Soft-event-triggered dynamic damping adaptive fuzzy constraints EPH control for robot manipulator

This article proposes a soft-event-triggered-based dynamic damping adaptive fuzzy output-constraints error-port Hamiltonian (EPH) control for robot manipulator with model uncertainty. In the controller design, a generalized desired Hamiltonian function, a dynamic damping matrix, and a soft-event-triggered mechanism are primarily developed. Firstly, a generalized desired Hamiltonian function is proposed, which not only reflects the physical properties of the system but also serves as a generalized Lyapunov function for stability analysis under both constrained and unconstrained conditions. The generalized desired Hamiltonian function provides a new framework for output constraint control and analysis of robot manipulator. Secondly, a dynamic damping matrix based on the equivalent damping ratio of a closed-loop system is designed to systematically optimize the tracking performance of the system by adjusting the equivalent damping ratio through dynamic damping. Thirdly, to reduce communication burden and prevent sampling failures caused by excessively large triggered thresholds, a soft-event-triggered controller is designed. In addition, an adaptive fuzzy system and an adaptive disturbance estimation are integrated to compensate for model uncertainty, nominal model inaccuracies and external disturbances. Finally, the effectiveness of the proposed controller is verified by comparative experiments on a robot manipulator platform.