کنترل بهینه زاویه اوج هواپیما با استفاده از PID و کنترل مد لغزشی مبتنی بر الگوریتم PSO

نوع مقاله : گرایش دینامیک، ارتعاشات و کنترل

نویسندگان

1 موسسه آموزش عالی احرار رشت

2 دانشگاه گیلان

3 باشگاه پژوهشگران جوان و نخبگان، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران

چکیده

مدل­سازی و کنترل هواپیمای بدون سرنشین بی­شک یکی از حوزه­های فعال در مهندسی کنترل به­شمار می­آید. با توجه به دینامیک غیرخطی، متغیر با زمان و عدم قطعیت­های ساختاری و پارامتری اجسام پرنده، مسئله کنترل پرواز در طراحی اجسام پرنده موضوعی نسبتا پیچیده و مهم محسوب می­شود. یکی از پرکاربردترین روش­های کنترلی مقاوم در این حوزه، روش کنترل مد لغزشی می­باشد. از این­رو در این مقاله، طراحی، شبیه­سازی و تحلیل دو کنترل­کننده، PID و مد لغزشی جهت کنترل بهینه زاویه اوج یک هواپیمای بدون سرنشین ارائه شده است. در ابتدا به­منظور مدل­سازی دینامیکی مدل ریاضی مناسبی جهت توصیف حرکت طولی هواپیما ارائه شده است، در ادامه، یک    کنترل­کننده مد لغزشی مقاوم بر مبنای الگوریتم بهینه­سازی ازدحام ذرات به­منظور کنترل زاویه اوج هواپیما در حضور نامعینی­ها و اغتشاشات خارجی طراحی شده است، آن­چنان­که پارامترهای بهینه با هدف به حداقل رساندن سیگنال کنترلی و خطای ردیابی تعیین می­شوند. سپس، کیفیت عملکرد روش پیشنهادی با نتایج حاصل از کنترل­کننده بهینه PID از نظر مشخصات پاسخ گذرا مقایسه شده است در نهایت، نتایج   شبیه­سازی نشان دادند که کنترل‌کننده مدل لغزشی پیشنهادی ضمن کاهش میزان فراجهش پاسخ سامانه، رفتار مقاوم­تری نسبت به کنترل‌کننده PID جهت کنترل زاویه اوج هواپیما دارد.

کلیدواژه‌ها


عنوان مقاله [English]

Optimal Control of an Aircraft Pitch Angle using PID and Sliding Mode Control Based on PSO Algorithm

نویسندگان [English]

  • milad barbastegan 1
  • ahmad bagheri 2
  • elham yazdani 3
  • saeed nezamivand chegini 2
1 moasese amoozesh ali ahrar rasht
2 gilan
3 azad ghazvin
چکیده [English]

Modeling and control of Unmanned Aerial Vehicle is undoubtedly one of the most active areas in the field of control engineering. The characteristics of aerial vehicles such as nonlinear dynamics, time variability and the structural and parametric uncertainties make flight control issue relatively a complex and important subject. One of the widely used methods in this area is sliding mode control technique. This paper proposes the design, the simulation, and the analysis of two controllers namely PID and sliding mode in order to optimally control the pitch angle of an unmanned aircraft. Initially, in order to model the dynamic system, an appropriate mathematical model is presented to describe the longitudinal motion of aircraft. Subsequently, a robust sliding mode controller is designed using particle swarm optimization (PSO) algorithm to control the pitch angle of an aircraft against the uncertainties and the external disturbances. The optimal parameters are determined by minimizing both the control signal and tracking error. Then, the performance quality of the proposed method was compared with the results of the optimal PID controller in terms of transient response characteristics. Finally, simulation results indicated that the proposed sliding mode controller can reduce the overshoot of system response and yield more robust performance than PID for the control of pitch angle.

کلیدواژه‌ها [English]

  • Unmanned Aircraft
  • Proportional Integral Derivative Control
  • Sliding Mode Control
  • Particle Swarm Optimization
  1.  Nelson, R. C. “Flight Stability and Automatic Control”, WCB/McGraw Hill, New York, 1998.##
  2. Redling, T. J. “Integrated Flight Control Systems: a New Paradigm for an Old Art” Aerospace and Electronic Systems Magazine, IEEE. Vol. 16, No. 5, pp. 17-22, 2001.##
  3. Stojiljkovic, B., Vasov, L., Mitrovic, C., and Cvetkovic, D. “The Application of the Root Locus Method for the Design of Pitch Controller of an F-104A Aircraft”, Strojniški vestnik, Vol. 5, No. 9, pp. 555-60, 2009.##
  4. Boskoski, P., Mileva, B., and Deskoski S. “Auto Landing Using Fuzzy Logic”, 6th International PhD Workshop on Systems and Control, Izola, Slovenia, 2005.##
  5. Choe, D., Lee, Y., and Cho, S. “Nonlinear Pitch Autopilot Design with Local Lines Linear System Analysis”, Proc. Int. Conf. Automatic Control and Systems Engineering, Cario, Egypt, 2005.[M1] [U2] ##
  6. Robert, E. A. “Reconfiguration Sscheme for Flight Control Adaptation to Fixed Position Actuator Failures”, PhD Dissertation, University of Florida, 2003.##
  7. Xie, Z. Y. and Xia, M. Fu. “Robust Trajectory Tracking Method for UAV Using Nonlinear Dynamic Inversion”, Proc. IEEE 5th Int. Conf.  Cybern. Intell. Syst, Qingdao, China, 2011.[M3] [U4] ##
  8. Reiner, J., Balas, G. J., and Garrard W. L. “Flight Control Design Using Robust Dynamic Inversion and Time-Scale Separation”, J.  Automatica. Vol. 32, No. 11, pp. 1493-1504, 1996.##
  9. Xu, H., Mirmirani, M. D., and Ioannou, P. A. “Adaptive Sliding Mode Control Design for a Hypersonic Flight Vehicle”, J. Guid. Control Dynam. Vol. 27, No. 5, pp. 829-838, 2004.[M5] [U6] ##

10. Ashari, A. E., and Khaloozadeh, H. “Substitute Sliding-Mode Controller Design for Aircraft Control”, Proc. IEEE Int. Conf of Industrial Technology, Mumbai, India, 2006.[M7] [U8] ##

11. Ure, N. K. and Inalhan, G. “Design of Higher Order Sliding Mode Control Laws for a Multi Modal Agile Maneuvering UCAV”, Proc. IEEE Int. Conf  ofSystems and Control in Aerospace and Astronautics, Shenzhen, China, 2008.[M9] [U10] ##

12. Hao, C., Beiji, Z., Haoyu, Z. and Lili, P. “SlidingMode Controller Design for an Aircraft Pitch Rate Track System”, Proc. IEEE Int. Conf of Networking, Sensing and Control, Hainan, China, 2008.[M11] [U12] ##

13. Promtun, E., and Seshagiri, S. “Sliding Mode Control of Pitch-Rate of an F-16 Aircraft”, J. Aerospace and Mecanical Engineering. Vol.3, No. 9,  pp. 1108-1114, 2009.[M13] [U14] ##

14. Bahrami, M., Ebrahimi, B. and Roshanian, J. “Dynamic Sliding Mode Autopilot for Nonlinear Non-Minimum Phases Flight Vehicle”, Trans. Jpn. Soc. Aeronaut. Space Sci. Vol. 51, No. 174,  pp. 236–243, 2009.[M15] [U16] ##

15. Luo, X. Y., Guan, X. P. “Chattering Reduction Adaptive Sliding-Mode Control for Nonlinear Time-Delay systems”, Control and Decision. Vol. 24, No. 9, pp. 1429–143, 2009.##

16. Zhang, L., Su, Y., and Liang, Y. “HPSO-Based Fuzzy Neural Network Control for AUV”, J. Control Theory and Applications. Vol. 6, No. 3, pp. 322–326, 2008.##

17. Pan, L. X., Wang, L. L. “Robust Control Based on Feedback Linearization for Roll Stabilizing of Autonomous Underwater Vehicle Under Wave Disturbances”, J. China Ocean Engineering. Vol. 25, No. 2, pp. 251–263, 2011.##

18. Jiang and M. Kamel. “Pitch Control of an Aircraft with Aggregated Reinforcement Learning Algorithms”; Proc. Int. Conf. Neural Networks, USA, 2007.##

19. Manocha, A. and Sharma A. “Three Axis Aircraft Autopilot Control Using Genetic Algorithms: An Experimental Study”; Proc. IEE Int. Conf, Advanced Computing, Patiala, India, 2009.##

20. Chugh, V. and Ohri, J. “GA Tuned LQR and PID Controller for Aircraft Pitch Control”; Proc. IEE  Int. Conf., Power Electronics (IICPE, India, 2014.##

21. Somakumar, R., and Chandrasechar, J. “Neural Network Based Nonlinear Inverse Dynamics for Flight Controller Design”, Proc. IEE Int. Conf of Control Applications, Trieste, Italy, 1998.[M17] [U18] ##

22. Moon, G., and Kim, Y. “Variable Structure Control with Optimized Sliding Surface for Aircraft Control System”, IAA Guidance, Navigation, and Control Conference, Providence, Rhode Island, USA, 2004.##

23. Pazooki, A., Tag, A., and Izadjoo, R. “ Control of Pitch Angle Using Fuzzy and PD Controllers”; Proc. Int. Conf. Electrical Eng. Iran, 2011, (In Pesian).##

24. Ting, E., and Ayoubi, M. A. “Optimized Fuzzy-Proportional/Integral/Derivative Controller for Aircraft Pitch Control”, Int. J. Aerospace Systems, Vol. 10, No. 8, pp. 414-429, 2013.##

25. Kennedy, J., and Eberhart, R. C. “Particle Swarm Optimization”, in Proc of the 1995 IEEE ICEC, IEEE Publ., Piscataway, NJ, pp. 1942-1948, 1995.##

26. Eberhart, R. C., and Kennedy, J. “A NewOptimizer Using Particle Swarm Theory”, in Proc of the Sixth International Symposium on Micro Machine and Human Science, IEEE Publ., Piscataway, pp. 39-43, 1995.##

27. Samanta, B., and Nataraj, C. “Design of Intelligent Ship Autopilots Using Particle Swarm Optimization”, in Proc of the Swarm Intelligence Symposium, IEEE Publ., Piscataway, pp. 1-7, 2008.##

28. Yu, G. R., Huang, J. W., and Chen, Y. H., “Optimal Fuzzy Control of Piezoelectric Systems Based on Hybird Taguchi Method and Particle Swarm Optimization”; Proc. Int. Conf. Systems, Man, and Cybernetics, IEEE Publ., Piscataway, 2009.##

29. Omizegba, E. E., and Adebay, G. E. “Optimizing Fuzzy Membership Functions Using Particle Swarm Algorithm”, Proc. IEEE Int. Conf. Systems, Man, and Cybernetics, IEEE Publ., Piscataway, 2009.##

30. Ayoubi, M. A., and Ting, E. “Optimized Fuzzy Proportional/Integral/Derivative Controller for Aircraft Pitch Control”, J. Aerospace Information Systems. Vol. 10, No. 8, pp. 411–429, 2013.##

31. Sangchul, L., Kwangjin, K., and Youdan, K. “A Sliding Mode Control with Optimized Sliding Surface for Aircraft Pitch Axis Control System”, Trans. Japan Soc. Aero. Space Sci. Vol. 55, No. 2, pp. 94–98, 2012.##

32. Welong, S. “Model Reference Adaptive Integral-type Sliding Mode Control Design for Class of Uncertain Systems”; Proc. Conf. Intelligent Control and Automation, IEEE Publ, Vol. 150, No. 8, pp. 383–388, China, 2006.##

33. Costin, E. “Integral Sliding-Mode Control With Applications to Aircraft Dynamics”, Applied Mechanics and Materials”, Vol. 245, No. 8, pp. 340-345, 2013.##

34. Mirmirani, Xu. H. and Ioannou, P. A. “Adaptive Sliding Mode Control Design for a Hypersonic Flight Vehicle”, Guid. Control Dynam. Vol. 27, No. 8, pp. 829–838, 2004.##

35. Lingling, W., Huali, W., Lili, Y., and Junwei, L. “A Simple Sliding Mode Control for Saucer-Shaped Aircraft”, Proc. Int. Conf.  Machinery, Materials and Computing Technology (ICMMCT), Beijing, China, 2017.[M19] [U20] ##

36. Jamoussi, K., Chrifi-Alaoui, L., Benderradji, H., E Hajjaji, A., and Ouali, M. “Robust Sliding Mode Control Using Adaptive Switching Gain for Induction Motors”, J. Automation and Computing. Vol. 10, No. 4, pp. 303–311, 2013.##

Degaki, T., and Suzuki, S. “Sliding Mode Control Application for Two- Dimensional Active Flutter Suppression”, Trans. Japan Soc. Aero. Space Sci. Vol. 43, No. 2, pp. 175-181, 2001.##