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Model-Free Tracking Control via Adaptive Dynamic Sliding Mode Control With Application to Robotic Systems | ||
| International Journal of Industrial Electronics Control and Optimization | ||
| مقاله 4، دوره 3، شماره 4، آذر 2020، صفحه 431-438 اصل مقاله (680.64 K) | ||
| نوع مقاله: Research Articles | ||
| شناسه دیجیتال (DOI): 10.22111/ieco.2020.31596.1207 | ||
| نویسندگان | ||
Mohammad Reza Shokoohinia  1؛ Mohammad Mehdi Fateh2
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| 1Department of Electrical and Robatic Engineering ,Shahrood University of Technology,Iran | ||
| 2Department of Electrical and Robatic Enbineering ,Shahrood University of Technology,Iran | ||
| چکیده | ||
| In this paper, a novel model-free control scheme is developed to enhance the tracking performance of robotic systems based on an adaptive dynamic sliding mode control and voltage control strategy. In the voltage control strategy, actuator dynamics have not been excluded. In other words, instead of the applied torques to the robot joints, motor voltages are computed by the control law. First, a dynamic sliding mode control is designed for the robotic system. Then, to enhance the tracking performance of the system, an adaptive mechanism is developed and integrated with the dynamic sliding mode control. Since the lumped uncertainty is unknown in practical applications, the uncertainty upper bound is necessary in the design of the dynamic sliding mode controller. Hence, the lumped uncertainty is estimated by an adaptive law. The stability of the closed-loop system is proved based on the Lyapunov stability theorem. The simulation results demonstrate the superior performance of the proposed adaptive dynamic sliding mode control strategy. | ||
| کلیدواژه‌ها | ||
| Model-Free Tracking Control؛ Adaptive Dynamic Sliding Mode Control؛ Robotic Systems؛ Voltage Control Strategy | ||
| مراجع | ||
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[1] Y. Su, , C. Zheng, and P. Mercorelli, “Robust approximate fixed-time tracking control for uncertain robot manipulators”, Mechanical Systems and Signal Processing, Vol. 135, (2020) p.106379. [2] R. Gholipour, M.M. Fateh, “Robust Control of Robotic Manipulators in the Task-Space Using an Adaptive Observer Based on Chebyshev Polynomials”, Journal of Systems Science and Complexity, (2020). https://doi.org/10.1007/s11424-020-8186-0. [3] M. Bekrani, M. Heydari, and S.T. Behrooz, “An Adaptive Control Method Based on Interval Fuzzy Sliding Mode for Direct Matrix Converters”, International Journal of Industrial Electronics, Control and Optimization, Vol. 3, No. 2, (2020), 159-171. [4] S.H. Shahalami, and F. Rajab Nejad, “Design of Adaptive Back-Stepping Controller for Chaos Control in Boost Converter and Controller Coefficients Optimization Using CHPSO Algorithm”, International Journal of Industrial Electronics, Control and Optimization. Vol. 3, No.3, (2020), 249-257. [5] A. Haqshenas M, M.M. Fateh, and S.M. Ahmadi, “Adaptive control of electrically‐driven nonholonomic wheeled mobile robots: Taylor series‐based approach with guaranteed asymptotic stability”, International Journal of Adaptive Control and Signal Processing, (2020), https://doi.org/10.1002/acs.3104. [6] S.M. Ahmadi, and M.M. Fateh, “Task-space control of robots using an adaptive Taylor series uncertainty estimator”, International Journal of Control, Vol. 92, No. 9, (2019), 2159-2169. [7] M. Van, S.S. Ge and H. Ren, “Finite time fault tolerant control for robot manipulators using time delay estimation and continuous nonsingular fast terminal sliding mode control”, IEEE transactions on cybernetics, Vol. 47, No. 7, (2017), 1681-1693. [8] R. Gholipour, A. Khosravi and H. Mojallali, “Multi-objective optimal backstepping controller design for chaos control in a rod-type plasma torch system using Bees Algorithm”, Applied Mathematical Modelling, Vol. 39, No. 15, (2015), 4432-4444. [9] S. Park and S. Rahmdel, “A new fuzzy sliding mode controller with auto-adjustable saturation boundary layers implemented on vehicle suspension”, International Journal of Engineering-Transactions C: Aspects, Vol. 26, No. 12, (2013), 1401-1410. [10] Y. Zhao, P. Huang and F. Zhang, “Dynamic modeling and Super-Twisting Sliding Mode Control for Tethered Space Robot”, Acta Astronautica, Vol. 143, (2018), 310-321. [11] G. Chen, B. Jin, Y. Chen, “Nonsingular fast terminal sliding mode posture control for six-legged walking robots with redundant actuation”, Mechatronics, Vol. 50, (2018), 1-15. [12] F.J. Lin, S.Y. Chen K.K. Shyu, “Robust dynamic sliding-mode control using adaptive RENN for magnetic levitation system”, IEEE Transactions on Neural Networks, Vol. 20, No. 6, (2009), 938-951. [13] S.Y. Chen, S.S. Gong, “Speed tracking control of pneumatic motor servo systems using observation-based adaptive dynamic sliding-mode control”, Mechanical Systems and Signal Processing, Vol. 94, (2017) , 111-128. [14] S. Wen, M.Z. Chen, Z. Zeng, X. Yu and T. Huang, “Fuzzy control for uncertain vehicle active suspension systems via dynamic sliding-mode approach”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 47, No. 1, (2017), 24-32. [15] S. Khorashadizadeh and M.M. Fateh, “Uncertainty estimation in robust tracking control of robot manipulators using the Fourier series expansion”, Robotica, Vol. 35, No. 2, (2017), 310-336. [16] S. Khorashadizadeh and M.H. Majidi, “Chaos synchronization using the Fourier series expansion with application to secure communications”, AEU-International Journal of Electronics and Communications, Vol. 82, (2017), 37-44. [17] R. Gholipour and M.M. Fateh, “Adaptive task-space control of robot manipulators using the Fourier series expansion without task-space velocity measurements”, Measurement, Vol. 123, (2018), 285-292. [18] M.R. Shokoohinia and M.M. Fateh, “Robust dynamic sliding mode control of robot manipulators using the Fourier series expansion”, Transactions of the Institute of Measurement and Control, https://doi.org/10.1177/0142331218802357, 2018. [19] M.R.Shokoohinia, M.M. Fateh, and R. Gholipour, “Design of an adaptive dynamic sliding mode control approach for robotic systems via uncertainty estimators with exponential convergence rate”, SN Applied Sciences, Vol. 2, No. 2, (2020), 1-11. [20] M.M. Fateh and M. Sadeghijaleh, “Voltage control strategy for direct-drive robots driven by permanent magnet synchronous motors”, International Journal of Engineering-Transactions B: Applications, Vol. 28, No. 5, (2015), 709-716. [21] M.M. Fateh and A. Arab, “Robust control of a wheeled mobile robot by voltage control strategy”, Nonlinear Dynamics, Vol. 79, No. 1, (2015), 335-348. [22] S. Khorashadizadeh and M.M. Fateh, “Robust task-space control of robot manipulators using Legendre polynomials for uncertainty estimation”, Nonlinear Dynamics, Vol. 79, No. 2, (2015), 1151-1161. [23] R. Gholipour and M.M. Fateh, “Observer-based robust task-space control of robot manipulators using Legendre polynomial”, In Electrical Engineering (ICEE), 2017 Iranian Conference on (pp. 766-771). IEEE, (2017). [24] M.W. Spong, S. Hutchinson and M. Vidyasagar, “Robot modeling and control”, (Vol. 3, pp. 187-227). New York: Wiley, (2006). [25] F.J. Lin, S.G. Chen and I.F. Sun, “Intelligent sliding-mode position control using recurrent wavelet fuzzy neural network for electrical power steering system” International journal of fuzzy systems, Vol. 19, No. 5, (2017), 1344-1361. [26] F.J. Lin, S.G. Chen and I.F. Sun, “Adaptive backstepping control of six‐phase PMSM using functional link radial basis function network uncertainty observer”, Asian Journal of Control, Vol. 19, No. 6, (2017), 2255-2269. [27] R. Gholipour and M.M. Fateh, “Designing a Robust Control Scheme for Robotic Systems with an Adaptive Observer”, International Journal of Engineering, Transactions B: Applications, Vol. 32, No. 2, (2019), 270-276. [28] F. Lin, S. Chen and C. Hsu, , “Intelligent Backstepping Control Using Recurrent Feature Selection Fuzzy Neural Network for Synchronous Reluctance Motor Position Servo Drive System”, IEEE Transactions on Fuzzy Systems, Vol. 27, No. 3, (2019), 413-427. [29] J.J.E. Slotine and W. Li, “Applied nonlinear control”, (Vol. 199, No. 1). Englewood Cliffs, NJ: Prentice hall, (1991). [30] M.M. Fateh and S. Khorashadizadeh, “Robust control of electrically driven robots by adaptive fuzzy estimation of uncertainty”, Nonlinear Dynamics, Vol. 69, No. 3, (2012), 1465-1477. [31] E. Salahshour, M. Malekzadeh, R. Gholipour, and S.Khorashadizadeh, “Designing multi-layer quantum neural network controller for chaos control of rod-type plasma torch system using improved particle swarm optimization”, Evolving Systems, Vol. 10, No. 3, (2019), 317-331. [32] R. Gholipour, J. Addeh, H. Mojallali, and A. Khosravi, “Multi-objective evolutionary optimization of PID controller by chaotic particle swarm optimization”, International Journal of Computer and Electrical Engineering, Vol. 4, No. 6, (2012), 833-838. [33] R. Gholipour, , H. Mojallali, and S.M.K., Akhlaghi, “A Novel Particle Swarm Optimization with Passive Congregation via Chaotic Sequences”, International Journal of Computer and Electrical Engineering, Vol. 4, No. 6, (2012), 809-815. [34] R. Gholipour, A. Khosravi, and H. Mojallali, “Suppression of chaotic behavior in duffing-holmes system using back-stepping controller optimized by unified particle swarm optimization algorithm”, International Journal of Engineering, Transactions B: Applications, Vol. 26, No. 11, (2013), 1299-1306. [35] R. Gholipour, A. Khosravi, and H. Mojallali, “Parameter estimation of loranz chaotic dynamic system using bees algorithm”, International Journal of Engineering, Transactions C: Aspects, Vol. 26, No. 3, (2013), 257-262. [36] N. Pourmousa, S.M. Ebrahimi, M. Malekzadeh, and M. Alizadeh, “Parameter estimation of photovoltaic cells using improved Lozi map based chaotic optimization Algorithm”, Solar Energy, Vol. 180, (2019), 180-191. [37] J. Farzaneh, , R. Keypour, and A. Karsaz, “A novel fast maximum power point tracking for a PV system using hybrid PSO-ANFIS algorithm under partial shading conditions”, International Journal of Industrial Electronics, Control and Optimization, Vol. 2, No. 1, (2019), 47-58. [38] H. Moradi CheshmehBeigi, and A. Mohamadi, “Torque Ripple Minimization in SRM Based on Advanced Torque Sharing Function Modified by Genetic Algorithm Combined with Fuzzy PSO”, International Journal of Industrial Electronics, Control and Optimization, Vol. 1, No. 1, (2018), 71-80. [39] M. Dehghani, Z. Montazeri, O.P. Malik, A. Ehsanifar, and A. Dehghani, “OSA: Orientation Search Algorithm”, International Journal of Industrial Electronics, Control and Optimization, Vol. 2, No. 2, (2019), 99-112. [40] N. Ghaffarzadeh, and H. Faramarzi, “A new whale optimization algorithm based fault location method by focusing on dispersed model of the transmission line”, International Journal of Industrial Electronics, Control and Optimization, (2020), doi: 10.22111/ieco.2020.32027.1218. [41] M.E.B. Aguilar, D.V. Coury, R. Reginatto, and R.M. Monaro, “Multi-objective PSO applied to PI control of DFIG wind turbine under electrical fault conditions”, Electric Power Systems Research, Vol. 180, (2020), p.106081, https://doi.org/10.1016/j.epsr.2019.106081. [42] Z. Hu, , X. Xu, , Q. Su, , H. Zhu, and J. Guo, “Grey prediction evolution algorithm for global optimization”, Applied Mathematical Modelling, Vol. 79, (2020), 145-160. [43] M. Kohler, M.M. Vellasco, and R. Tanscheit, “PSO+: A new particle swarm optimization algorithm for constrained problems”, Applied Soft Computing, Vol. 85, (2019), p.105865, https://doi.org/10.1016/j.asoc.2019.105865. [44] A. Taheri, and N. Asgari, “Sliding Mode Control of LLC Resonant DC-DC Converter for Wide Output Voltage Range in Battery Charging”, International Journal of Industrial Electronics, Control and Optimization, Vol. 2, No. 2, (2019), 127-136. | ||
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