Recursive PID-NT Estimation-Based Second-Order SMC Strategy for Knee Exoskeleton Robots: A Focus on Uncertainty Mitigation

This study introduces a modified second-order super-twisting sliding mode control algorithm designed to enhance the precision and robustness of knee exoskeleton robots by incorporating advanced uncertainty mitigation techniques. The key contribution of this research is the development of an efficien...

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Vydáno v:Electronics (Basel) Ročník 14; číslo 7; s. 1455
Hlavní autoři: Behnamgol, Vahid, Asadi, Mohamad, Aphale, Sumeet S., Sohani, Behnaz
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 03.04.2025
Témata:
Algorithms
Analysis
Approximation
Artificial intelligence
Closed loop systems
Control algorithms
Control methods
Control systems
Control theory
Controllers
Design
Effectiveness
Exoskeletons
Human performance
Injuries
Knee
Methods
Parameter identification
Parameter uncertainty
Rehabilitation
Robotics
Robotics industry
Robots
Robustness
Sliding mode control
Stability analysis
Systems stability
Upper bounds
ISSN:2079-9292, 2079-9292
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Shrnutí:This study introduces a modified second-order super-twisting sliding mode control algorithm designed to enhance the precision and robustness of knee exoskeleton robots by incorporating advanced uncertainty mitigation techniques. The key contribution of this research is the development of an efficient estimation mechanism capable of accurately identifying model parameter uncertainties and patients’ unwanted action torques disturbance within a finite time horizon, thereby improving overall system performance. The proposed control framework ensures smooth and precise control signal dynamics while effectively suppressing chattering effects, a common drawback in conventional sliding mode control methodologies. The theoretical foundation of the algorithm is rigorously established through the formulation of a PID non-singular terminal sliding variable, which ensures finite time stability in the sliding phase and a comprehensive Lyapunov-based stability analysis assuming that the upper bound of the uncertainty and its derivative are known in the reaching phase, which collectively guarantee the system’s robustness and reliability. Through simulations, the efficacy of the proposed control system is evaluated in its ability to track diverse desired knee angles, demonstrate robustness against disturbances, such as those caused by the patient’s foot reaction, and handle a 20% uncertainty in the model parameters. Additionally, the system’s effectiveness is assessed by three individuals with varying parameters. Notably, the controller gains remain consistent across all scenarios. This research constitutes a significant advancement in the domain of knee exoskeleton control, offering a more reliable and precise methodology for addressing model uncertainties.
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ISSN:2079-9292
2079-9292
DOI:10.3390/electronics14071455