Observer-Based Adaptive Fuzzy Event-Triggered Control for Mechatronic Systems With Inaccurate Signal Transmission and Motion Constraints

This article presents an adaptive output feedback controller for a class of Euler-Lagrange (EL) mechatronic systems subject to time-delay, input hysteresis, and motion constraints; simultaneously, the event-triggered mechanism is introduced to decrease communication costs. During controller design, the proposed method not only relaxes additional requirements on the model structures by other methods (e.g., parameters linearly appearing in dynamics or strict triangular/cascade normal forms), but also estimates uncertain dynamics and approximation errors online, instead of utilizing large-gain or discontinuous terms to suppress their impacts. Regarding the inaccurate signal transmission of EL systems, this article presents a modified fuzzy observer with an elaborately designed auxiliary term, to recover unmeasurable variables and simultaneously deal with state time-delay. Meanwhile, the Prandtl-Ishlinskii model is employed to imitate input hysteresis, whose unknown parameters are also estimated online to improve tracking accuracy. By Lyapunov-based stability analysis, it is proven that the error signals are always limited within preset constraints and asymptotically converge to zero. As far as we know, for EL systems, this article proposes the first controller to address such comprehensive effects of unreliable state feedback, limited workspace, and input/output nonlinearities in practice, and also eliminate tracking errors with a theoretical guarantee. More importantly, the utilized event-triggered mechanism further improves the practicability of this article. Finally, based on a pneumatic artificial muscle (PAM)-actuated robot manipulator, the performance of the proposed controller is validated via hardware experiments.

Automated summary

This article presents an adaptive output feedback controller for Euler-Lagrange mechatronic systems subject to time-delay, input hysteresis, and motion constraints. It introduces an event-triggered mechanism to reduce communication costs and utilizes a modified fuzzy observer and the Prandtl-Ishlinskii model to address inaccurate signal transmission and input hysteresis. The stability of the controller is analyzed using Lyapunov-based methods. Hardware experiments are conducted to validate the controller's performance.