A noval speed control strategy based on multi model framework for continuous wave mud pulser

Speed control of permanent magnet synchronous motor (PMSM) is the key part of continuous wave mud pulse generator to transmit data. In this paper, a multi model framework speed control of PMSM is proposed for the continuous wave mud pulser control system. With the knowing of the relationship between the PMSM mathematical model parameters and the temperature of the external environment, the decomposition of the PMSM model is carried out by the multiple model thinking. Then, different PID controllers are designed for the PMSM speed control based on the mathematical model corresponding to different external environment temperatures. Simulation results show that this control strategy solves the shortcoming of using a single PID controller and improves the speed tracking performance with the periodic step given signals.

[1]  Hong Song,et al.  Based on Adaptive Backstepping Error Control for Permanent Magnet Synchronous Motor , 2016 .

[2]  Shihong Ding,et al.  Design of an adaptive nonsingular terminal sliding model control method for a bearingless permanent magnet synchronous motor , 2017 .

[3]  Hyun-Suk Yang.  Parameter estimation of permanent magnet synchronous motor and adaptive control by MRAS , 2016 .

[4]  Kittithuch Paponpen,et al.  LQR state feedback controller based on particle swarm optimization for IPMSM drive system , 2015, 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA).

[5]  Sehoon Oh,et al.  A High-Precision Motion Control Based on a Periodic Adaptive Disturbance Observer in a PMLSM , 2015, IEEE/ASME Transactions on Mechatronics.

[6]  Yongchang Zhang,et al.  An improved model predictive current control of permanent magnet synchronous motor drives , 2016, 2016 IEEE Applied Power Electronics Conference and Exposition (APEC).

[7]  A. Fezzani,et al.  Robust control of permanent magnet synchronous motor , 2014, 2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA).

[8]  Nabil Derbel,et al.  Nonlinear adaptive backstepping control for variable-speed wind energy conversion system-based permanent magnet synchronous generator , 2017 .

[9]  Xinghuo Yu,et al.  High-Order Terminal Sliding-Mode Observer for Parameter Estimation of a Permanent-Magnet Synchronous Motor , 2013, IEEE Transactions on Industrial Electronics.

[10]  John E. Fletcher,et al.  A Linear Quadratic Regulator-Based Optimal Direct Thrust Force Control of Linear Permanent-Magnet Synchronous Motor , 2016, IEEE Transactions on Industrial Electronics.

[11]  Haisheng Yu,et al.  Position control of permanent magnet synchronous motor speed sensorless servo system via backstepping , 2015, The 27th Chinese Control and Decision Conference (2015 CCDC).

[12]  Christopher Edwards,et al.  Anti-windup and bumpless-transfer schemes , 1998, Autom..

[13]  Cao Shaozhong,et al.  Model reference adaptive control system simulation of permanent magnet synchronous motor , 2015, 2015 IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC).

[14]  Rodrigo Padilha Vieira,et al.  Sliding mode current control based on disturbance observer applied to permanent magnet synchronous motor , 2015 .

[15]  Alberto Bemporad,et al.  Online model predictive torque control for Permanent Magnet Synchronous Motors , 2015, 2015 IEEE International Conference on Industrial Technology (ICIT).