Volume 19, Issue 12 (December 2019)                   Modares Mechanical Engineering 2019, 19(12): 2895-2905 | Back to browse issues page

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Navabi M, Hossini S. Adaptive-Fuzzy Controller Design Based on the EULERINT Criterion for Satellit. Modares Mechanical Engineering 2019; 19 (12) :2895-2905
URL: http://mme.modares.ac.ir/article-15-18050-en.html
1- New Technologies Engineering Faculty, Shahid Beheshti University, Tehran, Iran , m_navabi@sbu.ac.ir
2- New Technologies Engineering Faculty, Shahid Beheshti University, Tehran, Iran
Abstract:   (5722 Views)

Maneuvering with the highest speed and low power has always been a challenge to design a satellite and spacecraft control system. In this paper, apart from the complexity of modeling actuators, different control methods were used to control the satellite attitude in the presence of uncertainties and disturbances in satellites, in order to obtain an explicit response to minimize the EULERINT criterion. The EULERINT criterion is the integral of the Euler angles between the body axes and the target around Euler's axis over time and somehow interprets the speed of the satellite maneuver in the three control axes. First, using the proportional-derivative control, the comparison of the EULERINT criterion in the application of different kinematic representations (Euler, quaternion vectors and direction cosine matrix equations) in linear and nonlinear models of the satellite was carried out. Then the comparison of the EULERINT criterion between the different methods was presented using the quaternion kinematic, which has the least amount of EULERINT, through changing the proportional-derivative controller to linear-quadratic regulator controllers, pole placement, adaptive, fuzzy, and adaptive-fuzzy. The comparison was conducted to achieve the best control method in terms of frequency response, the lowest EULERINT and the least control effort to control the attitude of the satellite in the presence of disturbance and uncertainty.
 

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Article Type: Original Research | Subject: Control
Received: 2018/04/21 | Accepted: 2019/05/26 | Published: 2019/12/21

References
1. 1- Navabi M, Akhlomadi MR. Nonlinear optimal control of space docking and Rendezvous problem. Journal of Space Science and Technology. 2015;8(3):27-40. [Persian] [Link]
2. Navabi M, Nasiri N. Modeling and simulating the earth's magnetic field utilizing the 10th generation of IGRF and comparison the linear and nonlinear transformation in order to use in satellite attitude control. Journal of Space Science and Technology. 2010;3(4):45-52. [Persian] [Link]
3. Navabi M, Hosseini M. Modeling and spacecraft attitude control using reaction wheel with feedback linearization, its performance study subject to power and EULERINT. Modares Mechanical Engineering. 2018;18(1):51-61. [Persian] [Link]
4. Sidi MJ. Spacecraft dynamics and control: a practical engineering approach. Cambridge: Cambridge University Press‎; 1997. [Link] [DOI:10.1017/CBO9780511815652]
5. Navabi M, Tavana M, Mirzaei HR. Attitude control of spacecraft by state dependent Riccati equation and power series expansion of Riccati methods. Journal of Space Science and Technology. 2014;7(4):39-49. [Persian] [Link]
6. Aydogan A, Hasturk O. Adaptive LQR stabilization control of reaction wheel for satellite systems. Proceedings of the 14th International Conference on Control, Automation. Robotics and Vision (ICARCV); 2016 Nov 13-15; Phuket, Thailand. IEEE; 2017. p. 1-6. [Link] [DOI:10.1109/ICARCV.2016.7838849]
7. Alsharif MA, Arslantas YE, Hölzel MS. A comparison between advanced model-free PID and model-based LQI attitude control of a quadcopter using asynchronous android flight data. Proceedings of the 25th Mediterranean Conference on Control and Automation (MED); 2017 July 3-6; Valletta, Malta. IEEE; 2017. p. 1023-1028. [Link] [DOI:10.1109/MED.2017.7984252]
8. Zeng Y, Jiang Q, Liu Q, Jing H. PID vs. MRAC control techniques applied to a quadrotor's attitude. Proceedings of the 2nd International Conference on Instrumentation, Measurement, Computer, Communication and Control; 2012 Dec 8-10; Harbin, China. IEEE; 2013. p. 1086-1089. [Link]
9. Navabi M, Soleymanpour S. Standard and robust backstepping control of a spacecraft with inertial uncertainty. Modares Mechanical Engineering. 2015;14(16):112-124. [Persian] [Link]
10. Navabi M, Soleymanpour S. Command Filtered modular adaptive backstepping attitude control spacecraft in presence of disturbance torque. Modares Mechanical Engineering. 2015;15(7):285-296. [Persian] [Link]
11. Chen F, Jiang R, Zhang K, Jiang B, Tao G. Robust backstepping sliding-mode control and observer-based fault estimation for a quadrotor UAV. IEEE Transactions on Industrial Electronics. 2016;63(8):5044-5056. [Link] [DOI:10.1109/TIE.2016.2552151]
12. Altuğ E, Ostrowski JP, Taylor CJ. Control of a quadrotor helicopter using dual camera visual feedback. The International Journal of Robotics Research. 2005;24(5):329-341. [Link] [DOI:10.1177/0278364905053804]
13. Navabi M, Mirzaei H. Robust optimal adaptive trajectory tracking control of quadrotor helicopter. Latin American Journal of Solids and Structures. 2017;14(6):1040-1063. [Link] [DOI:10.1590/1679-78253595]
14. ‎‎Zhao ZY‎,‎ Tomizuka M,‎ Isaka S‎. ‎Fuzzy gain scheduling of PID controllers‎. IEEE Transactions on Systems, Man, and Cybernetics. 1993;23(5):‎1392-1398‎. [Link] [DOI:10.1109/21.260670]
15. Zhang X, Zeng M, Yu X. Fuzzy control of rigid spacecraft attitude maneuver with decay rate and input constraints. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. 2011;19(6):1033-1046. [Link] [DOI:10.1142/S0218488511007453]
16. Barbosa GC, Bertolin R, González PJ, Neto ABG, Silvestre FJ. Fuzzy gain-scheduling applied for a very flexible aircraft. Proceedings of the Guidance, Navigation, and Control Conference; 2018 Jan 8-12; Kissimmee, Florida. [Link] [DOI:10.2514/6.2018-1868]
17. ‎MacKunis W‎, ‎‎Dupree K‎, ‎Fitz-Coy N‎, ‎Dixon WE. Adaptive satellite attitude control in the presence of inertia and CMG gimbal friction uncertainties. The Journal of the Astronautical Sciences‎. 2008;56(1):121-134‎.‎‎‎ [Link] [DOI:10.1007/BF03256544]
18. ‎‎ ‎Wang LX. Stable adaptive fuzzy control of nonlinear systems. IEEE Transactions on Fuzzy Systems. 1993;1(2):146-155. [Link] [DOI:10.1109/91.227383]
19. Chen B, Liu X, Liu K, Lin C. Direct adaptive fuzzy control of nonlinear strict-feedback systems. Automatica. 2009;45(6):1530-1535. [Link] [DOI:10.1016/j.automatica.2009.02.025]
20. Navabi M, Hosseini MR. Investigation in to the effect of kinematic of the space craft attitude control using feedback linearization method. Journal of Space Science and Technology. 2018;11(1):59-71. [Persian] [Link]
21. Ogata K. Modern control engineering. 5th Edition. Upper Saddle River, New Jersey: Prentice Hall; 2010. [Link]
22. Navabi M, Davoodi A. Modeling of fuel sloshing in a spacecraft and control it by active control method using nonlinear control. Modares Mechanical Engineering. 2019;19(9):2121-2128. [Link]
23. Tafazoli S, Khorasani K. Nonlinear control and stability analysis of spacecraft attitude recovery. IEEE Transactions on Aerospace and Electronic Systems. 2006;42(3):825-845. [Link] [DOI:10.1109/TAES.2006.248187]

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