Robust control design for a planar humanoid robot arm with high strength composite gear and experimental validation

Abstract Aiming at uncertainties and variable loads of the robot arm, a nonlinear control algorithm is proposed. The design of the proposed control is based on the engineering practice of the planar humanoid robot arm with high strength composite gear. The proposed control, consisting of a PD control portion and a robust control portion, retains the dynamic characteristics of the system and realizes based on error. Theoretical analysis shows that the proposed control can guarantee the uniform boundedness and uniform ultimate boundedness. Based on the humanoid robot arm, the experimental validation with the proposed control is carried out and compared with the PID control. Numerical simulations and experimental results show that the proposed control can effectively deal with load changes and parameter uncertainties, and the trajectory tracking accuracy of the robot is improved significantly with the proposed control.

[1]  Mohammad Ali Badamchizadeh,et al.  Adaptive backstepping control for an n-degree of freedom robotic manipulator based on combined state augmentation , 2017 .

[2]  Jing Na,et al.  Unknown System Dynamics Estimator for Motion Control of Nonlinear Robotic Systems , 2020, IEEE Transactions on Industrial Electronics.

[3]  Maolin Jin,et al.  A New Adaptive Sliding-Mode Control Scheme for Application to Robot Manipulators , 2016, IEEE Transactions on Industrial Electronics.

[4]  Renquan Lu,et al.  Adaptive Neural Network Tracking Control for Robotic Manipulators With Dead Zone , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[5]  Huiming Wang,et al.  Adaptive Command-Filtered Backstepping Control of Robot Arms With Compliant Actuators , 2018, IEEE Transactions on Control Systems Technology.

[6]  Zoran Miljkovic,et al.  Neural network Reinforcement Learning for visual control of robot manipulators , 2013, Expert Syst. Appl..

[7]  Siyuan Chen,et al.  Compatible Convex–Nonconvex Constrained QP-Based Dual Neural Networks for Motion Planning of Redundant Robot Manipulators , 2019, IEEE Transactions on Control Systems Technology.

[8]  Y. H. Chen,et al.  On the deterministic performance of uncertain dynamical systems , 1986 .

[9]  Zeng Wang,et al.  Continuous finite‐time control for uncertain robot manipulators with integral sliding mode , 2018, IET Control Theory & Applications.

[10]  Chun-Yi Su,et al.  Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision , 2017, IEEE Transactions on Industrial Informatics.

[11]  Paolo Mercorelli,et al.  Robust approximate fixed-time tracking control for uncertain robot manipulators , 2020 .

[12]  Miroslaw Galicki,et al.  Finite-time trajectory tracking control in a task space of robotic manipulators , 2016, Autom..

[13]  Wei He,et al.  Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[14]  J. F. Gómez-Aguilar,et al.  On the trajectory tracking control for an SCARA robot manipulator in a fractional model driven by induction motors with PSO tuning , 2018 .

[15]  Shuzhi Sam Ge,et al.  Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances , 2018, Int. J. Control.

[16]  Yunhui Liu,et al.  Adaptive visual servoing using common image features with unknown geometric parameters , 2013, Autom..

[17]  Yaonan Wang,et al.  Recurrent fuzzy wavelet neural networks based on robust adaptive sliding mode control for industrial robot manipulators , 2019, Neural Computing and Applications.

[18]  Jing Na,et al.  Adaptive Parameter Estimation and Control Design for Robot Manipulators With Finite-Time Convergence , 2018, IEEE Transactions on Industrial Electronics.

[19]  M. Corless,et al.  Continuous state feedback guaranteeing uniform ultimate boundedness for uncertain dynamic systems , 1981 .

[20]  Zhijun Yang,et al.  Dynamic Modeling, Simulation, and Experimental Verification of a Wafer Handling SCARA Robot With Decoupling Servo Control , 2019, IEEE Access.

[21]  Wen Yu,et al.  Neural PID Control of Robot Manipulators With Application to an Upper Limb Exoskeleton , 2013, IEEE Transactions on Cybernetics.

[22]  Minyue Fu,et al.  Finite-Time Control of a Linear Motor Positioner Using Adaptive Recursive Terminal Sliding Mode , 2020, IEEE Transactions on Industrial Electronics.

[23]  M. Corless Control of Uncertain Nonlinear Systems , 1993 .

[24]  Ju-Jang Lee,et al.  Trajectory Optimization With Particle Swarm Optimization for Manipulator Motion Planning , 2015, IEEE Transactions on Industrial Informatics.

[25]  Xiuxing Yin,et al.  Direct adaptive robust tracking control for 6 DOF industrial robot with enhanced accuracy. , 2017, ISA transactions.

[26]  G. Leitmann On One Approach to the Control of Uncertain Systems , 1993 .

[27]  Ke Shao,et al.  Recursive sliding mode control with adaptive disturbance observer for a linear motor positioner , 2021 .

[28]  Pham Duc Cuong,et al.  Adaptive trajectory tracking neural network control with robust compensator for robot manipulators , 2016 .

[29]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

[30]  Victor Manuel Hernández-Guzmán,et al.  Global PID Control of Robot Manipulators Equipped with PMSMs , 2018 .

[31]  P. M. Pradhan,et al.  Design of interval type-2 fuzzy precompensated PID controller applied to two-DOF robotic manipulator with variable payload. , 2019, ISA transactions.

[32]  Ian Howard,et al.  Neural adaptive tracking control for an uncertain robot manipulator with time-varying joint space constraints , 2018, Mechanical systems and signal processing.