TY - JOUR N2 - Electromagnetic mill installation for dry grinding represents a complex dynamical system that requires specially designed control system. The paper presents model-based predictive control which locates closed loop poles in arbitrary places. The controller performs as gain scheduling prototype where nonlinear model – artificial recurrent neural network, is parameterized with additional measurements and serves as a basis for local linear approximation. Application of such a concept to control electromagnetic mill load allows for stable performance of the installation and assures fulfilment of the product quality as well as the optimization of the energy consumption. L1 - http://journals.pan.pl/Content/117707/PDF/art04.pdf L2 - http://journals.pan.pl/Content/117707 PY - 2020 IS - No 3 EP - 500 DO - 10.24425/acs.2020.134674 KW - predictive control KW - pole placement KW - nonlinear dynamics KW - neural modelling KW - electromagnetic mill A1 - Ogonowski, Szymon A1 - Bismor, Dariusz A1 - Ogonowski, Zbigniew PB - Committee of Automatic Control and Robotics PAS VL - vol. 30 DA - 2020.09.30 T1 - Control of complex dynamic nonlinear loading process for electromagnetic mill SP - 471 UR - http://journals.pan.pl/dlibra/publication/edition/117707 T2 - Archives of Control Sciences ER -