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Event‐based model‐free sliding mode control for an inspection robot
Author(s) -
Chen Lin,
Duan Haibin,
Dian Songyi,
Hoang Son
Publication year - 2020
Publication title -
advanced control for applications: engineering and industrial systems
Language(s) - English
Resource type - Journals
ISSN - 2578-0727
DOI - 10.1002/adc2.33
Subject(s) - control theory (sociology) , sliding mode control , observer (physics) , controller (irrigation) , computer science , nonlinear system , state observer , linearization , lyapunov stability , lyapunov function , mode (computer interface) , control engineering , engineering , control (management) , artificial intelligence , physics , quantum mechanics , agronomy , biology , operating system
This article investigates the balance adjustment control of a power line inspection robot under the circumstance that (a) only the I/O information of the system is available and (b) the information is sampled aperiodically. To address the problem, an event‐based model‐free sliding mode control algorithm is proposed. The full‐form dynamic linearization (FFDL) technique is first employed to approximate the original nonlinear system via an unknown pseudo‐partial derivative (PPD) Jacobean matrix. Then, an observer is designed to obtain the update law of the PPD matrix using the aperiodically sampled I/O incremental data. Meanwhile, an event‐triggered mechanism is presented to determine when the data can be delivered to the observer. A model‐free sliding mode control framework combined with the established FFDL model, observer, and the event‐triggered mechanism is designed. The stability of the closed‐loop system and the scale of the controller's parameters are confirmed using the Lyapunov theorem. Simulation results demonstrate the effectiveness of the proposed control scheme.