ارائه الگوریتم کنترل فعال فازی بهینه شده با روش مسابقه طناب کشی برای کنترل پاسخ های پل بزرگراه

نوع مقاله : علمی - پژوهشی

نویسندگان

1 گروه سازه ، دانشگاه صنعتی نوشیروانی بابل

2 دانشیار، دانشکده مهندسی عمران، دانشگاه صنعتی نوشیروانی بابل، بابل، ایران

3 دانشیار، دانشگاه صنعتی نوشیروانی بابل

4 دانشیار، دانشکده مهندسی، دانشگاه فردوسی مشهد، مشهد، ایران

چکیده

این تحقیق یک الگوریتم کنترل فعال فازی بهینه شده تحت بارگذاری زلزله های مختلف، با روش بهینه سازی جدید بسیار کارآمد در مورد سازه های عمرانی برگرفته از مسابقه طناب کشی پیشنهاد می دهد. روش کنترل بر پایه ترکیب شبکه عصبی فازی و روش بهینه سازی فراابتکاری بر پایه جمعیت مسابقه طناب کشی ارائه شده است. کارآمدی الگوریتم پیشنهادی بر روی پل بزرگراه بنچ مارک با جداگرهای پایه غیرخطی و اعضای سازه‌ای غیر خطی مجهز به محرک های هیدرولیکی ارزیابی شده است. الگوریتم قادر است ماهیت میدان نزدیک یا دور بودن زلزله را تشخیص داده و براساس آن نیروی کنترلی لازم را برآورد نماید. نیروی کنترلی در این تحقیق با استفاده از یک شبکه عصبی پنج لایه بدست آمده است. شبکه عصبی برای تقریب قوانین غیرخطی کنترل، به صورت بهینه توسط روش بهینه‌سازی معرفی شده، توانمند شده است و محرک های نصب شده بر روی پایه های پل را کنترل می نماید. پایداری قوانین کنترل حین بهینه سازی برای رسیدن به بهترین پارامترها، توسط تئوری لیاپانوف کنترل می شود. نتایج مدلسازی عددی به صورت اندیس عملکرد و قابل قیاس با روش های پیشین ارائه شده است. نتایج نشان می دهد الگوریتم پیشنهادی در تمامی شش رکورد زلزله آزمایش شده در این تحقیق، از روش های ارائه شده پیشین در کاهش پاسخ‌های سازه موفق تر بوده است. الگوریتم در کنار کاهش کلی پاسخ های پل، سبب کاهش میزان خسارات سازه ای وارد بر آن نیز می شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Fuzzy-Tug of war structural active control for a seismically excited benchmark highway bridge

نویسندگان [English]

  • Mostafa Ghelichi 1
  • Alireza Mirza Goltabar Roshan 2
  • Hamidreza Tavakoli 3
  • Abbas Karamodin 4
1 structural department, Babol Noshirvani university of technology
2 Associate Professor, Faculty of Civil Engineering, Noshirvani University of ‎Technology, Babol, Iran
3 Associate Professor, Faculty of Civil Engineering, Babol Noshirvani University of Technology, Babol, Iran
4 Associate Professor, Department of Civil Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
چکیده [English]

In this paper a new optimized active control algorithm based on combination of fuzzy neural network and a new highly efficient meta-heuristic population based optimization method extracted from Tug of War competition presents under different earthquake loads. The Efficiency of the proposed control method has been evaluated on the recently proposed nonlinear highway bridge benchmark, consist of nonlinear isolation bearings and nonlinear structural elements which equipped with the hydraulic actuators. A 5-layer neural network is used to obtain the control force. The neural network is utilized to approximate nonlinear rules of control. It gets instructions to the actuators installed between the deck and abutments. Stability of control laws to choose the parameters of the neural network are derived based on Lyapunov theory. The Results are presented in terms of a well-defined set of performance indices which is comparable to previous methods. The results show that the proposed controller method in spite of a simple description of the nonlinearities and non-detailed structural information can effectively reduce the responses of the bridge especially maximum of base shear, maximum of midspan displacement and maximum of acceleration. Also sensible decrease in responses such as maximum of ductility, dissipated energy and plasticity connections show that the proposed method is very effective in reducing structural damages.

کلیدواژه‌ها [English]

  • Active control
  • Tug of War
  • ANFIS
  • Neural Network
  • Benchmark Bridge
  • Lyapunov Stability
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