Robust Continuous Sliding Mode Control for Manipulator PMSM Trajectory Tracking System Under Time-Varying Uncertain Disturbances

This paper focuses on a robust continuous sliding mode control (RCSMC) method for manipulator PMSM trajectory tracking system under time-varying uncertain disturbances. The main objective of this study is to improve the trajectory tracking dynamic response and disturbances rejection ability of the manipulator PMSM, and then the manipulator itself, by using the RCSMC method. The RCSMC method consists of two key parts: a terminal continuous sliding mode controller (TCSMC), and an extended state observer (ESO). The TCSMC has been demonstrated to have remarkable capabilities to reduce the chattering phenomenon caused by high frequency switching function in the conventional sliding mode control law, and reject the strong time-varying uncertain disturbances for PMSM velocity loops. However, the high control gain, which could lead high velocity steady state fluctuations, is needed. Therefore, an extended state observer is introduced to estimate the disturbances. The estimated disturbances are further used by the velocity loop controller as a kind of feed-forward compensation to reduce the gain of the TCSMC method. The stability of the PMSM trajectory tracking system with the RCSMC algorithm is guaranteed by the Lyapunov stability criteria. Simulations have been conducted to verify the performance of the proposed RCSMC algorithm. Finally, the proposed RCSMC algorithm is applied in a practical 6-DOF manipulator, and the experimental results exhibit the extraordinary robustness and capabilities in dynamic position tracking characteristics, velocity response and disturbances rejection.

[1]  Fayez F. M. El-Sousy,et al.  Fuzzy adaptive neural-network model-following speed control for PMSM drives , 2005 .

[2]  Shuhong Wang,et al.  Study of A PMSM Model Incorporating Structural and Saturation Saliencies , 2005, 2005 International Conference on Power Electronics and Drives Systems.

[3]  Chaouki Aouiti,et al.  Finite-time stabilization of uncertain delayed-hopfield neural networks with a time-varying leakage delay via non-chattering control , 2019 .

[4]  Saleh Mobayen,et al.  Chaos synchronization of uncertain chaotic systems using composite nonlinear feedback based integral sliding mode control. , 2018, ISA transactions.

[5]  Huai-Ning Wu,et al.  Disturbance observer based reliable H ∞ fuzzy attitude tracking control for Mars entry vehicles with actuator failures , 2018, Aerospace Science and Technology.

[6]  Yangsheng Chen,et al.  Adaptive load observer-based feed-forward control in PMSM drive system , 2015 .

[7]  Yan Li Yang,et al.  Sliding Mode Variable Structure Control of Active Magnetic Bearings Using Boundary Layer Approach , 2011 .

[8]  Sajad Jafari,et al.  Robust finite-time synchronization of a class of chaotic systems via adaptive global sliding mode control , 2018 .

[9]  Chen Song,et al.  Application of output feedback sliding mode control to active flutter suppression of two-dimensional airfoil , 2010 .

[10]  Leonid Fridman,et al.  Sliding Modes after the First Decade of the 21st Century : State of the Art , 2011 .

[11]  Khaled Ali Abuhasel Intelligent Mixed H2/H? Adaptive Tracking Control System Design Using Self-Organizing Recurrent Fuzzy-Wavelet-Neural-Network for Uncertain Two-Axis Motion Control System , 2016 .

[12]  Jang-Mok Kim,et al.  A Dead Time Compensation Algorithm of Independent Multi-Phase PMSM with Three- Dimensional Space Vector Control , 2013 .

[13]  Saeed Amirkhani,et al.  Fast terminal sliding mode tracking control of nonlinear uncertain mass–spring system with experimental verifications , 2019, International Journal of Advanced Robotic Systems.

[14]  Li Lin,et al.  Vibration control of piezoelectric flexible manipulator based on fuzzy self-tuning PID algorithm , 2010 .

[15]  Limei Wang,et al.  Fuzzy Self-adapting PID Control of PMSM Servo System , 2007, 2007 IEEE International Electric Machines & Drives Conference.

[16]  Huiming Wang,et al.  Generalized proportional integral observer based sliding mode control method for PMSM speed regulation system , 2015, The 27th Chinese Control and Decision Conference (2015 CCDC).

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

[18]  Yugong Luo,et al.  An adaptive cascade trajectory tracking control for over-actuated autonomous electric vehicles with input saturation , 2019 .

[19]  Zhanfeng Song,et al.  A modified predictive control strategy of three-phase grid-connected converters with optimized action time sequence , 2013 .

[20]  Yongchang Zhang,et al.  Model Predictive Current Control for PMSM Drives With Parameter Robustness Improvement , 2019, IEEE Transactions on Power Electronics.

[21]  Jun Yang,et al.  Continuous Sliding Mode Control for Permanent Magnet Synchronous Motor Speed Regulation Systems Under Time-Varying Disturbances , 2016 .

[22]  Min Tan,et al.  A marsupial robotic fish team: Design, motion and cooperation , 2010 .

[23]  Changyin Sun,et al.  Robust Continuous Terminal Sliding Mode Control Design for a Near-Space Hypersonic Vehicle , 2013, IScIDE.

[24]  Aishwarya Apte,et al.  Disturbance observer based speed control of PMSM using fractional order PI controller , 2019, IEEE/CAA Journal of Automatica Sinica.

[25]  Ming Cheng,et al.  Design, analysis and control of hybrid excited doubly salient stator-permanent-magnet motor , 2010 .

[26]  Bin Xu,et al.  Disturbance Observer-Based Dynamic Surface Control of Transport Aircraft With Continuous Heavy Cargo Airdrop , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[27]  Ying-Shieh Kung,et al.  FPGA-Based Speed Control IC for PMSM Drive With Adaptive Fuzzy Control , 2007, IEEE Transactions on Power Electronics.

[28]  Saleh Mobayen,et al.  Design of an adaptive super-twisting decoupled terminal sliding mode control scheme for a class of fourth-order systems. , 2018, ISA transactions.