Observer-Based Adaptive Impedance Control for Robotic Systems With Predefined Task Space

Abstract

This paper presents an observer-based adaptive impedance control (OBAIC) scheme to coordinate the robotic systems with predefined task space (output constraint), where the robot dynamic model is estimated by neural network (NN). The reference trajectory is shaped by the impedance control model and constraint region to ensure the safety and compliant performance of the robotic systems. Under no knowledge of the system model, an observer is proposed to obtain the velocities of the robotic manipulator. According to the barrier Lyapunov function (BLF) and NN technology, the OBAIC scheme is proposed to tracking the shaped trajectory and achieve the prescribed constraint and steady-state performance. Finally, the simulation tests of the 2-degree of freedom (DOF) robotic manipulator with output constraints are conducted to verify the proposed OBAIC strategy, and the results show the feasibility of the OBAIC scheme.