
تعداد نشریات | 33 |
تعداد شمارهها | 776 |
تعداد مقالات | 7,518 |
تعداد مشاهده مقاله | 12,637,011 |
تعداد دریافت فایل اصل مقاله | 8,530,595 |
Adaptive Non-singular Fast Terminal Sliding Mode Control and Synchronization of a Chaotic System via Interval Type-2 Fuzzy Inference System with Proportionate Controller | ||
Iranian Journal of Fuzzy Systems | ||
دوره 20، شماره 6، بهمن و اسفند 2023، صفحه 171-185 اصل مقاله (6.38 M) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22111/ijfs.2023.39658.6889 | ||
نویسندگان | ||
Mohammad Ali Labbaf Khaniki1؛ Mohammad Manthouri* 2؛ Mojtaba Ahmadieh Khanesar3 | ||
1Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran. | ||
2Electrical and Electronic Engineering Department, Shahed university, Persian Gulf Highway | ||
3Department of Material, Mechanical and Manufacturing, University of Nottingham, UK | ||
چکیده | ||
This paper introduces a novel adaptive nonsingular fast terminal sliding mode approach that benefits from an interval type-2 fuzzy logic estimator and a gain for control and synchronization of chaotic systems in the presence of uncertainty. The nonsingular fast terminal sliding mode controller is developed to increase the convergence rate and remove the singularity problem of the system. Using the proposed method, the finite-time convergence has been ensured. To eliminate the chattering phenomenon in the conventional sliding mode controller, the discontinuous sign function is estimated using an interval type-2 fuzzy inference system (FIS) based on the center of sets type reduction followed by defuzzification. By adding the proportionate gain to the interval type-2 FIS, the robustness and speed of the controller system is enhanced. An appropriate Lyapunov function is utilized to ensure the closed-loop stability of the control system. The performance of the controller is evaluated for a nonlinear time-varying second-order magnetic space-craft chaotic system with different initial conditions in the presence of uncertainty. The simulation results show the efficacy of the proposed approach for the tracking control problems. The time and frequency domain analysis of the control signal demonstrates that the chattering phenomenon is successfully diminished. | ||
کلیدواژهها | ||
Chaos؛ Non-singular terminal sliding mode control؛ Adaptive control؛ interval type-2 fuzzy inference system | ||
مراجع | ||
[1] P. Akbary, M. Ghiasi, M. R. R. Pourkheranjani, H. Alipour, N. Ghadimi, Extracting appropriate nodal marginal prices for all types of committed reserve, Computational Economics, 53(1) (2019), 1-26. [2] R. K. Amirabadi, O. S. Fard, A. Mansoori, A novel fuzzy sliding mode control approach for chaotic systems, Iranian Journal of Fuzzy Systems, 18(6) (2021), 133-150. [3] M. H. Barhaghtalab, S. Mobayen, F. Merrikh-Bavat, Design of a global sliding mode controller using hyperbolic func- tions for nonlinear systems and application in chaotic systems, ICEE 2019 - 27th Iranian Conference on Electrical Engineering, (2019), 1030-1034. [4] M. Boukattaya, N. Mezghani, T. Damak, Adaptive nonsingular fast terminal sliding-mode control for the tracking problem of uncertain dynamical systems, ISA Transactions, 77 (2018), 1-19. [5] W. Cai, R. Mohammaditab, G. Fathi, K. Wakil, A. G. Ebadi, N. Ghadimi, Optimal bidding and o ering strategies of compressed air energy storage: A hybrid robust-stochastic approach, Renewable Energy, 143 (2019), 1-8. [6] F. Farivar, M. A. Shoorehdeli, M. A. Nekoui, M. Teshnehlab, Chaos synchronization of uncertain nonlinear gyros via hybrid control, IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM, 1 (2009), 1365-1370. [7] Y. Feng, X. Yu, Z. Man, Non-singular terminal sliding mode control of rigid manipulators, Automatica, 38(12) (2002), 2159-2167. [8] K. Hooshmandi, F. Bayat, M. Jahedmotlagh, A. Jalali, Guaranteed cost nonlinear sampled-data control: Applications to a class of chaotic systems, Nonlinear Dynamics, 100 (2020), 731-748. [9] J. Huang, J. Yang, D. Xie, D. Wu, Optimal sliding mode chaos control of direct-drive wave power converter, IEEE Access, 7 (2019), 90922-90930. [10] Y. Jin, W. Cao, M.Wu, Y. Yuan, Data-based variable universe adaptive fuzzy controller with self-tuning parameters, Applied Soft Computing, 123 (2022), 108944. [11] S. Johari, M. Yaghoobi, H. R. Kobravi, Nonlinear model predictive control based on hyper chaotic diagonal recurrent neural network, Journal of Central South University, 29(1) (2022), 197-208. [12] R. Kavikumar, B. Kaviarasan, Y. G. Lee, O. M. Kwon, R. Sakthivel, S. G. Choi, Robust dynamic sliding mode control design for interval type-2 fuzzy systems, Discrete and Continuous Dynamical Systems, 15(7) (2022), 1839. [13] R. Khalili Amirabadi, O. S. Fard, A. Mansoori, A novel fuzzy sliding mode control approach for chaotic systems, Iranian Journal of Fuzzy Systems, 18(6) (2021), 133-150. [14] M. A. Khanesar, E. Kayacan, M. Reyhanoglu, O. Kaynak, Feedback error learning control of magnetic satellites using type-2 fuzzy neural networks with elliptic membership functions, IEEE Transactions on Cybernetics, 45(4) (2015), 858-868. [15] M. A. Khanesar, J. M. Mendel, Maclaurin series expansion complexity-reduced center of sets type-reduction + defuzzi cation for interval type-2 fuzzy systems, 2016 IEEE International Conference on Fuzzy Systems, no. D, (2016), 1224-1231. [16] M. A. L. Khaniki, M. B. Hadi, M. Manthouri, Tuning of novel fractional order fuzzy PID controller for automatic voltage regulator using grasshopper optimization algorithm, Majlesi Journal of Electrical Engineering, 15(2) (2021), 39-45. [17] S. Kumar, A. E. Matouk, H. Chaudhary, S. Kant, Control and synchronization of fractionalorder chaotic satel- lite systems using feedback and adaptive control techniques, International Journal of Adaptive Control and Signal Processing, 35(4) (2021), 484-497. [18] M. A. Labbaf Khaniki, M. Salehi Kho, M. Aliyari Shoorehdeli, Control and synchronization of chaotic spur gear system using adaptive non-singular fast terminal sliding mode controller, Transactions of the Institute of Measurement and Control, 44(14) (2022). DOI:10.1177/01423312221087578. [19] M. A. Labbaf Khaniki, M. TavakoliKakhki, Adaptive type-II fuzzy nonsingular fast terminal sliding mode controller using fractionalorder manifold for secondorder chaotic systems, Asian Journal of Control, 26(3) (2021), 2653. [20] J. Liu, C. Chen, Z. Liu, K. Jermsittiparsert, N. Ghadimi, An IGDT-based risk-involved optimal bidding strategy for hydrogen storage-based intelligent parking lot of electric vehicles, Journal of Energy Storage, 27 (2020), 101057. [21] H. F. L¨ochel, D. Eger, T. Sperlea, D. Heider, J. Wren, Deep learning on chaos game representation for proteins, Bioinformatics, 36(1) (2020), 272-279. [22] H. Medhaffar, M. Feki, N. Derbel, Stabilization of chaotic systems via fuzzy time-delayed controller approach, Iranian Journal of Fuzzy Systems, 16(2) (2019), 17-29. [23] M. Mehrpooya, N. Ghadimi, M. Marefati, S. A. Ghorbanian, Numerical investigation of a new combined energy system includes parabolic dish solar collector, Stirling engine and thermoelectric device, International Journal of Energy Research, 45(11) (2021), 16436-16455. [24] N. Miladi, H. Dimassi, S. Hadj Said, F. M’Sahli, Explicit nonlinear model predictive control tracking control based on a sliding mode observer for a quadrotor subject to disturbances, Transactions of the Institute of Measurement and Control, 42(2) (2020), 214-227. [25] M. Mir, M. Shafieezadeh, M. A. Heidari, N. Ghadimi, Application of hybrid forecast engine based intelligent algorithm and feature selection for wind signal prediction, Evolving Systems, 11(4) (2020), 559-573. [26] F. Mirzapour, M. Lakzaei, G. Varamini, M. Teimourian, N. Ghadimi, A new prediction model of battery and wind- solar output in hybrid power system, Journal of Ambient Intelligence and Humanized Computing, 10(1) (2019), 77-87. [27] S. Mondal, C. Mahanta, Adaptive second order terminal sliding mode controller for robotic manipulators, Journal of the Franklin Institute, 351(4) (2014), 2356-2377. [28] O. Solaymani Fard, R. Khalili, A. Mansoori, A novel fuzzy sliding mode control approach for chaotic systems, Iranian Journal of Fuzzy Systems, 18(6) (2021), 133-150. [29] K. Tahir, C. Belfedal, T. Allaoui, M. Dena¨ı, M. Doumi, A new sliding mode control strategy for variable-speed wind turbine power maximization, International Transactions on Electrical Energy Systems, 28(4) (2018), 1-22. [30] A. T. Vo, H. J. Kang, Adaptive neural integral full-order terminal sliding mode control for an uncertain nonlinear system, IEEE Access, 7(c) (2019), 42238-42246. [31] A. T. Vo, H. J. Kang, T. D. Le, An adaptive fuzzy terminal sliding mode control methodology for uncertain nonlinear second-order systems, 10954 LNCS. Springer International Publishing, 2018. [32] L. Xiong, P. Li, J. Wang, High-order sliding mode control of DFIG under unbalanced grid voltage conditions, International Journal of Electrical Power and Energy Systems, 117 (2020), 105608. [33] S. S. D. Xu, C. C. Chen, Z. L. Wu, Study of nonsingular fast terminal sliding-mode fault-tolerant control, IEEE Transactions on Industrial Electronics, 62(6) (2015), 3906-3913. [34] Z. Yang et al., Robust multi-objective optimal design of islanded hybrid system with renewable and diesel sources/stationary and mobile energy storage systems, Renewable and Sustainable Energy Reviews, 148 (2021), 111295. [35] Y. Yang, Y. Niu, Z. Zhang, Dynamic event-triggered sliding mode control for interval Type-2 fuzzy systems with fading channels, ISA Transactions, 110(xxxx) (2021), 53-62. [36] L. Yang, J. Yang, Nonsingular fast terminal sliding-mode control for nonlinear dynamical systems, International Journal of Robust and Nonlinear Control, 21(16) (2011), 1865-1879. [37] Y. Yu, Y. Yuan, H. Yang, H. Liu, Nonlinear sampled-data ESO-based active disturbance rejection control for networked control systems with actuator saturation, Nonlinear Dynamics, 95(2) (2019), 1415-1434. | ||
آمار تعداد مشاهده مقاله: 585 تعداد دریافت فایل اصل مقاله: 714 |