Event-Triggered Disturbance Rejection Control for Brain-Actuated Mobile Robot: An SSA-Optimized Sliding Mode Approach

This article proposes an event-triggered disturbance rejection control scheme for a brain-actuated two-legged wheeled mobile robot (WMR) by using sliding mode approach. An eight-channel brain-computer interface system is developed to evoke five modes of the steady-state visual evoked potential, whic...

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Veröffentlicht in:IEEE/ASME transactions on mechatronics Jg. 30; H. 1; S. 482 - 493
Hauptverfasser: Zhu, Ziming, Song, Jun, He, Shuping, Liu, Jason J. R., Lam, Hak-Keung
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.02.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Brain–computer interface (BCI)
Control systems design
Controllers
disturbance observer
Disturbance observers
Electroencephalography
Energy consumption
event-triggering protocol
Generators
Human-computer interface
Man-in-the-loop simulation
Mechatronics
Mobile robots
Multiple objective analysis
Rejection
Robot control
Robots
Robust control
Robustness
Search algorithms
Simulation
Sliding mode control
sliding mode control (SMC)
sparrow search algorithm (SSA)
Tracking errors
Visual observation
Visualization
Wheels
ISSN:1083-4435, 1941-014X
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Zusammenfassung:This article proposes an event-triggered disturbance rejection control scheme for a brain-actuated two-legged wheeled mobile robot (WMR) by using sliding mode approach. An eight-channel brain-computer interface system is developed to evoke five modes of the steady-state visual evoked potential, which are applied to control the WMR. In order to improve the speed tracking accuracy of the robot, a disturbance observer is integrated into the sliding mode controller design to actively compensate for unknown disturbances. Meanwhile, the energy usage of controlling robot is saved via introducing an event-triggering mechanism, which is designed via reachability of sliding mode. It is further shown that the tracking error can be driven into a neighborhood of the origin by the proposed sliding mode controller and event generator. The tradeoff between the convergence of sliding mode dynamics and the scheduling performance of the event generator is formulated into a multiobjective optimization problem, whose solutions are searched readily via invoking a sparrow search algorithm (SSA). Finally, the effectiveness and robustness of the proposed SSA-optimized sliding mode controller are evaluated in both human-in-the-loop simulation and experiment results. Specifically, the results demonstrate that by means of the proposed event-triggered sliding mode controller, the five subjects can complete the given tasks successfully with maintaining the disturbance rejection performance and saving 45.90% <inline-formula><tex-math notation="LaTeX">\pm</tex-math></inline-formula> 2.02% usage of computation resources for the brain-actuated WMR.
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ISSN:1083-4435
1941-014X
DOI:10.1109/TMECH.2024.3402116