A neural network (NN) based adaptive control law is proposed for the tracking control of an n link robot manipulator with unknown dynamic nonlinearities. Basis function like nets are employed to approximate the plant ...A neural network (NN) based adaptive control law is proposed for the tracking control of an n link robot manipulator with unknown dynamic nonlinearities. Basis function like nets are employed to approximate the plant nonlinearities, and the bound on the NN reconstruction error is assumed to be unknown. The proposed NN based adaptive control approach integrates an NN approach with an adaptive implementation of discrete variable structure control with a simple estimation law to estimate the upper bound on the NN reconstruction error and an additional control input to be updated as a function of the estimate. Lyapunov stability theory is used to prove the uniform ultimate boundedness of the tracking error.展开更多
文摘A neural network (NN) based adaptive control law is proposed for the tracking control of an n link robot manipulator with unknown dynamic nonlinearities. Basis function like nets are employed to approximate the plant nonlinearities, and the bound on the NN reconstruction error is assumed to be unknown. The proposed NN based adaptive control approach integrates an NN approach with an adaptive implementation of discrete variable structure control with a simple estimation law to estimate the upper bound on the NN reconstruction error and an additional control input to be updated as a function of the estimate. Lyapunov stability theory is used to prove the uniform ultimate boundedness of the tracking error.
