Title :
Practical adaptive neural control of nonlinear systems with unknown time delays
Author :
Hong, Fan ; Ge, Shuzhi Sam ; Lee, Tong Heng
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Abstract :
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.
Keywords :
Lyapunov methods; adaptive control; closed loop systems; control system synthesis; delay systems; delays; differential equations; feedback; neurocontrollers; nonlinear control systems; Lyapunov-Krasovskii functionals; closed-loop system; controller singularity problems; decoupled backstepping design; differentiable control function; nonlinear time-delay system; practical adaptive neural control; semi-global uniform ultimate boundedness; strict-feedback form; tracking error; Adaptive control; Backstepping; Control systems; Delay effects; Lyapunov method; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Robust control; Decoupled backstepping; differentiable control; nonlinear time-delay system; practical neural networks; Algorithms; Computer Simulation; Feedback; Models, Biological; Models, Statistical; Neural Networks (Computer); Nonlinear Dynamics; Time Factors;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2005.846645
