基于径向基神经网络的非线性系统自适应控制

Self-adaptive control for uncertain systems based-on RBF neural networks

针对一类非线性系统,利用神经网络可逼近任意非线性函数的能力,及滤波误差理论,提出了一种基于径向基神经网络的自适应控制器设计方案.根据Lyapunov稳定原理,给出了系统稳定的充分条件.该方案保证跟踪误差收敛,说明了该控制器的有效性,仿真结果表明了其实用性.

As we all know,the neural networks can approach any nonlinear function.So,in this paper,an adaptive neural networks control scheme is proposed for a class of nonlinear systems.A sufficient condition for the stability of the system is given,which has been proven by Lyapunov theory.And this scheme guarantees the convergence to the tracking error.It indicates that the controller is effectual.The result of simulation indicates its practicability.