Adaptive Force-Tracking Impedance Control Based on Fuzzy Logic Under Unknow and Varying Environment

Traditional position control can no longer meet the needs of reality, and it is imperative to enhance the pliability of the robot's interaction with its surroundings. For this reason, this paper combines impedance control with hybrid force/position control and proposes a fractional-order PI adaptive fuzzy hybrid impedance controller (PI-AFHIC). An adaptive fuzzy sliding mode position controller is devised within the position control subsystem, predicated on the dynamic model of the robot's joint space. The uncertainty of the robot dynamics modeling is compensated by a fuzzy neural network, and the stability of the position controller is substantiated utilizing Lyapunov's theorem. In the force control subspace, the traditional impedance model is improved by introducing fractional-order PI controller, which leads to a notable enhancement in both the transient and steady-state response characteristics of the system. Ultimately, the simulation assesses the force-tracking capabilities of PI-AFHIC in comparison to the fractional-order PI hybrid impedance control (PI-HIC) and the traditional hybrid impedance control (AFHIC) within an unfamiliar environment, confirming the efficacy of the proposed control algorithm.