Genetic and Simulated Annealing Algorithms in Placement Optimization of Sensor/ Actuator

作　　者：缑新科[1] 崔明月[1] 

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730050

出　　处：《机械与电子》2008年第11期39-41,共3页Machinery & Electronics

基　　金：甘肃省自然科学基金资助项目(3ZS051-A25-033)

摘　　要：基于遗传模拟退火算法,针对简支梁振动主动控制的传感器/作动器位置优化问题,提出了一种以结构总储能最小为优化目标的数学模型,并编制了遗传模拟退火算法软件对此模型进行了优化计算。结果表明,较之穷举法,用遗传模拟退火算法解决传感器/作动器的位置优化问题更高效,同时也是全局收敛的。Based on genetic and simulated annealing algorithms, a mathematical model of minimizing total energy for sensor/actuator placement of simple beam active control was brought forward. A genetic and simulated annealing algorithms software was eveloped for optimizing computation. According to computing results, comparing with exhaustion method, genetic and simulated annealing algorithms has high efficiency and global convergence for sensor/actuator placement question.

关 键 词：遗传模拟退火算法 主动控制 传感器/作动器 位置优化 

分 类 号：TB53[理学—物理]