Robust adaptive finite-time tracking control of uncertain mechanical systems with input saturation and deadzone

• Published in: Transactions of the Institute of Measurement and Control Vol. 41; no. 2; pp. 560 - 572
• Main Authors: Wang, Baofang, Li, Sheng, Chen, Qingwei
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01-01-2019; Sage Publications Ltd
• Subjects: Adaptive control; Continuity (mathematics); Mechanical systems; Neural networks; Radial basis function; Recursive methods; Robust control; Saturation; Tracking control; Tracking errors; Uncertainty; Upper bounds; Finite-time control; adaptive control; input saturation and deadzone; neural networks; mechanical systems
• ISSN: 0142-3312; 1477-0369
• DOI: 10.1177/0142331218767490

This paper addresses the problem of robust adaptive finite-time tracking control for a class of mechanical systems in the presence of model uncertainties, unknown external disturbances, and input nonlinearities containing saturation and deadzone. Without imposing any conditions on the model uncertainties, radial basis function neural networks are used to approximate unknown nonlinear continuous functions, and an adaptive tracking control scheme is proposed by exploiting the recursive design method. It is shown that the input saturation and deadzone model can be expressed as a simple linear system with a time-varying gain and bounded disturbance. An adaptive compensation term for the upper bound of the lumped disturbance is introduced. The semi-global finite-time uniform ultimate boundedness of the corresponding closed-loop tracking error system is proved with the help of the finite-time Lyapunov stability theory. Finally, an example is given to demonstrate the effectiveness of the proposed method.