مهندسی مکانیک مدرس

مهندسی مکانیک مدرس

کنترل پایدارساز زاویه ای تحمل پذیر عیب بلادرنگ یک کوادروتور در حضور عیب عملگر

نوع مقاله : پژوهشی اصیل

نویسندگان
1 هیات علمی دانشکده مهندسی برق دانشگاه شهید بهشتی
2 دانشجوی کارشناسی، دانشکده مهندسی برق دانشگاه شهید بهشتی
3 دانشگاه شهید بهشتی
چکیده
در این مقاله، کنترل تحمل‌پذیر عیب زمان محدود برمبنای الگوریتم مد لغزشی به عنوان یک روش کنترلی مقاوم برای کنترل پایدارساز زاویه­­ای سیستم کوادروتور در حضور عیب عملگر و عدم­ قطعیت ارائه شده است. کنترل­کننده بر مبنای مدل غیرخطی کوادروتور طراحی شده و تحلیل پایداری آن برمبنای تئوری لیاپانوف انجام گرفته است. همچنین با توجه به برخی نقاط ضعف سنسورهای ممز مانند نویزپذیری نسبتاً بالا و خطای بایوس، به منظور ترکیب داده‌های سنسورها و کاهش اثرات نویز و خطا روی داده­های خروجی، فیلتر کالمن توسعه­یافته طراحی و پیاده­سازی شد. به منظور اعتبارسنجی عملکرد کنترل‌کننده، آزمایش‌های عملی بر روی یک نمونه آزمایشگاهی مقیاس کامل کوادروتور به صورت بلادرنگ پیاده­سازی شد. ارزیابی عملکرد استراتژی طراحی شده در سناریوهای مختلفی از قبیل تست در حالت بدون عیب عملگر، با وجود عیب جزئی در عملگر و عدم قطعیت در پارامترهای کوادروتور انجام شده است. نتایج آزمایشگاهی حاکی از برتری استراتژی تحمل­پذیر مد لغزشی نسبت به خطی­سازی پسخورد در حضور عیب­های مختلف و اثرات عدم قطعیت می­باشند.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Real-time Fault Tolerant Attitude Stabilization Control of a Quadrotor in the Presence of Actuator Fault

نویسندگان English

Hadi Asharioun 1
mohammad jahanshahifar 2
Ehsan Davoudi 3
Mahmood Mazare 3
1 Faculty member, school of electrical engineering shahid beheshti university
2 shahid behheshti university
3 shahid beheshti university
چکیده English

In this paper, a finite-time fault tolerant controller based on sliding mode algorithm, as a robust control method, is presented to control the attitude stabilization of the quadrotor system in the presence of actuator fault and uncertainty. The controller is designed based on the nonlinear model of a quadrotor and its stability analysis is performed according to the Lyapunov stability theorem. Also, regarding some weaknesses of MEMS sensors such as partly high noise and bias error, an extended Kalman filter is designed and implemented in order to merge sensors data and reduce the noise effect on the outputs. To validate the controller performance, the experimental tests is implemented on a full-scale quadrotor in real-time. The evaluation of the designed strategy is carried out in different scenarios, no fault in the actuators and a partial loss of effectiveness of an actuator as well as uncertainty in the quadrotor parameters. The experimental results reveal the superiority of the sliding mode tolerant strategy over feedback linearization in the presence of various faults and uncertainty effects.

کلیدواژه‌ها English

Quadrotor
Attitude stabilization
Fault tolerant control
Sliding mode control
Extended Kalman Filter
[1] L. Derafa, A. Benallegue, L. Fridman, Super twisting control algorithm for the attitude tracking of a four rotors UAV, Journal of the Franklin Institute, Vol. 349, pp. 685–699, 2012.
[2] Davoodi, E. and Rezaei, M., 2014. Dynamic modeling, simulation and control of a quadrotor using MEMS sensors’ experimental data. Modares Mechanical Engineering, 14(3), pp.175-184.
[3] Afhami, R., Fesharakifard, R., & Khosravi, M. A. (2017, October). Updating LQR control for full dynamic of a quadrotor. In 2017 5th RSI International Conference on Robotics and Mechatronics (ICRoM) (pp. 279-285). IEEE.
[4] Liu, C., Pan, J., & Chang, Y. (2016). PID and LQR trajectory tracking control for an unmanned quadrotor helicopter: Experimental studies. In 2016 35th Chinese Control Conference (CCC) (pp. 10845-10850). IEEE.
[5] Liu, H., Xi, J. (2017). Robust attitude stabilization for nonlinear quadrotor systems with uncertainties and delays. IEEE Transactions on Industrial Electronics, 64(7), 5585-5594.
[6] Dhadekar, D.D., Sanghani, P.D., Mangrulkar, K.K. and Talole, S.E., 2021. Robust control of quadrotor using uncertainty and disturbance estimation. Journal of Intelligent & Robotic Systems, 101(3), pp.1-21.
[7] Nicol, C., Macnab, C. J. B., & Ramirez-Serrano, A. (2011). Robust adaptive control of a quadrotor helicopter. Mechatronics, 21(6), 927-938
[8] Outeiro, P., Cardeira, C. and Oliveira, P., 2021. Multiple-model adaptive control architecture for a quadrotor with constant unknown mass and inertia. Aerospace Science and Technology, 117, p.106899.
[9] Wu, Y., Xie, Y. and Li, S., 2021. Parameter Adaptive Control for a Quadrotor with a Suspended Unknown Payload under External Disturbance. IEEE Access, 9, pp.139958-139967.
[10] Huo, X., Huo, M., & Karimi, H. R. (2014). Attitude stabilization control of a quadrotor UAV by using backstepping approach. Mathematical Problems in Engineering, 2014.
[11] Koksal, N., An, H. and Fidan, B., 2020. Backstepping-based adaptive control of a quadrotor UAV with guaranteed tracking performance. ISA transactions, 105, pp.98-110.
[12] Bouadi, H., Cunha, S. S., Drouin, A., & Mora-Camino, F. (2011, November). Adaptive sliding mode control for quadrotor attitude stabilization and altitude tracking. In 2011 IEEE 12th international symposium on computational intelligence and informatics (CINTI) (pp. 449-455). IEEE.
[13] Hou, Z., Lu, P. and Tu, Z., 2020. Nonsingular terminal sliding mode control for a quadrotor UAV with a total rotor failure. Aerospace Science and Technology, 98, p.105716.
[14] Mofid, O., Mobayen, S. and Wong, W.K., 2020. Adaptive terminal sliding mode control for attitude and position tracking control of quadrotor UAVs in the existence of external disturbance. IEEE Access, 9, pp.3428-3440.
[15] Chen, F., Jiang, R., Zhang, K., Jiang, B., & Tao, G. (2016). Robust backstepping sliding-mode control and observer-based fault estimation for a quadrotor UAV. IEEE Transactions on Industrial Electronics, 63(8), 5044-5056.
[16] Yang, Y., & Yan, Y. (2016). Attitude regulation for unmanned quadrotors using adaptive fuzzy gain-scheduling sliding mode control. Aerospace Science and Technology, 54, 208-217.
[17] Ryoo, Y. J. (2017). An autonomous control of fuzzy-PD controller for quadcopter. International Journal of Fuzzy Logic and Intelligent Systems, 17(2), 107-113.
[18] Sarabakha, A., Fu, C., Kayacan, E., & Kumbasar, T. (2017). Type-2 fuzzy logic controllers made even simpler: From design to deployment for UAVs. IEEE Transactions on Industrial Electronics, 65(6), 5069-5077.
[19] Rabah, M., Rohan, A., Han, Y. J.(2018). Design of fuzzy-PID controller for quadcopter trajectory-tracking. International Journal of Fuzzy Logic and Intelligent Systems, 18(3), 204-213.
[20] S. Bouabdallah, Design and control of quadrotors with application to autonomous flying, PhD Thesis, Lausanne Polytechnic University, 2007.
[21] T. Bresciani, Modelling, identification and control of a quadrotor helicopter, Master's Thesis, Department of Automatic Control, Lund University, 2008.
[22] Davoodi, E., Mazare, M. and Safarpour, P., 2017. Dynamic modeling and control of a quadrotor using nonlinear approaches based on MEMS sensors’ experimental data. Modares Mechanical Engineering, 16(10), pp.31-41.
[23] Outamazirt, F., Yan, L., Li, F. and Nemra, A., 2015, March. Solving the UAV localization problem using a smooth variable Structure filtering. In 2015 IEEE Aerospace Conference (pp. 1-12). IEEE.