Fuzzy Model Reference Learning Control for Antilock Breaking Systems

سال انتشار: 1384
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 1,911

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شناسه ملی سند علمی:

ISME13_601

تاریخ نمایه سازی: 21 اسفند 1385

چکیده مقاله:

Although antiskid braking systems (ABS) are designed to optimize braking effectiveness while maintaining steer ability, their performance often degrades for harsh road conditions, e-g, and icy/snowy roads. This paper introduces the idea of using the fuzzy model reference learning control (FMRLC) technique for maintaining adequate performance even under such adverse road conditions. This controller utilizes a learning mechanism which observes the plant outputs and adjusts the rules in a direct fuzzy controller so that the overall system behaves like a “reference model” which characterizes the desired behavior. The performance of the FMRLC – based ABS is demonstrated by simulation for various road conditions (wet asphalt, icy) and transitions between such conditions (e.g., when emergency braking occurs and the road switches from wet to icy or vice versa).

کلیدواژه ها:

ABS-Reference model-Fuzzy controller-Fuzzy inverse model-Learning mechanism

نویسندگان

Omid Aghababai

Graduate Student in Mechanical Engineering, Center of Excellence in Design, Robotics, and Automation (CEDRA)

Aria Alasty

Associate Professor,Department of Mechanical Engineering, Sharif University of Technology

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