IJE TRANSACTIONS C: Aspects Vol. 28, No. 12 (December 2015) 1765-1773   

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A. Alfi
( Received: March 11, 2015 – Accepted: November 19, 2015 )

Abstract    This paper deals with the application of Iterative Learning Control (ILC) to further improve the performance of teleoperation systems based on Smith predictor. The goal is to achieve robust stability and optimal transparency for these systems. The proposed control structure make the slave manipulator follow the master in spite of uncertainties in time delay in communication channel and model parameters of master-slave robots, called model mismatch. The time delays in communication channel are assumed to be large, unknown and asymmetric, but the upper bound of the delay is assumed to be known. The main aspect of the proposed controller is that a designer can use the classical controller like Proportional-Integrator-Derivative (PID). However, one of its main difficulties is how to assign appropriate parameter values for the controller. In the other words, the parameters of the controller are not unique and are chosen only to satisfy the stability condition. To solve this problem, in this paper, the local controller is optimized by Backtracking Search optimization Algorithm (BSA), which is a novel heuristic algorithm with a simple construction. Simulation results illustrate the appropriate performance of the proposed controller.


Keywords    Teleoperation, Transparency, Iterative Learning Control, Smith predictor, Optimization, Backtracking Search Optimization Algorithm.


چکیده    اين مقاله به کاربرد کنترل يادگيري تکراري براي بهبود بيشتر عملکرد سيستم‌هاي حرکتي از راه دور بر اساس پيش‌بين اسميث مي‌پردازد. هدف دستيابي به پايداري مقاوم و عملکرد بهينه است. ساختار کنترلي پيشنهادي سبب مي‌گردد که سيستم فرمانبر از سيستم فرمانده در حضور نامعيني در زمان تاخير کانال ارتباطي و پارامترهاي مدل سيستم‌هاي فرمانده و فرمانبر تبعيت کند. زمان‌های تاخير در کانال ارتباطي بزرگ، نامشخص و نابرابر با حد بالايي محدود فرض مي‌شود. ويژگي اصلي کنترل‌کننده پيشنهادي آن است که طراح مي‌تواند از کنترل‌کننده‌هاي کلاسيک مانند تناسبي- انتگرالی‌گير- مشتق‌گير استفاده کند. هرچند مشکل اساسي تعيين مقادير مناسب پارامترهاي کنترل‌کننده است. به بياني ديگر، پارامترهاي کنترل‌کننده منحصر به فرد نبوده و تنها بايستي شرط پايداري را برآورده سازند. براي حل اين مساله، در اين مقاله کنترل‌کننده محلي توسط الگوريتم بهينه‌سازي جستجوي بازگشتي که يک الگوريتم اکتشافي جديد و ساده است بهينه مي‌شود. نتايج شبيه‌سازي عملکرد مناسب کنترل‌کننده پيشنهادي را نشان مي‌دهد.



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