کنترل بهینه مقاوم دینامیک عرضی وسایل نقلیه خودران با رویکرد برنامه‌ریزی پویای تطبیقی
محورهای موضوعی : مهندسی برق و کامپیوترمحمدرضا ساطوری 1 , ابوالحسن رزمی نیا 2 , آرش مرعشیان 3
1 - دانشگاه تهران
2 - دانشگاه خلیج فارس
3 - دانشگاه خلیج فارس بوشهر
کلید واژه: بازی مجموع- صفربرنامه‌ریزی پویای تطبیقیکنترل بهینهکنترل پیش‌گامکنترل عرضی خودرو,
چکیده مقاله :
در اين مقاله کنترل دینامیک عرضی خودرو با سرعت طولی ثابت، با استفاده از برنامه‌ریزی پویای تطبیقی، کنترل پس‌گام و نظریه بازی‌های مجموع- صفر بررسی شده است. دینامیک به صورت غیر خطی در نظر گرفته شده و گشتاور فرمان به جای زاویه فرمان به عنوان ورودی قرار گرفته است. در روش ارائه‌شده ابتدا دینامیک عرضی خودرو به همراه دینامیک نگهداری خط ادغام شده و تشکیل یک زیرسیستم می‌دهند که ورودی آن زاویه فرمان است و انحنای جاده به عنوان اغتشاش در نظر گرفته شده است. با استفاده از برنامه‌ریزی پویای تطبیقی، شبکههای عصبی و نظریه بازی‌های مجموع- صفر برای این زیرسیستم، قانون کنترل بهینه استخراج شده و سپس نتیجه به زیرسیستم دوم که همان دینامیک زاویه فرمان خودرو است اعمال می‌گردد که در آن قانون کنترل با استفاده از روش کنترل پس‌گام استخراج می‌شود. در پایان به منظور مشاهده کارایی الگوریتم ارائه‌شده، روش مذکور بر روی یک مدل، شبیه‌سازی می‌شود.
Lateral vehicle’s control with constant longitudinal velocity using adaptive dynamic programming, backstepping and zero-sum games theory is investigated in this paper. The nonlinear dynamics is considered and the steering torque is chosen to be the control input instead of the steering angle. At first, a subsystem is created by augmenting the lateral vehicle’s dynamics with lane keeping ones considering the steering angle as the control input and the road curvature as a disturbance. Utilizing adaptive dynamic programming, neural networks and zero-sum games theory, the optimal control law is obtained and then, the results exerted on the second subsystem which is the dynamics of the steering angle and a control law is captured for which using the backstepping control method. Finally, performance of the proposed algorithm is demonstrated by applying it on a typical vehicle model.
[1] K. Jo, J. Kim, D. Kim, C. Jang, and M. Sunwoo, "Development of autonomous car-part i: distributed system architecture and development process," IEEE Trans. Industrial Electronics, vol. 61, no. 12, pp. 7131-7140, Dec. 2014.
[2] K. Bimbraw, "Autonomous cars: past, present and future a review of the developments in the last century, the present scenario and the expected future of autonomous vehicle technology," in Proc. 12th Int. Conf. on Informatics in Control, Automation and Robotics, ICINCO'15, pp.191-198, Colmar, France, 21-23 Jul. 2015.
[3] R. Marino and S. Scalzi, "Nested PID steering control for lane keeping in autonomous vehicles," Control Engineering Practice, vol. 19, no. 12, pp. 1459-1467, Dec. 2011.
[4] J. Guldner, H. Tan, and S. Patwardhan, "Analysis of automatic steering control for highway vehicles with look-down lateral reference systems," Vehicle System Dynamics, vol. 26, no. 4, pp. 243-269, Jul. 1996.
[5] S. D. Cairano, H. E. Tseng, D. Bernardini, and A. Bemporad, "Vehicle yaw stability control by coordinated active front steering and differential braking in the tire sideslip angles domain," IEEE Trans. on Control Systems Technology, vol. 21, no. 4, pp. 1236-1248, Jul. 2013.
[6] S. Wu, H. Chiang, J. Perng, C. Chen, B. Wu, and T. Lee, "The heterogeneous systems integration design and implementation for lane keeping on a vehicle," IEEE Trans. Intelligent Transportation Systems, vol. 9, no. 2, pp. 246-263, Jun. 2008.
[7] S. Chaib, M. S. Netto, and S. Mammar, "H, adaptive, PID and fuzzy control: a comparison of controllers for vehicle lane keeping," in Proc. IEEE Intelligent Vehicles Symp., pp. 139-144, Parma, Italy, 14-17, Jun. 2004.
[8] S. Li, F. Gao, D. Cao, and K. Li, "Multiple-model switching control of vehicle longitudinal dynamics for platoon-level automation," IEEE Trans. on Vehicular Technology, vol. 65, no. 6, pp. 4480-4492, Jun. 2016.
[9] C. Latrach, M. Kchaou, A. E. Hajjaji, and A. Rahbi, "Robust H fuzzy networked control for vehicle lateral dynamics," in Proc. of IEEE Annual Conf. on Intelligent Transportation Systems, pp. 905-910,The Hague, Netherlands, 6-9 Oct. 2013.
[10] R. Wang, Y. Sun, M. Lin, and H. Zhang, "Research on bus roll stability control based on LQR," in Proc. of Int. Conf. on Intelligent Transportation, Big Data and Smart City, pp. 622-625,H along Bay, Vietnam, 19-20 Dec. 2015.
[11] G. Tagne, R. Talj, and A. Charara, "Higher-order sliding mode control for lateral dynamics of autonomous vehicles, with experimental validation," in Proc. of IEEE Intelligent Vehicles Symp., pp.678-683,Gold Coast, Australia, 23-26 Jun. 2013.
[12] C. Hatipoglu, U. Ozguner, and K. Redmill, "Automated lane change controller design," IEEE Trans. on Intelligent Transportation Systems, vol. 4, no. 1, pp. 13-22, Mar. 2003.
[13] J. Jiang and A. Astolfi, "A lateral control assistant for the dynamic model of vehicles subject to state constraints," in Proc. of IEEE Conf. on Decision and Control, pp.244-249, Melbourne, Australia, 12-15 Dec. 2017.
[14] P. Falcone, F. Borrelli, J. Asgari, H. Tseng, and D. Hrovat, “Predictiveactive steering control for autonomous vehicle systems,” IEEE Trans.on Control Systems Technology, vol. 15, no. 3, pp. 566–580, May 2007.
[15] S. Y. Oh, J. H. Lee, and D. H. Choi, "A new reinforcement learning vehicle control architecture for vision-based road following," IEEE Trans. on Vehicular Technology, vol. 49, no. 3, pp. 997-1005, May 2000.
[16] S. S. Shwartz, S. Shammah, and A. Shashua, Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving, arXiv: 1610.03295, 2016.
[17] R. Rajamani, Vehicle Dynamics and Control, Springer, 2005.
[18] S. Mammar and D. Koeing, "Vehicle handling improvement by active steering," Vehicle System Dynamics: International J. of Vehicle Mechanics and Mobility, vol. 38, no. 3, pp. 211-242, Aug. 2002.
[19] H. Pacejka, Tyre and Vehicle Dynamics, Butterworth-Heinemann, 2012.
[20] Z. Chu, Y. Sun, C. Wu, and N. Sepehri, "Active disturbance rejection control applied to automated steering for lane keeping in autonomous vehicles," Control Engineering Practice, vol. 74, pp. 13-21, May 2018.
[21] A. J. van der Schaft, "L2-gain analysis of nonlinear systems and nonlinear state feedback H control," IEEE Trans. on Automatic Control, vol. 37, no. 6, pp. 770-784, Jun. 1992.
[22] Q. Wei, R. Song, and P. Yan, "Data-driven zero-sum neuro-optimal control for a class of continuous-time unknown nonlinear systems with disturbance using ADP," IEEE Trans. on Neural Networks and Learning Systems, vol. 27, no. 2, pp. 444-458, Feb. 2016.
[23] F. L. Lewis, D. Vrabie, and V. L. Syrmos, Optimal Control, John Wiley & Sons, 2012.
[24] D. P. Mandic, A. I. Hanna, and M. Razaz, "A normalized gradient descent algorithm for nonlinear adaptive filters using a gradient adaptive step size," IEEE Signal Processing Letters, vol. 8, no. 11, pp. 295-297, Nov. 2001.