کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
411078 | 679177 | 2010 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Computationally efficient nonlinear predictive control based on neural Wiener models
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This paper describes a computationally efficient nonlinear model predictive control (MPC) algorithm based on neural Wiener models and its application. The model contains a linear dynamic part in series with a steady-state nonlinear part which is realised by a neural network. In the presented MPC algorithm the model is linearised on-line, as a result the future control policy is easily calculated from a quadratic programming problem. The algorithm gives control performance similar to that obtained in fully fledged nonlinear MPC, which hinges on non-convex optimisation. In order to demonstrate the accuracy and the computational efficiency of the considered MPC algorithm a polymerisation process is studied.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 74, Issues 1–3, December 2010, Pages 401–417
Journal: Neurocomputing - Volume 74, Issues 1–3, December 2010, Pages 401–417
نویسندگان
Maciej ławryńczuk,