کنترل زمان گسسته مستقل از مدل برای بازوی ماهر ربات اسکارا با استفاده از الگوریتم گرادیان نزولی
محورهای موضوعی :
مهندسی الکترونیک
رضا زرین
1
,
سیامک آذرگشسب
2
1 - گروه برق، واحد بوشهر، دانشگاه آزاد اسلامی، بوشهر، ایران
2 - گروه برق، واحد بوشهر، دانشگاه آزاد اسلامی، بوشهر، ایران
تاریخ دریافت : 1399/08/05
تاریخ پذیرش : 1400/03/03
تاریخ انتشار : 1400/07/01
کلید واژه:
اندازه-گیری موقعیت,
الگوریتم گرادیان نزولی,
مستقل از مدل,
کنترل زمان گسسته,
بازوی ربات اسکارا,
چکیده مقاله :
کنترل گسسته بازوی مکانیکی ربات با مدل نامعینی هدف این مقاله است. کنترل پیشنهادی مستقل از مدل با استفاده از تخمین گر فازی تطبیقی در کنترل کننده برای تخمین نامعینی یک تابع نامعلوم طراحی شده است. مکانیزم تطبیقی به منظور غلبه بر عدم قطعیت ها پیشنهاد شده است. پارامترهای تخمین فازی برای حداقل کردن خطای تخمین با استفاده از الگوریتم گرادیان نزولی تطبیق داده شده اند. کنترل گسسته پیشنهادی مستقل از مدل در برابر همه نامعینی ها مرتبط با مدل سیستم ربات شامل بازوی مکانیکی و محرکه های ربات و اغتشاش خارجی مقاوم است. الگوریتم های گرادیان نزولی از یک تابع هزینه شناخته شده بر اساس خطای ردیابی برای مکانیزم تطبیق استفاده کرده اند در حالی که در این مقاله الگوریتم گرادیان نزولی پیشنهادی یک تابع هزینه را بر اساس خطای تخمین عدم قطعیت پیشنهاد داده است. سپس، خطای تخمین عدم قطعیت از خطای موقعیت مفصل و مشتقات آن با استفاده از سیستم حلقه بسته محاسبه می شود.اکثر الگوریتم های کنترلی با تضمین پایداری برای بازوی مکانیکی ربات، همه فیدبک های متغیرهای حالت را نیاز دارد. در این مقاله، فقط از موقعیت مفصل اندازه گیری می کند و پیاده سازی عملی این روش کنترلی آسان است از آنجا که ساختار غیر متمرکز دارد.نتایج شبیه سازی عملکرد صحیح این روش را تأیید می کند.
چکیده انگلیسی:
Discrete control of the robot manipulators with uncertain model is the purpose of this paper. The proposed control design is model-free by employing an adaptive fuzzy estimator in the controller for the estimation of uncertainty as unknown function. An adaptive mechanism is proposed in order to overcome uncertainties. Parameters of the fuzzy estimator are adapted to minimize the estimation error using a novel gradient descent algorithm. The proposed model-free discrete control is robust against all uncertainties associated with the robot manipulator and actuators including model’s uncertainty and external disturbances. The most gradient descent algorithms have used a known cost function based on the tracking error for adaptation whereas the proposed algorithm has proposed a cost function based on the uncertainty estimation error. Then, the uncertainty estimation error is calculated from the joint position error and its derivative using the closed-loop system. Most control algorithms require all state variable feedback to ensuring stability for the robot manipulators. Practical implementation of this control method is easy because it has a decentralized structure and measures only from the joint position. The simulation results confirm the correct operation of this method and we will prove the stability of the control system.
منابع و مأخذ:
W. Spong and M. Vidyasagar, “Robot dynamic and control”, Wiley, New York, 1989.
Wang, X. Zhou, Z. Xia and X. Gu, “A Survey of Welding robot Intelligent Path Optimazation,” Journal of Manufacturing Processes, 14 may 2020.
Zhang, X. Wang, X. Zhu, Q. Cao and F. Tao, “Cloud Manufacturing Paradigm with Ubiquitous Robotic system for Product Customization”, Robotics and Computer-Integrated Manufacturing, Vol. 60, pp. 12-22, 2019.
Ogata, “Discrete-Time Control Systems,” Prentice-Hall, NJ, 1987.
Treesatayapun and A. J. M. Vazquez, “Discrete-Time Fractional-Order Control Based on Data-Driven Equivalent Model,” Applied Soft Computing, Vol. 96, pp. 65-71, 2020.
M. Fateh, H. Ahsani Tehrani, S.M. Karbassi, “Repetitive control of electrically driven robot manipulators,” International Journal of Systems Science, vol. 44, no. 4, pp. 775-785, 2013.
Qu and D.M. Dawson, “Robust tracking control of robot manipulators,” IEEE Press, Inc., New York, 1996.
Wang and D.M. Dawson, “Robust tracking control of robot manipulators”, IEEE Press, Inc., New, 1997.
Qi, G. Tao, B. Jiang and C. Tan, “Adaptive control schemes for discrete-time T–S fuzzy systems with unknown parameters and actuator failures,” IEEE Transactions on Fuzzy Systems, vol. 20, no. 3, pp. 471-486 ,2012.
Kim, “A discrete-time fuzzy disturbance observer and its application to control,” IEEE Transactions on Fuzzy Systems, Vol. 11, No. 3, pp. 399-410,2003.
Ruiyun and A.B. Mietek, “Stable indirect adaptive control based on discrete-time T–S fuzzy model,” Fuzzy Sets and Systems, Vol. 159, No. 8, pp. 900-925, 2008.
Zhang, X. Huang, X. Ban and X. Z. Gao, “Stability analysis and design for discrete fuzzy systems with time-delay under imperfect premise matching,” Journal of Information & Computational Science, Vol. 8, No. 13, pp. 2613-2622, 2011.
Zhang and G. Feng, “Stability analysis and controller design of discrete-time fuzzy large-scale systems based on piecewise Lyapunov functions,” IEEE Transactions on Systems, Vol. 38, No. 5, pp. 1390-1401, 2008.
M. Fateh, “Proper uncertainty bound parameter to robust control of electrical manipulators using nominal model,” Nonlinear Dyn, Vol. 61, No. 4, pp. 655-666, 2010.
A. Fahmy and A. M. Abdel Ghany, “Neuro-fuzzy inverse model control structure of robotic manipulators utilized for physiotherapy applications,” Ain Shams Engineering Journal, Vol. 4, No. 4, pp. 805-829, 2013.
T. Spooner and K. M. Passino, “Stable adaptive control using fuzzy systems and neural networks,” IEEE Trans. Fuzzy Systems, Vol. 4, pp. 339–359, 1996.
V. Spong, S. Hutchinson and M. Vidyasagar, “Robot Modelling and Control,” Wiley, Hoboken, 2006.
M. Fateh, “On the voltage-based control of robot manipulators,” International Journal of Control, Automation, and Systems, Vol. 6, No. 5, pp. 702-712, 2008.
M. Fateh, “Robust fuzzy control of electrical manipulators,” J. Intell. Robot. Syst. Vol. 60, No. 3, pp. 415-434, 2010.
M. Fateh S. Khorashadizadeh, Robust control of electrically driven robots by adaptive fuzzy estimation of uncertainty”, Nonlinear Dyn., Vol. 69, No. 13, pp. 1465-1477, 2012.
M. Fateh and S. Fateh,” Decentralized direct adaptive fuzzy control of robots using voltage control strategy”, Nonlinear Dyn., Vol. 70, No. 3, pp. 1919-1930, 2012.
Moreno-Valenzuela, R. Campa and V. Santibanez,”On passivity-based control of a class of electrically driven robots” In proc IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society, pp. 2756-2761 ,2012.
X. Wang, “Adaptive fuzzy systems and control”, Prentice Hall, 1994.
Qu and D. M. Dawson, “Robust tracking control of robot manipulators”, IEEE Press, Inc., New York, 1996.
Q. Ruiyun and A.B. Mietek,”Stable indirect adaptive control based on discrete time T-S fuzzy model” Fuzzy Sets Syst, 159, No. 8, pp. 900-925, 2008.
J. Schilling, "Fundamentals of Robotics Analysis & Control", Prentice-Hall of India, New Delhi, 2003.
R. shokoohinia and M. M. Fateh, "Robust dynamic sliding mode control or robot manipulators ysing the fourier series expansion", Transactions of the Institute of Measurment and Control, First Published October 15, 2018.
_||_
W. Spong and M. Vidyasagar, “Robot dynamic and control”, Wiley, New York, 1989.
Wang, X. Zhou, Z. Xia and X. Gu, “A Survey of Welding robot Intelligent Path Optimazation,” Journal of Manufacturing Processes, 14 may 2020.
Zhang, X. Wang, X. Zhu, Q. Cao and F. Tao, “Cloud Manufacturing Paradigm with Ubiquitous Robotic system for Product Customization”, Robotics and Computer-Integrated Manufacturing, Vol. 60, pp. 12-22, 2019.
Ogata, “Discrete-Time Control Systems,” Prentice-Hall, NJ, 1987.
Treesatayapun and A. J. M. Vazquez, “Discrete-Time Fractional-Order Control Based on Data-Driven Equivalent Model,” Applied Soft Computing, Vol. 96, pp. 65-71, 2020.
M. Fateh, H. Ahsani Tehrani, S.M. Karbassi, “Repetitive control of electrically driven robot manipulators,” International Journal of Systems Science, vol. 44, no. 4, pp. 775-785, 2013.
Qu and D.M. Dawson, “Robust tracking control of robot manipulators,” IEEE Press, Inc., New York, 1996.
Wang and D.M. Dawson, “Robust tracking control of robot manipulators”, IEEE Press, Inc., New, 1997.
Qi, G. Tao, B. Jiang and C. Tan, “Adaptive control schemes for discrete-time T–S fuzzy systems with unknown parameters and actuator failures,” IEEE Transactions on Fuzzy Systems, vol. 20, no. 3, pp. 471-486 ,2012.
Kim, “A discrete-time fuzzy disturbance observer and its application to control,” IEEE Transactions on Fuzzy Systems, Vol. 11, No. 3, pp. 399-410,2003.
Ruiyun and A.B. Mietek, “Stable indirect adaptive control based on discrete-time T–S fuzzy model,” Fuzzy Sets and Systems, Vol. 159, No. 8, pp. 900-925, 2008.
Zhang, X. Huang, X. Ban and X. Z. Gao, “Stability analysis and design for discrete fuzzy systems with time-delay under imperfect premise matching,” Journal of Information & Computational Science, Vol. 8, No. 13, pp. 2613-2622, 2011.
Zhang and G. Feng, “Stability analysis and controller design of discrete-time fuzzy large-scale systems based on piecewise Lyapunov functions,” IEEE Transactions on Systems, Vol. 38, No. 5, pp. 1390-1401, 2008.
M. Fateh, “Proper uncertainty bound parameter to robust control of electrical manipulators using nominal model,” Nonlinear Dyn, Vol. 61, No. 4, pp. 655-666, 2010.
A. Fahmy and A. M. Abdel Ghany, “Neuro-fuzzy inverse model control structure of robotic manipulators utilized for physiotherapy applications,” Ain Shams Engineering Journal, Vol. 4, No. 4, pp. 805-829, 2013.
T. Spooner and K. M. Passino, “Stable adaptive control using fuzzy systems and neural networks,” IEEE Trans. Fuzzy Systems, Vol. 4, pp. 339–359, 1996.
V. Spong, S. Hutchinson and M. Vidyasagar, “Robot Modelling and Control,” Wiley, Hoboken, 2006.
M. Fateh, “On the voltage-based control of robot manipulators,” International Journal of Control, Automation, and Systems, Vol. 6, No. 5, pp. 702-712, 2008.
M. Fateh, “Robust fuzzy control of electrical manipulators,” J. Intell. Robot. Syst. Vol. 60, No. 3, pp. 415-434, 2010.
M. Fateh S. Khorashadizadeh, Robust control of electrically driven robots by adaptive fuzzy estimation of uncertainty”, Nonlinear Dyn., Vol. 69, No. 13, pp. 1465-1477, 2012.
M. Fateh and S. Fateh,” Decentralized direct adaptive fuzzy control of robots using voltage control strategy”, Nonlinear Dyn., Vol. 70, No. 3, pp. 1919-1930, 2012.
Moreno-Valenzuela, R. Campa and V. Santibanez,”On passivity-based control of a class of electrically driven robots” In proc IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society, pp. 2756-2761 ,2012.
X. Wang, “Adaptive fuzzy systems and control”, Prentice Hall, 1994.
Qu and D. M. Dawson, “Robust tracking control of robot manipulators”, IEEE Press, Inc., New York, 1996.
Q. Ruiyun and A.B. Mietek,”Stable indirect adaptive control based on discrete time T-S fuzzy model” Fuzzy Sets Syst, 159, No. 8, pp. 900-925, 2008.
J. Schilling, "Fundamentals of Robotics Analysis & Control", Prentice-Hall of India, New Delhi, 2003.
R. shokoohinia and M. M. Fateh, "Robust dynamic sliding mode control or robot manipulators ysing the fourier series expansion", Transactions of the Institute of Measurment and Control, First Published October 15, 2018.
