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 methodnot onlyrelaxes additional requirements on the model structures by other methods (e.g., parameters linearly appearing in dynamics or strict triangular/cascade normal forms),but alsoestimates uncertain dynamics and approximation errors online,instead ofutilizing “large-gain” or discontinuous terms to suppress their impacts. Regarding the inaccurate signal transmission of EL systems, this article presents amodifiedfuzzy 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 thefirstcontroller to address suchcomprehensiveeffects ofunreliablestate feedback, limited workspace, and input/output nonlinearities in practice, and also eliminate tracking errors with atheoretical 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.