A Hybrid Adaptive Control Strategy for Industrial Robotic Joints

This paper presents a hybrid adaptive approximation-based control (HAAC) strategy for a class of uncertain robotic joints’ system. The proposed control structure consists of a robust sliding mode controller and an adaptive approximation-based controller. The robust sliding mode controller is designed by using the super-twisting algorithm, which is a particularly effective method to decrease the chattering caused by the traditional sliding mode control (SMC) and compensate the disturbances. Another improvement of the robust sliding mode controller is that the robust control parameters only subject to the upper bound of the derivative of the external disturbances, rather than choosing a relatively large value. Moreover, the designed adaptive approximation-based controller has the following two distinctive features: 1) the control parameters are designed to be adjusted in real time and 2) the prior knowledge of actual robotic model is not required to be known. These features contribute to compensating the uncertainties. The stability of the closed-loop system is proved by using the Lyapunov theory, and the simulation results demonstrate the effectiveness of the proposed control method. Finally, the proposed HAAC could apply in the experiments of industrial robotic joints’ system.

[1]  Hee-Jun Kang,et al.  A novel adaptive finite-time tracking control for robotic manipulators using nonsingular terminal sliding mode and RBF neural networks , 2016 .

[2]  Sun Fuchun Research and development on theory and algorithms of sliding mode control , 2007 .

[3]  Jiang Long-guan An adaptive control approach for manipulator , 2014 .

[4]  Li Xiaomin Design of a Sliding Mode Control Scheme Based on Improved Exponent Trending Law for Robotic Manipulators , 2012 .

[5]  Cheng Yee Low,et al.  Adaptive Controller Algorithm for 2-DOF Humanoid Robot Arm , 2014 .

[6]  Li Bo Research on the Processing of Vibration Acceleration Signal , 2008 .

[7]  Liu Shirong A Survey of Trajectory Tracking Control for Robot Manipulators , 2011 .

[8]  José de Jesús Rubio,et al.  Learning of operator hand movements via least angle regression to be teached in a manipulator , 2020, Evol. Syst..

[9]  Wei He,et al.  Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints , 2016, IEEE Transactions on Cybernetics.

[10]  C.-K. Lin,et al.  Nonsingular Terminal Sliding Mode Control of Robot Manipulators Using Fuzzy Wavelet Networks , 2006, IEEE Transactions on Fuzzy Systems.

[11]  M. Neila,et al.  Adaptive terminal sliding mode control for rigid robotic manipulators , 2011 .

[12]  Madan M. Gupta,et al.  An adaptive switching learning control method for trajectory tracking of robot manipulators , 2006 .

[13]  Zhihong Man,et al.  Design of fuzzy sliding-mode control systems , 1998, Fuzzy Sets Syst..

[14]  A. Tayebi,et al.  Robust Iterative Learning Control Design: Application to a Robot Manipulator , 2008, IEEE/ASME Transactions on Mechatronics.

[15]  Haoyong Yu,et al.  Hybrid feedback feedforward: An efficient design of adaptive neural network control , 2016, Neural Networks.

[16]  José de Jesús Rubio,et al.  Robust feedback linearization for nonlinear processes control. , 2018, ISA transactions.

[17]  Tsuneo Yoshikawa,et al.  Adaptive Robust Control for Robot Manipulators , 1991 .

[18]  Haoyong Yu,et al.  Biomimetic Hybrid Feedback Feedforward Neural-Network Learning Control , 2017, IEEE Transactions on Neural Networks and Learning Systems.

[19]  Jinkun Liu,et al.  Sliding Mode Control for Robot , 2011 .

[20]  Fang Hui-juan Trajectory Tracking Sliding Mode Control for Robot1 , 2008 .

[21]  Wang San-xi Adaptive Robust Tracking Control for Robotic Manipulators , 2015 .

[22]  Peter Xiaoping Liu,et al.  Robust Sliding Mode Control for Robot Manipulators , 2011, IEEE Transactions on Industrial Electronics.

[23]  Tie Zhang,et al.  Adaptive Neural Network Finite-Time Control for Uncertain Robotic Manipulators , 2013, Journal of Intelligent & Robotic Systems.

[24]  Chih-Min Lin,et al.  Robust Adaptive Tracking Control for Manipulators Based on a TSK Fuzzy Cerebellar Model Articulation Controller , 2018, IEEE Access.

[25]  Chun-Yi Su,et al.  A sliding mode controller with bound estimation for robot manipulators , 1993, IEEE Trans. Robotics Autom..

[26]  Shuzhi Sam Ge,et al.  Neural Network Control of a Rehabilitation Robot by State and Output Feedback , 2015, J. Intell. Robotic Syst..

[27]  Huiming Wang,et al.  Robust Sliding Mode Control for Robots Driven by Compliant Actuators , 2019, IEEE Transactions on Control Systems Technology.

[28]  Huiming Wang,et al.  Continuous sliding mode control of compliant robot arms: A singularly perturbed approach , 2018, Mechatronics.