移动机器人路径跟踪的自适应控制

提出一种结构简单的自适应控制器，控制器是由模糊神经网络和PD控制器并行控制移动机器人路径跟踪。在初始阶段，PD控制器控制路径跟踪并提供控制经验给模糊神经网络学习。在学习信号触发器的管理下，可以在线学习自适应调整模糊神经网络的参数。模糊神经网络控制器既推理产生控制规律，也辩识移动机器人动力学模型，通过BP学习算法实时在线调整自身参数达到路径跟踪自适应控制目的。

Adaptive Control Applications on Path-Tracking Control of Mobile Robot

A simple adaptive controller consists of fuzzy-neural network and PD controller,which makes parallel controls on path tracking of the mobile robot.In the initialization,the PD controller controls the path-tracking and supplies experience of control for learning of fuzzy neural work.The fuzzy neural network controller can on-line learn and adaptive tune parameters of network controlled by management of learning signal trigger.The fuzzy neural network controller can provide the control law and identify the dynamics of mobile robot.The BP learning algorithm is used for real-time on-line adaptive tune parameters of network to adaptive control path tracking of the mobile robot.