IJE TRANSACTIONS A: Basics Vol. 29, No. 4 (April 2016) 490-499   

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M. H. Vali, B. Rezaie and Z. Rahmani
( Received: February 18, 2016 – Accepted in Revised Form: April 14, 2016 )

Abstract    This paper addresses control design in networked control system by considering stochastic packet dropouts in the forward path of the control loop. The packet dropouts are modelled by mutually independent stochastic variables satisfying Bernoulli binary distribution. A sliding mode controller is utilized to overcome the adverse influences of stochastic packet dropouts in networked control systems. Firstly, to determine the parameters of switching function used in the sliding mode control design, an improved genetic algorithm is applied. The proposed improved genetic algorithm provides a fast convergence rate and a proper dynamic performance in comparison with conventional genetic algorithms especially in online control applications. Then, an adaptive neural sliding mode control based on radial-basis function neural network approximation is proposed to eliminate chattering phenomenon in the sliding mode control. A numerical example is given to illustrate the effectiveness of the proposed controller in networked control systems. The results show that the proposed controller provides high-performance dynamic characteristics and robustness against plant parameter variations and external disturbances.


Keywords    Networked control systems, packet dropouts, sliding mode control, genetic algorithm, radial-basis function neural network


چکیده    در این مقاله طراحي کنترل در سیستمهای کنترل شبکهای با وجود حذف تصادفی بستههای داده در مسیر کنترلکننده به محرک بررسی میگردد. در این راستا حذف تصادفی بستههای داده با روش متغيرهای تصادفي مستقل با توزیع باینری برنولی مدلسازی شده است. برای جبران اثرات نامطلوب حذف تصادفی بستههای داده در سیستمهای کنترل شبکهای از یک کنترلکننده مود لغزشی استفاده شده است. ابتدا برای تعیین پارامترهاي تابع سوئیچینگ در کنترل مود لغزشی از یک روش بهبود یافته از الگوریتم ژنتیک استفاده شده است. این الگوریتم بهبود یافته، همگرایی سریعتر همراه با عملکرد دینامیکی مطلوبتري را نسبت به الگوریتم ژنتیک معمولي بهويژه در کاربردهای آنلاین فراهم مي‏سازد. سپس، يک روش تطبیقی کنترل مود لغزشی عصبی مبتنی بر تقريب با شبکه‏هاي عصبی با تابع پايه شعاعي به منظور حذف پدیدۀ چترینگ پيشنهاد شده است. برای نمایش کارايي کنترلکننده پیشنهادی در سیستم های کنترل شبکهای یک مثال عددی آورده شده است. نتايج حاصل شده نشاندهنده بهبود عملکرد دینامیکی سیستم و مقاومت در برابر تغييرات پارامترهاي سيستم و اغتشاشات خارجی مي‏باشد.


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