摘要
粒子群优化算法(PSO)是基于群体的演化算法,本质上是一种随机搜索算法,并能以较大概率收敛到全局最优。本文针对欠驱动Acrobot机械臂系统,利用模糊控制原理设计平衡控制器,运用粒子群算法对模糊控制器的量化因子进行在线优化,获得平衡控制器参数的最优值,以实现降低系统超调量,减少系统振荡和平衡时间的目的。仿真实验结果验证了该方法的有效性。
Particle swam optimization （PSO） is an optimization technique based on evolutionary computation. The algorithm is a random searching algorithm in nature. It can converge to the global minima more probability. In this paper, proposes a fuzzy control strategy based on LQR to design balance controller and PSO is used for optimization of fuzzy controller. The optimum parameters of balance controller were obtained. The proposed method has a good performance to reduce overshoot, and is easy to shorten a time. The simulation results show that the proposed method is effective.
出处
《微计算机信息》
北大核心
2006年第03S期80-82,176,共4页
Control & Automation
基金
国家自然科学基金资助项目(No.10372014)
