Stable adaptive systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
IEEE Transactions on Neural Networks
Nonlinear adaptive control of interconnected systems using neural networks
IEEE Transactions on Neural Networks
Stochastic choice of basis functions in adaptive function approximation and the functional-link net
IEEE Transactions on Neural Networks
Hi-index | 0.00 |
A novel decentralized controller using the dynamic surface control (DSC) is proposed for a class of uncertain large scale interconnected nonlinear systems in strict-feedback form while relaxing the "explosion of complexity" problem which is observed in the typical backstepping approach. The matching condition is not assumed when dealing with the interconnection terms. Neural networks (NNs) are utilized to approximate the uncertainties in both subsystem and interconnected terms. By using novel NN weight update laws, it is demonstrated using Lyapunov stability that the closed-loop signals are asymptotically stable in the presence of NN approximation errors in contrast with the uniform ultimate boundedness result that is common in the literature with NN-based DSC and backstepping schemes. Simulation results of the controller performance for a nonlinear decentralized system justify theoretical conclusions.