The combination of model predictive control based on linear models (MPC) with feedback linearization (FL) has attracted interest for a number of years, giving rise to MPC+FL control schemes. An important advantage of such schemes is that feedback linearizable plants can be controlled with a linear predictive controller with a fixed model. Handling input constraints within such schemes is difficult since simple bound contraints on the input become state dependent because of the nonlinear transformation introduced by feedback linearization. ; This paper introduces a technique for handling input constraints within a real time MPC/FL scheme, where the plant model employed is a class of dynamic neural networks. The technique is based on a simple affine transformation of the feasible area. A simulated case study is presented to illustrate the use and benefits of the technique.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 19, number 2 (2009) ; kliknij tutaj, żeby przejść
Biblioteka Uniwersytetu Zielonogórskiego
2024-04-09
2024-04-09
10
https://zbc.uz.zgora.pl/publication/88538
Nazwa wydania | Data |
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Input constraints handling in an MPC/feedback linearization scheme | 2024-04-09 |
Ahmida, Zahir Charef, Abdelfettah Becerra, Victor M. Korbicz, Józef - red. Uciński, Dariusz - red.
Tatjewski, Piotr Ławryńczuk, Maciej Korbicz, Józef - red.
Kaczorek, Tadeusz (1932- ) Iacono, Mauro - ed. Kołodziej, Joanna - ed.
Haber, Robert Bars, Ruth Lengyel, Orsolya Kowalczuk, Zdzisław - red.
Dzieliński, Andrzej Korbicz, Józef - red. Uciński, Dariusz - red.
Ławryńczuk, Maciej Tatjewski, Piotr Korbicz, Józef - red. Uciński, Dariusz - red.
Ławryńczuk, Maciej Korbicz, Józef - ed.
Pedro, Jimoh Olarewaju Dahunsi, Olurotimi Akintunde Korbicz, Józef - red. Uciński, Dariusz - red.