Robust Optimal Stable Fuzzy Controller Design for Stabilization of Electric Vehicle Speed, in Presence of Parametric Uncertainties and External Disturbances
Subject Areas : electrical and computer engineeringMohammad Veysi 1 , M. Shasadeghi 2 , M. R. Soltanpour 3
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Abstract :
In electric vehicle’s nonlinear dynamic equations, some parameters has uncertainty such as the coefficient of rolling resistance, drag coefficient, armature resistance and field winding resistance. Design of a controller that is robust in the presence of these parametric uncertainties and also in presence of external disturbances, and on the other hand simultaneously satisfies the optimality criteria, is a challenging issue. In practical applications, in addition to the above problem, the computational load of the control input should also be considered and provide a rational interaction between the controller's desirable performance and the calculations volume. In the present paper, a robust optimal stable fuzzy controller based on the parallel distributed compensation is designed, using Takagi-Sugeno fuzzy model of electric vehicle. The stabilizer feedback gains of fuzzy model, the upper bound of the uncertainties, the upper bound of the disturbances effect, and the upper bound of the cost function are obtained completely offline, through the solving of a minimization problem based on the linear matrix inequality. Therefore, the calculation volume of the control input is extremely low. This allows the practical implementation of the proposed controller. The favorable performance of the proposed controller is demonstrated in five-step simulations.
[1] م. ح. مرادی، م. رضایی مظفر و م. علیزاده پرهام، "جایابی و تعیین ظرفیت بهینه منابع انرژی تجدیدپذیر و ایستگاه شارژ خودروی برقی به صورت همزمان با استفاده از الگوریتم بهینهسازی GA-PSO،" نشریه مهندسی برق و مهندسی کامپیوتر ایران، الف- مهندسی برق، جلد 15، شماره 4- ب، صص. 268-258، زمستان 1396.
[2] C. Mi and M. Abul Masrur, Hybrid Electric Vehicles: Principles and Applications with Practical Perspectives, John Wiley & Sons, 2017.
[3] M. S. Kumar and S. T. Revankar, "Development scheme and key technology of an electric vehicle: an overview," Renewable and Sustainable Energy Reviews, vol. 70, no. 1, pp. 1266-1285, Apr. 2017.
[4] J. S. Hu, Y. Wang, H. Fujimoto, and Y. Hori, "Robust yaw stability control for in-wheel motor electric vehicles," IEEE/ASME Trans. on Mechatronics, vol. 22, no. 3, pp. 1360-1370, Jun. 2017.
[5] M. Amoozadeh, A. Raghuramu, C. N. Chuah, D. Ghosal, H. M. Zhang, J. Rowe, and K. Levitt, "Security vulnerabilities of connected vehicle streams and their impact on cooperative driving," IEEE Communications Magazine, vol. 53, no. 6, pp. 126-132, Jun. 2015.
[6] F. Naseri, E. Farjah, and T. Ghanbari, "An efficient regenerative braking system based on battery/super-capacitor for electric, hybrid, and plug-in hybrid electric vehicles with BLDC motor," IEEE Trans. on Vehicular Technology, vol. 66, no. 5, pp. 3724-3738, May 2017.
[7] J. Funke, M. Brown, S. M. Erlien, and J. C. Gerdes, "Collision avoidance and stabilization for autonomous vehicles in emergency scenarios," IEEE Trans. on Control Systems Technology, vol. 25, no. 4, pp. 1204-1216, Jul. 2017.
[8] Z. Yi and P. H. Bauer, "Optimal stochastic eco-routing solutions for electric vehicles," IEEE Trans. on Intelligent Transportation Systems, vol. 19, no. 12, pp. 3807-3817, Dec. 2018.
[9] K. H. Nam, AC Motor Control and Electrical Vehicle Applications, CRC Press, 2017.
[10] Q. Huang, C. Yong, and L. Jian, Control of Electric Vehicle, Urban Transport and Hybrid Vehicles, InTech, 2010.
[11] V. Kumar, K. P. S. Rana, and P. Mishra, "Robust speed control of hybrid electric vehicle using fractional order fuzzy PD and PI controllers in cascade control loop," J. of the Franklin Institute, vol. 353, no. 8, pp. 1713-1741, May 2016.
[12] J. Nagpal, R. Agarwal, and M. Shah, "A comparative study on different speed control methods of DC drives for electric vehicle," International J. of Research, vol. 2, no. 7, 6 pp., Jul. 2015.
[13] A. K. Yadav, P. Gaur, S. K. Jha, J. R. P. Gupta, and A. P. Mittal, "Optimal speed control of hybrid electric vehicles," J. of Power Electronics, vol. 11, no. 4, pp. 393-400, 2011.
[14] Q. Huang, Z. Huang, and H. Zhou, "Nonlinear optimal and robust speed control for a light-weighted all-electric vehicle," IET Control Theory & Applications, vol. 3, no. 4, pp. 437-444, Apr. 2009.
[15] M. H. Khooban, N. Vafamand, and T. Niknam, "T-S fuzzy model predictive speed control of electrical vehicles," ISA Trans., vol. 64, no. 5, pp. 231-240, Sept. 2016.
[16] L. Xu, J. Lu, and J. Zhang, "Speed control of pure electric vehicle based on adaptive fuzzy PID controller," in Proc. Int. Symp. for Intelligent Transportation and Smart City, ITASC'17, pp. 20-26, Shanghai, China, 19-20 May 2017.
[17] M. H. Khooban, T. Niknam, F. Blaabjerg, and M. Dehghani, "Free chattering hybrid sliding mode control for a class of non-linear systems: electric vehicles as a case study," IET Science, Measurement & Technology, vol. 10, no. 7, pp. 776-785, Oct. 2016.
[18] M. H. Khooban, O. Naghash-Almasi, T. Niknam, and M. Sha-Sadeghi, "Intelligent robust PI adaptive control strategy for speed control of EV (s)," IET Science, Measurement & Technology, vol. 10, no. 5, pp. 433-441, Aug. 2016.
[19] M. Veysi and M. R. Soltanpour, "Eliminating chattering phenomenon in sliding mode control of robot manipulators in the joint space using fuzzy logic," J. of Solid and Fluid Mechanic, vol. 2, no. 3, pp. 45-54, Fall. 2012.
[20] M. Veysi, M. R. Soltanpour, and M. H. Khooban, "A novel self-adaptive modified bat fuzzy sliding mode control of robot manipulator in presence of uncertainties in task space," Robotica, vol. 33, no. 10, pp. 2045-2064, Dec. 2015.
[21] M. Veysi and M. R. Soltanpour, "Voltage-base control of robot manipulator using adaptive fuzzy sliding mode control," International J. of Fuzzy Systems, vol. 19, no. 5, pp. 1430-1443, Oct. 2017.
[22] M. Veysi and M. R. Soltanpour, "Voltage-base control of camera stabilizer using optimal adaptive fuzzy sliding mode control," J. of Iranian Association of Electrical and Electronics Engineers, vol. 14, no. 4, pp. 23-40, Winter. 2018.
[23] T. Takagi and M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. on Systems, Man, and Cybernetics, vol. 15, no. 1, pp. 116-132, Jan./Feb. 1985.
[24] K. Tanaka, I. Takayuki, and H. O. Wang, "Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, H/sup/spl infin//control theory, and linear matrix inequalities," IEEE Trans. on Fuzzy Systems, vol. 4, no. 1, pp. 1-13, Feb. 1996.
[25] S. Kawamoto, T. Kensho, I. Atsushi, and T. Tsuneo, "An approach to stability analysis of second order fuzzy systems," in Proc. IEEE Int. Conf. on Fuzzy System, pp. 1427-1434, San Diego, CA, USA, 8-12 Mar. 1992.
[26] K. Tanaka and H. O. Wang, Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach, John Wiley & Sons, 2004.
[27] K. Tanaka, T. Taniguchi, and H. O. Wang, "Trajectory control of an articulated vehicle with triple trailers," in Proc. of the IEEE Int. Conf. on Control Applications, , vol. 2, pp. 1673-1678, Kohala Coast, HI, USA, 22-27 Aug. 1999.
[28] J. Li, H. O. Wang, L. Bushnell, and Y. Hong, "A fuzzy logic approach to optimal control of nonlinear systems," International J. of Fuzzy Systems, vol. 2, no. 3, pp. 153-163, Sept. 2000.
[29] S. Boyd and V. Lieven, Convex Optimization, Cambridge University Press, 2004.
[30] K. Tanaka, T. Taniguchi, and H. O. Wang, "Robust and optimal fuzzy control: a linear matrix inequality approach," IFAC Proceedings Volumes, vol. 32, no. 2, pp. 5380-5385, Jul. 1999.
