@misc{Tzafestas_Spyros_G._Model-based, author={Tzafestas, Spyros G. and Kyriannakis, Efthimios and Anthopoulos, Yiannis}, howpublished={online}, publisher={Zielona Góra: Uniwersytet Zielonogórski}, language={eng}, abstract={An approach to the design of discrete-time decentralized control systems based on model-based predictive control (MBPC) and neural estimation is proposed. The class of interconnected large-scale systems (LSS) is considered, and a model is used at each control station to predict the corresponding subsystem output over a long time period.}, abstract={In the case of subsystems with m-step delay information patterns the non-locally available interaction trajectories are estimated by a multi-layer neural network trained on-line with a modified backpropagation-type algorithm. Representative computer simulation results are provided and compared for a set of illustrative examples. The proposed control scheme shows better performance than the other schemes, and also covers the important case where the subsystems' interactions are nonlinear.}, type={artykuł}, title={Model-based predictive control of large-scale systems using a neural estimator}, keywords={sterowanie, sterowanie-teoria, sztuczna inteligencja, matematyka stosowana, informatyka}, }