کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5005392 1369025 2007 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An on-line modified least-mean-square algorithm for training neurofuzzy controllers
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
An on-line modified least-mean-square algorithm for training neurofuzzy controllers
چکیده انگلیسی
The problem hindering the use of data-driven modelling methods for training controllers on-line is the lack of control over the amount by which the plant is excited. As the operating schedule determines the information available on-line, the knowledge of the process may degrade if the setpoint remains constant for an extended period. This paper proposes an identification algorithm that alleviates “learning interference” by incorporating fuzzy theory into the normalized least-mean-square update rule. The ability of the proposed methodology to achieve faster learning is examined by employing the algorithm to train a neurofuzzy feedforward controller for controlling a liquid level process. Since the proposed identification strategy has similarities with the normalized least-mean-square update rule and the recursive least-square estimator, the on-line learning rates of these algorithms are also compared.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISA Transactions - Volume 46, Issue 2, April 2007, Pages 181-188
نویسندگان
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