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Impedance Sliding Mode Control With Adaptive Fuzzy Compensation for Robot-Environment Interacting

Heyu Hu, Xiaoqi Wang, L Chen

2020IEEE Access24 citationsDOIOpen Access PDF

Abstract

In the field of robot research and application, improving the interaction performance between robots and the environment is the basic requirement of robot control. Hence, the position/force control problem needs to be solved. However, in practice, the model of the robot is usually inaccurate, and the working environment is usually uncertain. To solve the position/force control problem of the robot when the model and position are uncertain, a new method of impedance sliding mode control with adaptive fuzzy compensation (ISMCAF) is proposed. The dynamics of the robot are governed to follow a target impedance model and the interaction control objective is achieved. According to Lyapulov's theory, sliding mode control law and adaptive control law are designed to ensure the stability of the closed-loop system. The proposed method is further verified by simulation.

Topics & Concepts

Control theory (sociology)Impedance controlRobotComputer scienceCompensation (psychology)Sliding mode controlControl engineeringAdaptive controlRobot controlFuzzy control systemPosition (finance)Stability (learning theory)Fuzzy logicMobile robotControl (management)EngineeringArtificial intelligenceNonlinear systemPhysicsQuantum mechanicsMachine learningPsychoanalysisEconomicsPsychologyFinanceRobot Manipulation and LearningTeleoperation and Haptic SystemsSoft Robotics and Applications