Fuzzy Model Reference Learning Control for Antilock Breaking Systems
Publish place: 13th Annual Conference of Mechanical Engineering
Publish Year: 1384
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ISME13_601
تاریخ نمایه سازی: 21 اسفند 1385
Abstract:
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).
Keywords:
ABS-Reference model-Fuzzy controller-Fuzzy inverse model-Learning mechanism
Authors
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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