基于神经元网和带死区的最小二乘算法的非线性离散时间系统的自适应控制(英文)

Adaptive Control of Nonlinear DiscreteTime Systems UsingNeural Networks and Least Squares Algorithm with DeadZone

针对非线性离散时间系统，提出了一种用带死区的最小二乘算法去调节神经网参数的算法，同其他算法相比，这种算法具有非常高的收敛速度．对于这种自适应控制算法，证明了闭环系统的所有信号是有界的，跟踪误差收敛到以零为原点的球中．

Multilayer neural networks are used in a nonlinear discretetime adaptive control problem.The weights of the neural networks are updated by using least squares (LS) algorithm with deadzone.LS algorithm has much superior rate of convergence compared with gradient algorithm and modification algorithm.For the adaptive control algorithm,we prove that:1) all signals in the closedloop systems are bounded;and 2) the tracking error converges to a bounded ball.