A controller architecture for nonlinear systems described by Gaussian RBF neural networks is proposed. The controller is a stabilising solution to a class of nonlinear optimal state tracking problems and consists of a combination of a state feedback stabilising regulator and a feedforward neuro-controller. ; The state feedback stabilising regulator is computed online by transforming the tracking problem into a more manageable regulation one, which is solved within the framework of a nonlinear predictive control strategy with guaranteed stability. The feedforward neuro-controller has been designed using the concept of inverse mapping. The proposed control scheme is demonstrated on a simulated single-link robotic manipulator.
Aug 21, 2020
Aug 21, 2020
|Stabilising solutions to a class of nonlinear optimal state tracking problems using radial basis function networks||Aug 21, 2020|
Haber, Robert Bars, Ruth Lengyel, Orsolya Kowalczuk, Zdzisław - red.
Tatjewski, Piotr Ławryńczuk, Maciej Korbicz, Józef - red.
Ławryńczuk, Maciej Tatjewski, Piotr Korbicz, Józef - red. Uciński, Dariusz - red.
Janczak, Andrzej Korbicz, Józef - red. Patton, Ronald J. - red.
Korbicz, Józef Patan, Krzysztof Korbicz, Józef - red. Uciński, Dariusz - red.
Debbache, Ghania Bennia, Abdelhak Goléa, Noureddine Korbicz, Józef - red. Uciński, Dariusz - red.
Dzieliński, Andrzej Beliczyński, Bartłomiej - red.
Witczak, Marcin Korbicz, Józef - red.