摘要
设计一种移动机器人轨迹跟踪控制器并利用Lyapunov稳定性定理证明了该控制器的全局稳定性。针对人为设定该类控制器参数工作量较大,根据移动机器人跟踪控制过程的非线性本质,提出了一种采用模糊非线性参数的跟踪控制方法。在无先验知识的前提下,利用粒子群算法自动提取控制器参数的模糊规则基。设计一种动态群体的粒子群方法,使得种群的多样性得到保证,减少局部收敛的可能,同时又不会对已有种群的模式造成巨大破坏。对比实验验证了该方法的有效性。
A novel controller with fuzzy non-linear parameter was proposed. The controller was proved to be global stable with Lyapunov theory. It aims to solve the problems of time consuming and hard to satisfy the control demands when seeking the parameters. A particle swarm optimization （PSO） algorithm was used to generate the non-linear fuzzy rule base automatically without prior knowledge. A dynamic PSO algorithm was designed instead of traditional PSO. In order to improve the popularity of the particle swam, decrease the possibility of local constrain and not to destroy the pattern of the particle swarm, the algorithm decided the number of degenerated particles based on a designated popularity function. Comparison with existing methods shows the effectiveness of the proposed method.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2007年第9期1971-1975,共5页
Journal of System Simulation
关键词
跟踪控制
粒子群
模糊参数自适应
局部收敛
tracking control
particle swarm optimization algorithm
fuzzy parameter adaptive
local constrain
