Practical adaptive neural control of nonlinear systems with unknown time delays.
Practical adaptive neural control is presented for a class of nonlinear systems with unknown time delays in strict-feedback form. Using appropriate Lyapunov-Krasovskii functionals, the unknown time delays are compensated for. Controller singularity problems are solved by practical neural network control. A novel differentiable control function is provided such that the practical design can be carried out in the decoupled backstepping design. It is proved that the proposed design method is able to guarantee semi-global uniform ultimate boundedness of all the signals in the closed-loop system, and the tracking error is proven to converge to a small neighborhood of the origin.
Hong
Fan
F
Ge
Shuzhi Sam
SS
Lee
Tong Heng
TH
D000465:Algorithms; D003198:Computer Simulation; D005246:Feedback; D008954:Models, Biological; D015233:Models, Statistical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors