Abstract
In this article, an adaptive fault-tolerant tracking control algorithm is developed for the multi-input-multi-output (MIMO) pure-feedback nonlinear systems with full state constraints. The state constraints are time-varying, hence greatly improve the applicability of the result but significantly increase the difficulties and complexities of control system design. To overcome the feasibility conditions in barrier Lyapunov function for handling time-varying constraints, a novel nonlinear mapping method for MIMO nonlinear systems is developed. Adaptive techniques and Neural Networks (NNs) are applied to estimate unknown uncertainties and disturbances, which the tracking control accuracy is improved. It is proved that the designed control algorithm can not only achieve the control objectives but also guarantee the boundedness of all signals. Finally, the effectiveness of the developed control algorithm is demonstrated via a simulation example.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
