Finite Time Back-Stepping Algorithm to Control Permanent Magnet Synchronous Motor Speed

محورهای موضوعی : Electrical Engineering

Nazanin Seyed Gogani ¹ (Renewable energy research center, Damavand Brach, Islamic Azad University, Damavand, Iran)
vahid behnamgol ² (Faculty of Electrical& Computer, MalekAshtar University of Technology, Iran)
Seyed Mahdi Hakimi ³ (Renewable energy research center, Damavand Brach, Islamic Azad University, Damavand, Iran)
Ghasem Derakhshan ⁴ (Renewable energy research center, Damavand Brach, Islamic Azad University, Damavand, Iran)

تاریخ دریافت : 1400/09/03 تاریخ پذیرش : 1400/11/15 تاریخ انتشار : 1400/09/10

کلید واژه: nonlinear control, Permanent Magnet Synchronous Motor, Finite time convergence,

چکیده مقاله :

In this paper, the speed control of a permanent magnet synchronous motor is performed in a desired finite time. Due to the nonlinearity of the dynamics of this type of motors and the form of the state equations, a back-stepping strategy has been chosen to design the control system. In the proposed method, in each design step, the finite time stability condition is used, so the nonlinear controller has the ability to guarantee finite time convergence of output tracking error. The finite time stability of the proposed control method is proved based on Lyapunov theory. Adjusting the convergence time of system outputs can be done by changing the gain of the controllers. Furthermore, the proposed controller generates smooth control signal that can be implemented. The simulation results show that the proposed method is able to control the speed and current of a permanent magnet synchronous motor in desired finite time.

منابع و مأخذ:

• Chikh, et al., Improved DTC Algorithms for Reducing Torque and Flux Ripples of PMSM Based on Fuzzy Logic and PWM Techniques,INTECH Open Access Publisher, 2012.


• Xiao, et al., Performance control of PMSM drives using a self-tuning PID, IEEE International Conference on in Electric Machines and Drives, 2005.


• Huazhong, et al., Design of vector controller of PMSM based on Pan-Boolean algebra self-adapting PID control, International Conference on in Mechatronics and Automation, 2009.


• Jong-Woo and L. Sang-Cheol, Antiwindup Strategy for PI-Type Speed Controller, IEEE Transactions on Industrial Electronics, Vol. 56, 2009.


• Kumar, et al., Intelligent Tuned PID Controllers for PMSM Drive - A Critical Analysis, IEEE International Conference on Industrial Technology, 2006.


• J. Underwood and I. Husain, Online Parameter Estimation and Adaptive Control of Permanent-Magnet Synchronous Machines, IEEE Transactions on Industrial Electronics, Vol. 57, 2010.


• F. M. El-Sousy, High-performance neural-network model-following speed controller for vector-controlled PMSM drive system, IEEE International Conference on Industrial Technology, Vol. 1, 2004.


• DENG, et al., Speed Control of Switched Reluctance Motor using Sliding Mode Variable Structure Control, Micromotors Servo Technique, Vol. 7, 2006.


• Niu, et al., A predictive current control scheme for permanent magnet synchronous motors, Proceedings of the Chinese Society of Electrical Engineering, 2012.


• Y. Cheng and Y. Y. Tzou, Fuzzy optimization techniques applied to the design of a digital PMSM servo drive, IEEE Transactions on Power electronics, , Vol. 19, 2004.


• Siami, D. Arab Khaburi, and J. Rodriguez, Simplified finite control set-model predictive control for matrix converter-fed PMSM drives, IEEE Transactions on Power Electronics, Vol. 33, No.3, 2018.


• Zhang, L. Zhang, and Y. Zhang, Model predictive current control for PMSM drives with parameter robustness improvement, IEEE Transactions on Power Electronics, Vol. 34, No. 2, 2019.


• Zhang, et al. Electrolytic Capacitor-Less PMSM Control System With a Neural Network-Based Bus Voltage Fluctuation Suppression Strategy, IEEE International Power Electronics and Application Conference and Exposition, 2018.


• Leiming, et al. Research on PMSM Sensorless Control Based on Improved RBF Neural Network Algorithm, 2018 37th Chinese Control Conference, 2018.


• Liang, et al. Adaptive second-order sliding-mode observer for PMSM sensorless control considering VSI nonlinearity, IEEE Transactions on Power Electronics,Vol. 33, No. 10, 2018.


• Mani, et al. Adaptive fractional fuzzy integral sliding mode control for PMSM model, IEEE Transactions on Fuzzy Systems,2018.


• Tian, et al. Rotor Position Estimation of Sensorless PMSM Based on ExtendedKalman Filter, IEEE International Conference on Mechatronics, Robotics and Automation, 2018.


• Lyu, et al. Robust Nonlinear Predictive Current Control Techniques for PMSM, Energies, Vol. 12, No. 3, 2019.


• Zhou, Sh. Sun, Guidance Laws with Finite Time Convergence, Journal of Guidance, Control, and Dynamics, Vol. 32, No. 6, 2009.


• Hong, J. Huang, and Y. Xu, On an Output Feedback Finite-Time Stabilization Problem, IEEE Transactions on Automatic Control, Vol. 46, No. 2, 2001.


• Hong, Finite-time stabilization and stabilizability of a class of controllable systems, Systems & Control Letters, Vol. 46, 2002.


• Huang, W. Lin, B. Yang, Global finite-time stabilization of a class of uncertain nonlinear systems, Automatica, Vol. 41, 2005.


• B. Shtessel, I. A. Shkolnikov, and A. Levant, Smooth second-order sliding modes: Missile guidance application, Automatica, Vol. 43, 2007.


• Shtessel, M. Taleb, F. Plestan, A novel adaptive-gain super twisting sliding mode controller: Methodology and application, Automatica, Vol. 48, 2012.


• Parvathy and R. Devanathan, Linearization of Permanent Magnet Synchronous Motor Using MATLAB and Simulink,INTECH Open Access Publisher, 2011.


• G. Hong, Finite Time Stabilization and Stability of a Class of Controllable Systems,Systems and Control Letters, Vol. 46, 2002.


• P. Bhat and D. S. Bernstein, Continuous Finite-Time Stabilization of the Translational and Rotational Double Integrators, IEEE Transactions on Automatic Control, Vol. 43, 1998.


• P. Bhat and D.S. Bernstein. Finite time stability of continuous autonomous systems. SIAM J. Control Optim, Vol. 38, 2000