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طراحی سامانه ی راهبری بهینه ی خودکار قطار با استفاده از کنترل کننده ی پیش بین مدل به همراه مطالعه ی موردی بخشی از خط یک متروی تهران | ||
| مدل سازی در مهندسی | ||
| دوره 23، شماره 83، دی 1404، صفحه 85-101 اصل مقاله (877.53 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22075/jme.2024.29257.2373 | ||
| نویسندگان | ||
| عطا مستوفی نیا1؛ محمدعلی صندیدزاده* 1؛ سعید شمقدری2 | ||
| 1گروه مهندسی کنترل و علائم، دانشکده مهندسی راه آهن، دانشگاه علم و صنعت ایران | ||
| 2گروه مهندسی کنترل، دانشکده مهندسی برق، دانشگاه علم و صنعت ایران | ||
| تاریخ دریافت: 20 آذر 1401، تاریخ بازنگری: 23 بهمن 1402، تاریخ پذیرش: 30 بهمن 1402 | ||
| چکیده | ||
| با افزایش تقاضای سفرهای درون شهری و همچنین با توجه به مسائل زیست محیطی، حمل و نقل ریلی درون شهری به عنوان گزینه ای سبز مسئله ای با همیت دوچندان محسوب می گردد. نظر به محدود بودن زیرساخت ها اعم از خطوط و ناوگان های ریلی و منابع انرژی، بهره برداری ایمن و بهینه از شبکه های ریلی اهمیت ویژه ای پیدا می کند. در این پژوهش، پس از بررسی هدف و عملکرد فنآوری راهبری خودکار قطار، سامانه ی راهبری خودکاری با استفاده از روش کنترلی پیش بین، طراحی و معرفی شده است. به عنوان نوآوری این پژوهش، روش کنترل پیش بین جدیدی ارائه می گردد که با لحاظ کردن مشخصات فنی قطار و خط ریلی، به تعیین و اجرای راهبردی برای حرکت قطار می پردازد که ضمن درنظر گرفتن محدودیت های فیزیکی قطار و خط، و رعایت قیود مربوط به ایمنی و کارایی سفر، مساله ی بهینگی مصرف انرژی را نیز مدنظر می گیرد. سپس با روابط اصلاح شده مسئله خاص راهبری و فضای حالت برای کنترل کننده پیش بین مدل مدلسازی و کنترلکننده طراحی می گردد. در نهایت برای بررسی تاثیر سامانه ی پیشنهادی و کارایی آن در حضور اغتشاشات و نامعینی های مربوط به فضای عملی، مطالعه ی موردی خط یک متروی تهران از ایستگاه شهید بخارایی به ایستگاه پایانه جنوب انجام میگردد که نتایج، نشان دهنده ی بهبود 5.4 درصدی مصرف سوخت و موفقیت عملکردی آن است. | ||
| کلیدواژه‌ها | ||
| فرآیند تصمیم‌گیری مارکوفی؛ برنامه‌ریزی پویای تصادفی؛ برنامه‌ریزی توأم تولید و نگهداری و تعمیرات؛ نگهداری و تعمیرات ناقص؛ سیستم تولید تک‌محصولی | ||
| عنوان مقاله [English] | ||
| Designing an Optimal Automatic Train Operation System Using a Model Predictive Controller with a Case Study of a Part of Tehran Metro Line 1 | ||
| نویسندگان [English] | ||
| Ata Mostowfi Nia1؛ Mohammad Ali Sandidzadeh1؛ Saeed Shamaghdari2 | ||
| 1Department of Control Engineering and Signalling, School of Railway Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| 2Department of Control Engineering, School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran | ||
| چکیده [English] | ||
| With the increasing demand for intra-city travel and also considering environmental issues, intra-city rail transportation is considered a green solution, an option of double importance. Given the limited infrastructure, including rail lines and fleets and energy resources, safe and optimal operation of rail networks is of particular importance. In this research, after examining the purpose and performance of automatic train guidance technology, an automatic guidance system using a model predictive control method has been designed and introduced. As an innovation of this research, a new predictive control method is presented that, by considering the technical specifications of the train and the rail line, determines and implements a strategy for train movement that, while taking into account the physical limitations of the train and the line, and observing the constraints related to travel safety and efficiency, also considers the issue of energy consumption optimization; Thus, first by examining the dynamics of train motion and the physical relations governing it, state space equations were obtained for more accurate modeling of train motion, and then using a predictive controller, a system for optimal train control was designed. Finally, to investigate the effect of the proposed system and its efficiency in the presence of disturbances and uncertainties related to the practical space, a case study of Tehran Metro Line 1 is conducted by simulating train motion from Shahid Bukharaei Station to the South Terminal Station, and the results indicate a 5.4 percent improvement in fuel consumption and its operational success. | ||
| کلیدواژه‌ها [English] | ||
| Automatic train operation, Nonlinear model predictive control, Optimal speed profile, Longitudinal train dynamics | ||
| مراجع | ||
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