欠驱动机械臂优化控制的粒子群算法  

Optimal Control of an Underactuated Manipulator System Using the Particle Swarm Optimization

作　　者：厉虹[1] 张冰[1] 刘小河[1] 

机构地区：[1]北京机械工业学院计算机与自动化系,北京100085

出　　处：《计算机工程与应用》2006年第26期180-182,共3页Computer Engineering and Applications

基　　金：国家自然科学基金资助项目(编号:10372014)

摘　　要：粒子群优化算法是基于群体的演化算法,本质上是一种随机搜索算法,能以较大概率收敛到全局最优。论文针对欠驱动Acrobot机械臂系统,运用部分反馈线性化的状态反馈控制设计摇起控制器,利用粒子群算法(PSO)进行在线优化获得摇起控制器参数最优值,为平滑而稳定地切换到平衡控制器提供了保障。仿真结果显示,该方法能大大缩短系统摇起到进入平衡状态的时间,并具有容易实现以及计算量小的优点。The particle swarm optimization（PSO）,which is an optimization technique based on evolutionary computation, essentially is a random searching algorithm.It can converge to the global minima with great probability.The underactuated system is a second-order nonholonomic system with less actuators than freedoms.Using the state feedback control of partial feedback linearization,a swing-up controller is designed.Then using the utilized particle swarm optimization,an optimal value of the system parameters is obtained.Therefore the controller is transformed smoothly.The simulation results are presented showing that the proposed method can shorten the period of time and be implemented easily,simultaneously require less computational resource.

关 键 词：欠驱动系统 ACROBOT 粒子群算法 优化 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]