Abstract
This paper deals with a new design of a hybrid fuzzy super-twisting sliding mode controller (HFSTSMC) for a three-phase induction motor (IM) controlled by the rotor flux orientation technique. Super-twisting sliding mode control is employed as a potential solution to limit the inherent chattering effect in the conventional sliding mode control without affecting the tracking accuracy and robustness. The super-twisting sliding mode control (STSMC) scheme is a modified second-order sliding mode control (SOSMC) scheme that does not need the information of any derivative of the sliding surface, but the experimental control coefficients found in the control law have an obvious effect on limiting chattering and the system response speed. Therefore, a robust hybrid controller was proposed based on the fuzzy logic control (FLC) approach to optimally tuning these coefficients. Whereas, the fuzzy logic controller is used as a supervisory controller to adjust the value of the gains according to the state of the system. Thus, providing high dynamic performance and achieving the highest rates of robustness in transient and uncertain conditions. On the other hand, increasing tracking accuracy and chattering phenomena reduction in steady states. The validation of the suggested scheme is verified by experimental approximating of simulations using MATLAB/SIMULINK and also compared with conventional and advanced controllers. The obtained results confirm the reduction of the chattering phenomenon and thus reduction of the total harmonic distortion (THD) in the motor current, and the effectiveness of the proposed scheme in various operating conditions.
Similar content being viewed by others
Notes
IAE: Integral absolute error ISE: Integral square error They are performance measures of the error value of any feedback control system. Thus reducing performance measures will ensure the minimization of error. as the error may become negative also that is why these performance measures are mostly expressed in terms of either absolute value of error or in terms of square error
References
Leonhard W (1996) Controlled AC drives, a successful transfer from ideas to industrial practice. Control Eng Pract 4(7):897–908
Fitzgerald AE, Kingsley CU, Stephen D (1990) Electric machinery. McGraw-Hill, New York
Krishnan R (2002) Electric motors drives modeling analysis and control. Publication Prentice Hall of India, Upper Saddle River
Blaschke F (1972) The principle of field orientation as applied to the new transvector closed-loop system for rotating-field machines. Siemens Rev 34(3):217–220
Hasse K (1968) Zum Dynamischen Verhalten der Asynchronmachine bei Betriek Mit Variabler Standerfrequenz und Standerspannung ETZ-A 89
Zhang Y, Jiang Z, Yu X (2008) Indirect field-oriented control of induction machines based on synergetic control theory IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, Pittsburgh, PA 1–7
Guoa Z, Zhanga J, Suna Z, Zheng C (2017) Indirect field oriented control of three-phase induction motor based on current-source inverter. Procedia Eng 174:588–594
Srinu Nai B (2014) Comparison of direct and indirect vector control of induction motor. Int J New Technol Sci Eng 1(1)
Gunabalan R, Subbiah V (2015) Speed sensorless vector control of induction motor drive with PI and fuzzy controller. Int J Power Electron Drive Syst 3:315–325
Vallabhai MJ, Swarnkar P, Deshpande DM (2012) PI control based vector control strategy for induction motor drive. Int J Electron Commun Computer Eng 3(2):328–335
Yongchang Z, Zhengming Z (2008) Comparative study of PI, sliding mode and fuzzy logic controller for rotor field oriented controlled induction motor drives Proc 11th Int Conf Electr Mach Syst ICEMS 1(3): 1089–1094
Biranchi NK, Satish C, Kanungo BM, Madhu S (2011) Indirect vector control of induction motor using sliding-mode controller. International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2011):507–511. https://doi.org/10.1049/cp.2011.0415
Patakor FA, Sulaiman M, Ibrahim Z (2013) Sliding mode speed control for induction motor drives with state-dependent gain method. Int Rev Electric Eng 8(8):1446–1453
Brehm T, Rattan K S (1994) Hybrid fuzzy logic PID controller. Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference 3: 1682–1687
Fadaei F, Shahbazian M, Aghajani M, Jazayeri-Rad H (2013) A novel hybrid fuzzy PID controller based on cooperative co-evolutionary genetic algorithm. J Basic Appl Sci Res 3:337–344
- Kumar A, JL FD (2013) A novel self-tuning fuzzy based PID controller for speed control of induction motor drive IEEE International Conference on Control Communication and Computing
Saghafinia A, Ping HW, Uddin MN, Gaeid KS (2015) Adaptive fuzzy sliding mode control into chattering-free IM drive. IEEE Trans Ind Appl 51(1):692–701
Ardjoun S, Abid M (2015) Fuzzy sliding mode control applied to a doubly fed induction generator for wind turbines. Turkish J Electric Eng Computer Sci 23(6):1673–1686
Abderazak S, Farid N (2017) Comparative study between Sliding mode controller and Fuzzy Sliding mode controller in a speed control for doubly fed induction motor 4th Int Conf Control Eng Inf Technol1–6
Lekhchine S, Bahi T, Abadlia I, Bouzeria H (2017) PV-battery energy storage system operating of asynchronous motor driven by using fuzzy sliding mode control. Int J Hydrog Energy 42(13):8756–8764
Sahu A, Mohanty KB, Mishra RN, Nayak DR. (2020) Adaptive fuzzy sliding mode-based torque and speed compensator for DTC IM drive In2020 IEEE 29th International Symposium on Industrial Electronics (ISIE) 2020 Jun 17:247–252
Lu YK (2015) Adaptive fuzzy integral sliding-mode regulator for induction motor using nonlinear sliding surface. Int J Power Electron Drive Syst 5(4):512–519
Yang Y, Chen Y, Chu Y, Wang Y, Liang Q (2016) Fractional order adaptive sliding mode controller for permanent magnet synchronous motor. Chinese Control Conf: 3412–3416
Zaidi E, Marouani K, Bouadi H, Kassel AE, Bentouhami L, Merabet E (2019) Fuzzy sliding mode method for speed regulation of a dual star induction machine drive fed by multi-level inverters Proc 2018 Int Conf Appl Smart Syst: 24–25
Eksin I, Guzelkaya M, Tokat S (2002) Sliding surface slope adjustment in fuzzy sliding mode controller In Mediterranean Conference 160–168
Yorgancıoğlu F, Kömürcügil H (2008) Single-input fuzzy-like moving sliding surface approach to the sliding mode control. Electr Eng 90(3):199–207
Wang SY, Lin CM, Tseng CL, Chou JH, Syu BL (2017) Design of a fuzzy sliding-mode controller for induction motor vector control systems Int Autom Control Conf 206–211
Barrero F, Torralba A, Franquelo LG (2002) Speed control of induction motors using a novel fuzzy sliding-mode structure. IEEE Trans Fuzzy Syst 10(3):375–383
Ahmed H, Rajoriya A (2017) A hybrid of sliding mode control and fuzzy logic control using a fuzzy supervisory switched system for DC motor speed control. Turkish J Electr Eng Comput Sci 25(3):1993–2004
- Layadi N, Djerioui A, Zeghlache S, Houari A, Benkhoris MF, Berrabah F (2018) A hybrid fuzzy sliding mode controller for a double star induction machine International Conference on Communications and Electrical Engineering (ICCEE):1–6
Levant A (1993) Sliding order and sliding accuracy in sliding mode control. Int J Control 58(6):1247–1263
Bartolini G, Ferrara A, Usai E (1998) Chattering avoidance by second-order sliding mode control. IEEE Transactions Automatic Control 43(2):241–246
Morfin OA, Valenzuela FA, Betancour RR, CastañEda CE, Ruíz-Cruz R, Valderrabano-Gonzalez A (2018) Real-time SOSM super-twisting combined with block control for regulating induction motor velocity. IEEE Access 6:25898–25907
Chiang HK, Lin WB, Chang YC, Fang CC (2011) Super-twisting second-order sliding mode control for a synchronous reluctance motor. Artif Life Robot 16(3):307–310
Ammar A, Benakcha A, Bourek A (2017) Closed loop torque SVM-DTC based on robust super twisting speed controller for induction motor drive with efficiency optimization International. J Hydrog Energy 42(28):17940–17952
Fei J, Feng Z (2021) Adaptive super-twisting sliding mode control for micro gyroscope based on double loop fuzzy neural network structure. Int J Mach Learn Cybern 12(3):611–624
Abdul Zahra AK, Abdalla TY (2021) Design of fuzzy super twisting sliding mode control scheme for unknown full vehicle active suspension systems using an artificial bee colony optimization algorithm. Asian J Control 23(4):1966–1981
Li M, Li Y, Wang Q (2021) Adaptive fuzzy backstepping super-twisting sliding mode control of nonlinear systems with unknown hysteresis. Asian J Control 1–18. https://doi.org/10.1002/asjc.2554
Ferhat N, Aounallah T, Essounbouli N, Bouchafaa F, Hamzaoui A (2021) Fractional-Order Adaptive Fuzzy Super Twisting Sliding Mode Controller for Permanent Magnet Synchronous Generators. InIECON 2021–47th Annual Conference of the IEEE Industrial Electronics Society 2021: 1–7
Soufyane B, Abdelhamid R, Smail Z. (2019) Fuzzy-Variable Gain Super Twisting Algorithm Control Design for Direct-Drive PMSG Wind Turbines In2019 IEEE 58th Conference on Decision and Control (CDC) 2019 Dec 11: 4885–4890
Bala JA, Sadiq T, Aibinu AM, Folorunso TA (2021) A fuzzy super twisting sliding mode control scheme for velocity regulation in autonomous vehicles In2021 1st International Conference on Multidisciplinary Engineering and Applied Science (ICMEAS) 2021 Jul 15:1–7
Nguyen NP, Kim W, Moon J (2019) Super-twisting observer-based sliding mode control with fuzzy variable gains and its applications to fully-actuated hexarotors. J Franklin Inst 356(8):4270–4303
Rashed M, Goh KB, Dunnigan MW, MacConnell PFA, Stronach AF, Williams BW (2005) Sensorless second-order sliding-mode speed control of a voltage-fed induction motor drive using nonlinear state feedback. IEE Proc Electr Power Appl 152(5):1127–1136
Dávila A, Moreno JA, Fridman L (2009) Optimal Lyapunov function selection for reaching time estimation of Super Twisting algorithm Proceedings of the 48h IEEE Conference on Decision and Control Conference:8405–8410
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Abdulhamid Alamoura: Abdülhamit Nurettin’s name can be written in two different ways due to his dual citizenship.
Rights and permissions
About this article
Cite this article
Nurettin, A., İnanç, N. Design of a robust hybrid fuzzy super-twisting speed controller for induction motor vector control systems. Neural Comput & Applic 34, 19863–19876 (2022). https://doi.org/10.1007/s00521-022-07519-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00521-022-07519-4