Design of the Model Predictive Controller Based on Orthonormal Basis Functions for Automotive Air Conditioning System

سال انتشار: 1394
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 151

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شناسه ملی سند علمی:

JR_MJEEMO-16-1_002

تاریخ نمایه سازی: 21 اسفند 1403

چکیده مقاله:

— Air conditioning system (A/C) of the car imposes an additional load on the engine, increasing fuel consumption and losses. Therefore, any improvement in its performance has a direct impact on vehicle performance and fuel consumption. The automotive A/C system is a Multi Input- Multi Output (MIMO) plant and There are constraints on its variables So the method of Model Predictive Control (MPC) as an effective method. So far the MPC method is implemented largely for this system. In this paper a predictive control method based on orthonormal functions is provided for automotive air conditioning system. System's model has been changed with an embedded integrator, inputs and outputs changes are highly penalized in cost function and Laguerre orthonormal basis functions are added in MPC's structure and it will be shown that in the proposed control method compared to the conventional MPC method, the automotive air conditioning system performance has been improved and because of reduced computational load the runtime of simulations implementation has been reduced.

کلیدواژه ها:

Automotive air conditioning system ، Model Predictive Controller ، Orthonormal functions ، سیستم تهویه مطبوع خودرو ، کنترل پیش بین مبتنی بر مدل ، توابع اورتونرمال

نویسندگان

پگاه خاوش

, Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran.

امین رمضانی

Assistant Professor of Electrical Engineering, Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran

سجاد ازگلی

Associate Professor of Electrical Engineering, Department of Electrical Engineering, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran.