摘要
提出了一种适用于机械臂的基于神经网络的分散自适应轨迹跟踪控制方法。将机械臂的轨迹跟踪控制系统考虑为由多个非线性关联组成的不确定性复杂系统,采用分散控制方法进行控制器设计。在对每一子系统设计控制器时,采用直接反馈线性化,利用控制器构建伪线性系统,并引入神经网络自适应环节消除干扰、关联及逼近误差,从而使所提出的控制方法能够保证系统状态有较高的跟踪精度,且算法简单,易于实现。仿真表明,该算法能保证较高的跟踪效果。
A decentralized adaptive control for trajectory tracking of robot manipulators is presented, The system is considered as a set of nonlinear subsystems with nonlinear uncertainties and interconnections. The tracking problem is tackled with decentralized controller. For each subsystem, an output feedback linearization is employed, and neural networks are used to compensate the system errors, the disturbances and the interconnections, which can simplify the design of the controller, improve the dynamic performance and make the system robust, Simulation results show that the system has a good tracking performance.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2006年第5期1267-1270,共4页
Journal of System Simulation
关键词
分散控制
机械臂
神经网络
自适应控制
decentralized control
robot manipulators
neural networks
adaptive control
