Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks

• Published in: IEEE transactions on neural networks Vol. 16; no. 2; pp. 414 - 422
• Main Authors: PARK, Jang-Hyun, HUH, Sung-Hoe, KIM, Seong-Hwan, SEO, Sam-Jun, PARK, Gwi-Tae
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01-03-2005; Institute of Electrical and Electronics Engineers
• Subjects: Adaptation, Physiological; Adaptive control; Adaptive systems; Applied sciences; Artificial intelligence; Computer science; control theory; systems; Connectionism. Neural networks; Control systems; Error correction; Exact sciences and technology; Flexible structures; Neural network (NN); Neural networks; Neural Networks (Computer); Neurons; nonaffine nonlinear system; Nonlinear control systems; Nonlinear Dynamics; Nonlinear systems; Programmable control; robust adaptive control; Closed loop; State feedback; Asymptotic stability; Closed systems; Non linear control; Lyapunov method; Tracking error; Neural network; Adaptive control; Lyapunov function
• ISSN: 1045-9227; 1941-0093
• DOI: 10.1109/TNN.2004.841786

A direct adaptive state-feedback controller is proposed for highly nonlinear systems. We consider uncertain or ill-defined nonaffine nonlinear systems and employ a neural network (NN) with flexible structure, i.e., an online variation of the number of neurons. The NN approximates and adaptively cancels an unknown plant nonlinearity. A control law and adaptive laws for the weights in the hidden layer and output layer of the NN are established so that the whole closed-loop system is stable in the sense of Lyapunov. Moreover, the tracking error is guaranteed to be uniformly asymptotically stable (UAS) rather than uniformly ultimately bounded (UUB) with the aid of an additional robustifying control term. The proposed control algorithm is relatively simple and requires no restrictive conditions on the design constants for the stability. The efficiency of the proposed scheme is shown through the simulation of a simple nonaffine nonlinear system.