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Adaptive fuzzy sliding mode and indirect radial-basis-function neural network controller for trajectory tracking control of a car-like robot | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 14، دوره 10، شماره 1، بهمن 2019، صفحه 153-166 اصل مقاله (829 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2019.4060 | ||
| نویسندگان | ||
| Masoud Shirzadeh1؛ Abdollah Amirkhani* 2؛ Mohammad H. Shojaeefard3؛ Hamid Behroozi4 | ||
| 1Dept. of Electrical Engineering, Amirkabir University of Technology, Tehran 15875-4413, Iran | ||
| 2Dept. of Automotive Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran | ||
| 3Department of Automotive Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran | ||
| 4Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran | ||
| تاریخ دریافت: 24 اردیبهشت 1398، تاریخ بازنگری: 03 مرداد 1398، تاریخ پذیرش: 19 مهر 1398 | ||
| چکیده | ||
| The ever-growing use of various vehicles for transportation, on the one hand, and the statistics of soaring road accidents resulting from human error, on the other hand, reminds us of the necessity to conduct more extensive research on the design, manufacturing and control of driver-less intelligent vehicles. For the automatic control of an autonomous vehicle, we need its dynamic model, which, due to the existing uncertainties, the unmodeled dynamics and the performed simplifications, is impossible to determine exactly. Add to this, the external disturbances that exist on the movement path. In this paper, two adaptive controllers have been proposed for tracking the trajectory of a car-like robot. The first controller includes an indirect radial-basis-function neural network whose parameters are updated online via gradient descent. The second controller is adaptively updated online by means of fuzzy logic. The proposed controller includes a nonlinear robust section that uses the sliding mode method and a fuzzy logic section that updates some of the nonlinear control parameters online. The fuzzy logic system has been designed to deal with the chattering problem in the controller of a car-like robot. In both controllers, the parameters have been determined by means of genetic algorithm. The obtained results indicate that even with the consideration of un-ideal effects such as uncertainties and external disturbances, the proposed controller has been able to perform successfully. | ||
| کلیدواژهها | ||
| dynamic model؛ trajectory tracking؛ car-like robot؛ sliding mode؛ fuzzy logic system | ||
| مراجع | ||
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[1] L.D. Burns, A vision of our transport future, Nature 497 (2013) 181–182. [2] If autonomous vehicles rule the world: from horseless to driverless, Economist 2015. [3] S.A. Cohen and D. Hopkins, Autonomous vehicles and the future of urban tourism, Ann. Tourism Res. 74 (2019) 33–42. [4] T. Litman, Autonomous vehicle implementation predictions, Victoria Transport Policy Institute, 2015. [5] C. Gkartzonikas and K. Gkritza, What have we learned? A review of stated preference and choice studies on autonomous vehicles, Transport. Res. Part C: Emerg. Technol. 98 (2019) 323–337. [6] World Health Organization (2015), ”The top 10 causes of death,” 2016. [Online]. Available: http://www.who.int/en/news-room/factsheets/detail/the-top-10-causes-of-death. [Accessed November 2018]. [7] P. Thomas, A. Morris, R. Talbot, and H. Fagerlind, Identifying the causes of road crashes in Europe, Ann. Adv. Automotive Med. 57 (2013) 13–22. [8] R. Fierro and F.L. Lewis, Control of a nonholonomic mobile robot: backstepping kinematics into dynamics, 34th IEEE Conf. Decision Control, 1995, pp. 3805–3810. [9] J. Funke, M. Brown, S.M. Erlien, and J.C. Gerdes, Collision avoidance and stabilization for autonomous vehicles in emergency scenarios, IEEE Trans. Control Syst. Technol. 25 (2017) 1204–1216. [10] B.S. Park, S.J. Yoo, J.B. Park, and Y.H. Choi, A simple adaptive control approach for trajectory tracking of electrically driven nonholonomic mobile robots, IEEE Trans. Control Syst, 18 (2010) 1199-1206. [11] D. Chwa, Tracking control of differential-drive wheeled mobile robots using a backstepping-like feedback linearization, IEEE Trans. Syst. Ma Cyber 40 (2010) 1285–1295. [12] R. Murray, Z. Li, and S. Sastry, A Mathematical Introduction to Robotic Manipulation, CRC Press, Boca Raton, 1994. [13] Generic 4-Wheeled Vehicle with Independent Suspension, Maplesoft, [Online]. Available:https://www.maplesoft.com/products/maplesim/mod elgallery/detail.aspx?id=60. [14] F. Pourboghrat and M.P. Karlsson, Adaptive control of dynamic mobile robots with nonholonomic constraints, Comput. Electri. Engin. 28 (2002) 241–253. [15] G. Klancar, A. Zdesar, S. Blazic, and I. Skrjanc, Wheeled Mobile Robotics: From Fundamentals Towards Autonomous Systems, Elsevier Science, 2017. [16] J. Liu, Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: Design, Analysis and Matlab Simulation, Springer, 2013. [17] O. Mohareri, R. Dhaouadi, and A.B. Rad, Indirect adaptive tracking control of a nonholonomic mobile robot via neural networks, Neurocomputing 88 (2012) 54–66. [18] J.-J.E. Slotine, and W. Li, Applied Nonlinear Control, Prentice-Hall, Englewood Cliffs, NJ., 1991. [19] N. Noguchi and H. Terao, Path planning of an agricultural mobile robot by neural network and genetic algorithm, Comput. Electron. Agricul. 18 (1997) 187–204. [20] J. Liu and X.Wang, Fuzzy Sliding Mode Control, Advanced sliding mode control for mechanical systems, Springer, Berlin, 2011, pp. 233–279. | ||
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