A GMDH neural network-based approach to robust fault diagnosis: Application to the DAMADICS benchmark problem M Witczak, J Korbicz, M Mrugalski, RJ Patton Control Engineering Practice 14 (6), 671-683, 2006 | 138 | 2006 |
An unscented Kalman filter in designing dynamic GMDH neural networks for robust fault detection M Mrugalski International Journal of Applied Mathematics and Computer Science 23 (1 …, 2013 | 109 | 2013 |
Confidence estimation of the multi-layer perceptron and its application in fault detection systems M Mrugalski, M Witczak, J Korbicz Engineering Applications of Artificial Intelligence 21 (6), 895-906, 2008 | 62 | 2008 |
Neural network-based robust actuator fault diagnosis for a non-linear multi-tank system M Mrugalski, M Luzar, M Pazera, M Witczak, C Aubrun ISA transactions 61, 318-328, 2016 | 58 | 2016 |
Advanced neural network-based computational schemes for robust fault diagnosis M Mrugalski Springer International Publishing 510, 182, 2014 | 57 | 2014 |
A quadratic boundedness approach to robust DC motor fault estimation M Buciakowski, M Witczak, M Mrugalski, D Theilliol Control Engineering Practice 66, 181-194, 2017 | 36 | 2017 |
Confidence estimation of GMDH neural networks and its application in fault detection systems J Korbicz, M Mrugalski International Journal of Systems Science 39 (8), 783-800, 2008 | 33 | 2008 |
A neural network approach to simultaneous state and actuator fault estimation under unknown input decoupling P Witczak, K Patan, M Witczak, M Mrugalski Neurocomputing 250, 65-75, 2017 | 30 | 2017 |
State-space GMDH neural networks for actuator robust fault diagnosis M Mrugalski, M Witczak Advances in Electrical and Computer Engineering 12 (3), 65-72, 2012 | 27 | 2012 |
Towards robust neural-network-based sensor and actuator fault diagnosis: Application to a tunnel furnace M Witczak, M Mrugalski, J Korbicz Neural Processing Letters 42, 71-87, 2015 | 20 | 2015 |
A quadratic boundedness approach to a neural network-based simultaneous estimation of actuator and sensor faults M Pazera, M Buciakowski, M Witczak, M Mrugalski Neural Computing and Applications 32, 379-389, 2020 | 19 | 2020 |
An H∞approach to fault estimation of non-linear systems: Application to one-link manipulator M Witczak, M Buciakowski, M Mrugalski 2014 19th International Conference on Methods and Models in Automation and …, 2014 | 18 | 2014 |
Remaining useful life prediction of MOSFETs via the Takagi–Sugeno framework M Witczak, M Mrugalski, B Lipiec Energies 14 (8), 2135, 2021 | 14 | 2021 |
Least mean square vs. outer bounding ellipsoid algorithm in confidence estimation of the GMDH neural networks M Mrugalski, J Korbicz International Conference on Adaptive and Natural Computing Algorithms, 19-26, 2007 | 14 | 2007 |
Neural network based modelling of non-linear systems in fault detection schemes M Mrugalski PhD thesis, 2004 | 14 | 2004 |
Parameter estimation of dynamic GMDH neural networks with the bounded-error technique M Mrugalski, M Witczak Journal of Applied Computer Science 10 (1), 77-90, 2002 | 13 | 2002 |
Fault diagnosis of an automated guided vehicle with torque and motion forces estimation: A case study M Witczak, M Mrugalski, M Pazera, N Kukurowski ISA transactions 104, 370-381, 2020 | 12 | 2020 |
Dynamic GMDH type neural networks M Mrugalski, E Arinton, J Korbicz Neural Networks and Soft Computing: Proceedings of the Sixth International …, 2003 | 11 | 2003 |
Robust fault detection via GMDH neural networks M Mrugalski, J Korbicz, RJ Patton IFAC Proceedings Volumes 38 (1), 83-88, 2005 | 10 | 2005 |
Fault-tolerant tracking control for a non-linear twin-rotor system under ellipsoidal bounding N Kukurowski, M Mrugalski, M Pazera, M Witczak International Journal of Applied Mathematics and Computer Science 32 (2), 2022 | 7 | 2022 |