Interval Type-2 Fuzzy Dynamic High Type Control of Permanent Magnet Synchronous Motor with Vector Decoupling Method
<p>Structure of the PMSM vector control system.</p> "> Figure 2
<p>Current closed-loop control block diagram.</p> "> Figure 3
<p>Structure of the voltage feed-forward decoupling PI.</p> "> Figure 4
<p>Structure of HT based on feed-forward decoupling PI.</p> "> Figure 5
<p>Comparison of HT control effect.</p> "> Figure 6
<p>Structure diagram of a T1FLS.</p> "> Figure 7
<p>Structure of FDHT based on feed-forward decoupling PI.</p> "> Figure 8
<p>MFs of input and output variables. (<b>a</b>) MFs of input variable <span class="html-italic">E</span>; (<b>b</b>) MFs of input variable <math display="inline"><semantics> <mrow> <mi>E</mi> <mi>C</mi> </mrow> </semantics></math>; (<b>c</b>) MFs of output variable <span class="html-italic">U</span>.</p> "> Figure 9
<p>Structure diagram of an IT2FLS.</p> "> Figure 10
<p>MFs of input variables in the IT2FLS. (<b>a</b>) MFs of input variable <span class="html-italic">E</span>; (<b>b</b>) MFs of input variable <math display="inline"><semantics> <mrow> <mi>E</mi> <mi>C</mi> </mrow> </semantics></math>.</p> "> Figure 11
<p>Structure of the PMSM vector control system applying FDPI-FDHT.</p> "> Figure 12
<p>Motor speed tracking results under no-load situation.</p> "> Figure 13
<p>Electromagnetic torque response results in the no-load case.</p> "> Figure 14
<p>Motor speed tracking results under load situation.</p> "> Figure 15
<p>Electromagnetic torque response results in the load case.</p> "> Figure 16
<p>Voltage responses of <math display="inline"><semantics> <msub> <mi>u</mi> <mi>d</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>u</mi> <mi>q</mi> </msub> </semantics></math>. (<b>a</b>) PI; (<b>b</b>) FDPI; (<b>c</b>) FDPI-HT; (<b>d</b>) FDPI-T1FDHT; (<b>e</b>) FDPI-IT2FDHT.</p> "> Figure 17
<p>Three-phase current variation curves. (<b>a</b>) PI; (<b>b</b>) FDPI; (<b>c</b>) FDPI-HT; (<b>d</b>) FDPI-T1FDHT; (<b>e</b>) FDPI-IT2FDHT.</p> "> Figure 18
<p>Current variation of Ia, Ib and Ic. (<b>a</b>) Ia; (<b>b</b>) Ib; (<b>c</b>) Ic.</p> ">
Abstract
:1. Introduction
- (1)
- Fuzzy dynamic high type methods are provided for the vector decoupling control of PMSM.
- (2)
- Aiming at the problem that related parameters in the IT2FLSs are difficult to determine, QPSO is employed.
- (3)
- In addition to the proposed method, PI, FDPI, FDPI-HT, FDPI-T1FDHT are also designed for simulations.
2. PMSM Mathematical Model and Vector Control
2.1. PMSM Mathematical Model
- (1)
- Neglecting the saturation of the motor core;
- (2)
- Excluding eddy current and hysteresis losses in the motor;
- (3)
- The current in the motor is a symmetrical three-phase sine wave current.
2.2. PMSM Vector Control
3. PMSM Traditional Control Methods
3.1. Conventional PI
3.2. Feed-Forward Decoupling PI
4. Fuzzy Dynamic High Type Methods
4.1. QPSO Algorithm
4.2. High Type
4.3. Type-1 Fuzzy Dynamic High Type
4.4. Interval Type-2 Fuzzy Dynamic High Type
5. Simulation Analyses
5.1. Experimental Preparation
5.2. No-Load Situation
5.3. Load Situation
6. Conclusions and Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- Shi, Z.; Zhang, P.; Lin, J.; Ding, H. Permanent Magnet Synchronous Motor Speed Control Based on Improved Active Disturbance Rejection Control. Actuators 2021, 10, 147. [Google Scholar] [CrossRef]
- Sun, X.; Shi, Z.; Lei, G.; Guo, Y.; Zhu, J. Analysis and design optimization of a permanent magnet synchronous motor for a campus patrol electric vehicle. IEEE Trans. Veh. Technol. 2019, 68, 10535–10544. [Google Scholar] [CrossRef]
- Wang, X.; Chen, F.; Zhu, R.; Huang, X.; Sang, N.; Yang, G.; Zhang, C. A Review on Disturbance Analysis and Suppression for Permanent Magnet Linear Synchronous Motor. Actuators 2021, 10, 77. [Google Scholar] [CrossRef]
- Rodríguez, J.; Kennel, R.M.; Espinoza, J.R.; Trincado, M.; Silva, C.A.; Rojas, C.A. High-performance control strategies for electrical drives: An experimental assessment. IEEE Trans. Ind. Electron. 2011, 59, 812–820. [Google Scholar] [CrossRef]
- Adase, L.A.; Alsofyani, I.M.; Lee, K.B. Predictive torque control with simple duty-ratio regulator of PMSM for minimizing torque and flux ripples. IEEE Access 2019, 8, 2373–2381. [Google Scholar] [CrossRef]
- Casadei, D.; Profumo, F.; Serra, G.; Tani, A. FOC and DTC: Two viable schemes for induction motors torque control. IEEE Trans. Power Electron. 2002, 17, 779–787. [Google Scholar] [CrossRef] [Green Version]
- Gong, C.; Hu, Y.; Gao, J.; Wang, Y.; Yan, L. An improved delay-suppressed sliding-mode observer for sensorless vector-controlled PMSM. IEEE Trans. Ind. Electron. 2019, 67, 5913–5923. [Google Scholar] [CrossRef]
- Sant, A.V.; Khadkikar, V.; Xiao, W.; Zeineldin, H.H. Four-axis vector-controlled dual-rotor PMSM for plug-in electric vehicles. IEEE Trans. Ind. Electron. 2014, 62, 3202–3212. [Google Scholar] [CrossRef]
- Lakhe, R.K.; Chaoui, H.; Alzayed, M.; Liu, S. Universal Control of Permanent Magnet Synchronous Motors with Uncertain Dynamics. Actuators 2021, 10, 49. [Google Scholar] [CrossRef]
- Feng, G.; Lai, C.; Kar, N.C. Speed harmonic based decoupled torque ripple minimization control for permanent magnet synchronous machine with minimized loss. IEEE Trans. Energy Convers. 2020, 35, 1796–1805. [Google Scholar] [CrossRef]
- Moon, H.T.; Kim, H.S.; Youn, M.J. A discrete-time predictive current control for PMSM. IEEE Trans. Power Electron. 2003, 18, 464–472. [Google Scholar] [CrossRef]
- Guclu, R.; Gulez, K. Neural network control of seat vibrations of a non-linear full vehicle model using PMSM. Math. Comput. Model. 2008, 47, 1356–1371. [Google Scholar] [CrossRef]
- Xing, Q.J.; Dong, E.B.; Chen, J.; Jiang, Y.H. Dynamic high-type control for the servo system of an photoelectric theodolite. Electron. Opt. Control 2007, 3, 146–149. [Google Scholar]
- Golnaraghi, F.; Kuo, B.C. Automatic Control Systems; McGraw-Hill Education: New York, NY, USA, 2017. [Google Scholar]
- Tang, T.; Ma, J.; Ge, R. PID-I controller of charge coupled device-based tracking loop for fast-steering mirror. Opt. Eng. 2011, 50, 043002. [Google Scholar] [CrossRef]
- Papadopoulos, K.G.; Papastefanaki, E.N.; Margaris, N.I. Explicit analytical PID tuning rules for the design of type-III control loops. IEEE Trans. Ind. Electron. 2012, 60, 4650–4664. [Google Scholar] [CrossRef]
- Castillo, O.; Amador-Angulo, L.; Castro, J.R.; Garcia-Valdez, M. A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems. Inf. Sci. 2016, 354, 257–274. [Google Scholar] [CrossRef]
- Zhao, T.; Liu, J.; Dian, S. Finite-time control for interval type-2 fuzzy time-delay systems with norm-bounded uncertainties and limited communication capacity. Inf. Sci. 2019, 483, 153–173. [Google Scholar] [CrossRef]
- Tong, W.; Zhao, T.; Duan, Q.; Zhang, H.; Mao, Y. Non-singleton interval type-2 fuzzy PID control for high precision electro-optical tracking system. ISA Trans. 2021, in press. [Google Scholar] [CrossRef]
- Zhao, T.; Dian, S. State feedback control for interval type-2 fuzzy systems with time-varying delay and unreliable communication links. IEEE Trans. Fuzzy Syst. 2017, 26, 951–966. [Google Scholar] [CrossRef]
- Barkat, S.; Tlemçani, A.; Nouri, H. Noninteracting adaptive control of PMSM using interval type-2 fuzzy logic systems. IEEE Trans. Fuzzy Syst. 2011, 19, 925–936. [Google Scholar] [CrossRef]
- Chaoui, H.; Khayamy, M.; Aljarboua, A.A. Adaptive interval type-2 fuzzy logic control for PMSM drives with a modified reference frame. IEEE Trans. Ind. Electron. 2017, 64, 3786–3797. [Google Scholar] [CrossRef]
- Whitley, D. A genetic algorithm tutorial. Stat. Comput. 1994, 4, 65–85. [Google Scholar] [CrossRef]
- Marini, F.; Walczak, B. Particle swarm optimization (PSO). A tutorial. Chemom. Intell. Lab. Syst. 2015, 149, 153–165. [Google Scholar] [CrossRef]
- Omkar, S.; Khandelwal, R.; Ananth, T.; Naik, G.N.; Gopalakrishnan, S. Quantum behaved Particle Swarm Optimization (QPSO) for multi-objective design optimization of composite structures. Expert Syst. Appl. 2009, 36, 11312–11322. [Google Scholar] [CrossRef]
- Thike, R.; Pillay, P. Mathematical model of an interior pmsm with aligned magnet and reluctance torques. IEEE Trans. Transp. Electrif. 2020, 6, 647–658. [Google Scholar] [CrossRef]
- Liu, T.T.; Tan, Y.; Wu, G.; Wang, S.M. Simulation of PMSM vector control system based on Matlab/Simulink. In Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation, Zhangjiajie, China, 11–12 April 2009; Volume 2, pp. 343–346. [Google Scholar]
- Zhu, H.; Xiao, X.; Li, Y. PI type dynamic decoupling control scheme for PMSM high speed operation. In Proceedings of the 2010 Twenty-Fifth Annual IEEE Applied Power Electronics Conference and Exposition (APEC), Palm Springs, CA, USA, 21–25 February 2010; pp. 1736–1739. [Google Scholar]
- Xingye, G.; Chuang, L.; Yuefei, Z.; Kai, W. Analysis and dynamic decoupling control schemes for PMSM current Loop. In Proceedings of the 2016 IEEE International Conference on Aircraft Utility Systems (AUS), Beijing, China, 10–12 October 2016; pp. 570–574. [Google Scholar]
- Nie, M.; Tan, W.W. Towards an efficient type-reduction method for interval type-2 fuzzy logic systems. In Proceedings of the 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), Hong Kong, China, 1–6 June 2008; pp. 1425–1432. [Google Scholar]
- Leonhard, W. Control of Electrical Drives; Springer Science & Business Media: New York, NY, USA, 2001. [Google Scholar]
0 | 7.4876 | 38.20 | 22.4% |
10 | 7.0199 | 35.82 | 23.7% |
20 | 6.5607 | 24.84 | 32.2% |
30 | 6.1593 | 27.90 | 46.1% |
40 | 5.8526 | 32.27 | 53.7% |
Rules | E | |||||
---|---|---|---|---|---|---|
NB | N | Z | P | PB | ||
EC | N | PB | PB | N | Z | P |
Z | P | Z | Z | PB | PB | |
P | N | N | Z | N | N |
Consequent | Range (r/min) | Consequent | Range (r/min) |
---|---|---|---|
N | [−35,000, −30,000] | P | [15,000, 20,000] |
Z | [−10, 10] | PB | [25,000, 30,000] |
Parameter | Value |
---|---|
Pole pairs | 4 |
Inertia | 0.003 |
Stator resistance | 0.958 |
d-axis inductance | 5.25 |
q-axis inductance | 12 |
Flux linkage | 0.1827 |
Viscous damping | 0.008 |
Torque constant | 1.0962 |
Parameter | Value |
---|---|
Speed outer loop | 0.14 |
Speed outer loop | 7 |
d-axis current inner loop | 17.5 |
d-axis current inner loop | 3193.3 |
q-axis current inner loop | 40 |
q-axis current inner loop | 3193.3 |
Parameter | Value |
---|---|
Maximum generation G | 100 |
Population size M | 50 |
Dimension N | 1 or 3 |
Contraction-expansion coefficient | [2, ..., 1] |
Method | Optimized Parameters |
---|---|
FDPI-HT | |
FDPI-T1FDHT | |
FDPI-IT2FDHT |
Method | IAE | ITSE | ISE |
---|---|---|---|
PI | 11.5138 | 28.8293 | 5.4714 × 103 |
FDPI | 10.5075 | 23.4418 | 5.0137 × 103 |
FDPI-HT | 9.8549 | 26.5121 | 5.0747 × 103 |
FDPI-T1FDHT | 9.5774 | 18.0999 | 4.3204 × 103 |
FDPI-IT2FDHT | 9.0851 | 16.0875 | 4.0772 × 103 |
Method | IAE | ITSE | ISE |
---|---|---|---|
PI | 12.7659 | 41.2678 | 5.5309 × 103 |
FDPI | 11.7122 | 33.4576 | 5.0612 × 103 |
FDPI-HT | 10.9804 | 35.3746 | 5.1168 × 103 |
FDPI-T1FDHT | 10.7188 | 25.2505 | 4.3542 × 103 |
FDPI-IT2FDHT | 10.3825 | 24.4755 | 4.1169 × 103 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Chen, X.; Tong, W.; Mao, Y.; Zhao, T. Interval Type-2 Fuzzy Dynamic High Type Control of Permanent Magnet Synchronous Motor with Vector Decoupling Method. Actuators 2021, 10, 293. https://doi.org/10.3390/act10110293
Chen X, Tong W, Mao Y, Zhao T. Interval Type-2 Fuzzy Dynamic High Type Control of Permanent Magnet Synchronous Motor with Vector Decoupling Method. Actuators. 2021; 10(11):293. https://doi.org/10.3390/act10110293
Chicago/Turabian StyleChen, Xinglong, Wei Tong, Yao Mao, and Tao Zhao. 2021. "Interval Type-2 Fuzzy Dynamic High Type Control of Permanent Magnet Synchronous Motor with Vector Decoupling Method" Actuators 10, no. 11: 293. https://doi.org/10.3390/act10110293