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Register a new userDesigning a control unit for suspension system in quarter car model using Extended Adaptive Neuro Fuzzy Inference System
تصميم وحدة تحكم لنظام التعليق في نموذج ربع المركبة باستخدام نظام الاستدلال العصبي الضبابي المتكيف الموسع
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تعتبر أنظمة التعليق من أهم المكونات في المركبات الحديثة كما أنها تعد أهم عوامل الراحة و الأمان فيها لذلك كان لابد من تأمين متحكم يضمن التفاعل الكامل بين مكونات نظام التعليق و يساعد في اتخاذ القرارات الدقيقة في الوقت المناسب, يقترح البحث تصميم متحكم باستخدام نظام الاستدلال العصبي الضبابي المكيف الموسع (EANFIS) و استخدامه كوحدة اتخاذ قرار في نظام التعليق لنموذج ربع المركبة بغاية المحافظة على ثبات المركبة على الطرقات لتأمين راحة الركاب حيث يقوم بتحقيق دقة في اتخاذ القرار للمساهمة في تخفيض الاهتزازات و امتصاص الصدمات الناتجة عن عدم استواء الطريق و بالتالي يمنع وصولها إلى مقصورة القيادة و يؤمن الثبات و التماسك المطلوب تم تطبيق المتحكم على نموذج ربع المركبة و دراسة استجابة النموذج في حال حدوث اضطرابات مختلفة و مقارنة أداء المتحكم مع متحكم يعتمد على نظام الاستدلال الضبابي و مع استجابة النموذج الرياضي ذو الحلقة المفتوحة بوجود اضطرابات دخل مختلفة و قد أظهر المتحكم تفوقاً في الأداء من حيث تخفيض الإزاحات و سرعة الاهتزاز و تسارعه.
Suspension system is considered one of the most important components of modern automobiles as it is the responsible for the vehicle’s stability, balance and safety. The presence of robust controller is very necessary in order to ensure full interaction between suspension components and making accurate decisions at the right time. This paper proposes to design an Extended Adaptive Neuro Fuzzy Inference System (EANFIS) controller for suspension system in quarter car model. The proposed controller is used as decision maker In order to contribute in absorbing shocks caused by bumpy roads, and to prevent vibrations from reaching the cockpit. Furthermore, it provides stability and coherence required to reduce the discomfort felt by passengers, which arises from road roughness, which in turn, improve the road handling. The MATLAB Simulink is used to simulate the proposed controller with the controlled model and to display the responses of the controlled model under different types of disturbance. In addition, a comparison between EANFIS controller, Fuzzy controller and open loop model (passive suspension) was done with different types of disturbance on order to evaluate the performance of the proposed model. Controller has shown excelled performance in terms of reducing displacements, velocity and acceleration.
References used
FARD, H., SAMADI, F. Active Suspension System Control Using Adaptive Neuro Fuzzy (ANFIS) Controller,International Journal of Engineering.Vol.28,No.3, 2015,396-401
WEIHUA, LI., HAIPING, D. An adaptive Neuro fuzzy hybrid control strategy for a semi active suspension with magneto rheological damper. Hindawi Publishing Corporation. Vol. 3,No.4, 2014, 71-82
HEIDARI, M., HOMAEI, H. Design a PID Controller for Suspension System by Back Propagation Neural Network. Journal of Engineering. Vol.13,No.1, 2013, 1-9
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