Composite learning adaptive sliding mode control of fractional-order nonlinear systems with actuator faults |
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| Institution: | 1. Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, School of Mathematics, Southeast University, Nanjing 211189, China;2. School of Science, Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis, Guangxi University for Nationalities, Nanning 530006, China;3. NAAM Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia;4. Department of Mathematics, Quaid-I-Azam University, Islamabad, Pakistan;1. Department of Mathematics, Bharathiar University, Coimbatore 641046, India;2. Department of Mathematics, Sungkyunkwan University, Suwon 440-746, South Korea;3. Department of Mathematics, Anna University Regional Campus, Coimbatore 641046, India;4. Department of Mathematics, Yunnan University, Kunming, Yunnan 650091, China |
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| Abstract: | This paper considers the tracking control of fractional-order nonlinear systems (FONSs) in triangular form with actuator faults by means of sliding mode control (SMC) and composite learning SMC (CLSMC). In SMC design, a fractional sliding surface is introduced, and an adaptation law is designed to update the estimation of the mismatched parametric uncertainty in the actuator faults. The proposed SMC can guarantee the convergence of the tracking error where a persistent excitation (PE) condition should be satisfied. To overcome this limitation, by using the online recorded data and the instantaneous data, a prediction error of the parametric uncertainty is defined. Both the tracking error and the prediction error are utilized to generate a composite learning law. A composite learning law is designed by using the prediction error and the tracking error. The proposed CLSMC can guarantee not only the stability of system but also the accurate estimation of the parametric uncertainties in the actuator faults. In CLSMC, only an interval-excitation (IE) condition that is weaker than the PE one should be satisfied. Finally, simulation example is presented to show the control performance of the proposed methods. |
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