Adaptive Neural Network Tracking Control of MIMO Nonlinear Systems With Unknown Dead Zones and Control Directions

• Published in: IEEE transactions on neural networks Vol. 20; no. 3; pp. 483 - 497
• Main Authors: Tianping Zhang, Ge, S.S.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2009; Institute of Electrical and Electronics Engineers
• Subjects: Adaptative systems; Adaptive control; Adaptive control systems; Adaptive systems; Applied sciences; Computer science; control theory; systems; Computer simulation; Control system analysis; Control systems; Control theory. Systems; dead zone; Disturbances; Dynamical systems; Exact sciences and technology; Linear systems; MIMO; neural network (NN) control; Neural networks; Nonlinear control systems; Nonlinear dynamics; Nonlinear systems; Nussbaum function; Programmable control; Sliding mode control; Tracking control; Sliding mode; sliding mode control; Non linear control; Adaptive control; Adaptive method; Time varying system; Uncertain system; Tracking error; neural network (NN) control; MIMO system; Triangular system; Variable structure control; Nussbaum function; Bounded error; Error bound; Tracking task; Dead zone; Neural network; Non linear system; Closed feedback; Characteristic function; Neurocontrollers; Upper bound; Distributed control; Approximation error; Optimal approximation; Lyapunov function
• ISSN: 1045-9227; 1941-0093
• DOI: 10.1109/TNN.2008.2010349

In this paper, adaptive neural network (NN) tracking control is investigated for a class of uncertain multiple-input-multiple-output (MIMO) nonlinear systems in triangular control structure with unknown nonsymmetric dead zones and control directions. The design is based on the principle of sliding mode control and the use of Nussbaum-type functions in solving the problem of the completely unknown control directions. It is shown that the dead-zone output can be represented as a simple linear system with a static time-varying gain and bounded disturbance by introducing characteristic function. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the optimal approximation error and the dead-zone disturbance, the closed-loop control system is proved to be semiglobally uniformly ultimately bounded, with tracking errors converging to zero under the condition that the slopes of unknown dead zones are equal. Simulation results demonstrate the effectiveness of the approach.