Title :
Neural network based direct adaptive control for a class of affine nonlinear systems
Author :
Kar, Indrani ; Behera, Laxmidhar
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., Kanpur
Abstract :
This paper presents a neural network based direct adaptive control scheme for a class of affine nonlinear systems which are exactly input-output linearizable by nonlinear state feedback. When the system dynamics are completely unknown, the control input comprises two terms. One is an adaptive feedback linearization term and the other one is a sliding mode term. The neural networks weight update laws have been derived to make the closed loop system Lyapunov stable. It is shown that the proposed control action can also be applied to multi-input-multi-output systems with minor modifications. Simulation results are presented to validate the theoretical formulations
Keywords :
Lyapunov methods; adaptive control; closed loop systems; linearisation techniques; neurocontrollers; nonlinear control systems; state feedback; variable structure systems; Lyapunov stability; adaptive feedback linearization; affine nonlinear system; closed loop system; direct adaptive control; input-output linearizable; multiinput-multioutput systems; neural network; nonlinear state feedback; sliding mode term; system dynamics; Adaptive control; Closed loop systems; Control systems; Neural networks; Neurofeedback; Nonlinear dynamical systems; Nonlinear systems; Sliding mode control; State feedback; Two-term control;
Conference_Titel :
Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control, 2006 IEEE
Conference_Location :
Munich
Print_ISBN :
0-7803-9797-5
Electronic_ISBN :
0-7803-9797-5
DOI :
10.1109/CACSD-CCA-ISIC.2006.4776952
