A GMDH neural network-based approach to robust fault diagnosis : Application to the DAMADICS benchmark problem
暂无分享,去创建一个
Józef Korbicz | Marcin Witczak | Ron J. Patton | Marcin Mrugalski | R. Patton | M. Witczak | J. Korbicz | M. Mrugalski
[1] R. Fletcher. Practical Methods of Optimization , 1988 .
[2] Michel Kinnaert,et al. Diagnosis and Fault-Tolerant Control , 2004, IEEE Transactions on Automatic Control.
[3] J. P. Norton,et al. Fast and robust algorithm to compute exact polytope parameter bounds , 1990 .
[4] Nariman Sepehri,et al. Diagnosis of process valve actuator faults using a multilayer neural network , 2003 .
[5] Duc Truong Pham,et al. Neural Networks for Identification, Prediction and Control , 1995 .
[6] J. Norton,et al. Bounding Approaches to System Identification , 1996 .
[7] Petre Stoica,et al. Decentralized Control , 2018, The Control Systems Handbook.
[8] Paul M. Frank,et al. Issues of Fault Diagnosis for Dynamic Systems , 2010, Springer London.
[9] Thomas Parisini,et al. Keynote paper: Fault diagnosis and neural networks: A power plant application , 1995 .
[10] Paul M. Frank,et al. Robust Observer-Based Fault Diagnosis in Non-Linear Uncertain Systems , 2000 .
[11] W. Cholewa,et al. Fault Diagnosis: Models, Artificial Intelligence, Applications , 2004 .
[12] Marcin Witczak,et al. Genetic programming based approaches to identification and fault diagnosis of non-linear dynamic systems , 2002 .
[13] Jie Chen,et al. Robust Model-Based Fault Diagnosis for Dynamic Systems , 1998, The International Series on Asian Studies in Computer and Information Science.
[14] Eric Walter,et al. Identification of Parametric Models: from Experimental Data , 1997 .
[15] Paul M. Frank,et al. Nonlinear observers for fault detection and isolation , 1999 .
[16] N. T. Russell,et al. Modular neural network modelling for long-range prediction of an evaporator , 2000 .
[17] Joseba Quevedo,et al. Development and Application of Methods for Actuator Diagnosis in Industrial Control Systems (DAMADICS): A Benchmark Study , 2003 .
[18] Sylviane Gentil,et al. Reformulation of parameter identification with unknown-but-bounded errors , 1988 .
[19] Józef Korbicz,et al. Observers and Genetic Programming in the Identification and Fault Diagnosis of Non-Linear Dynamic Systems , 2004 .
[20] Józef Korbicz,et al. A novel genetic programming approach to nonlinear system modelling: application to the DAMADICS benchmark problem , 2004, Eng. Appl. Artif. Intell..
[21] P. Laycock,et al. Optimum Experimental Designs , 1995 .
[22] Zbigniew Michalewicz,et al. Handbook of Evolutionary Computation , 1997 .
[23] Alan F. Murray,et al. Confidence estimation methods for neural networks : a practical comparison , 2001, ESANN.
[24] Sylviane Gentil,et al. Recursive membership estimation for output-error models , 1990 .
[25] Javier Segovia,et al. Parameter estimation of dynamic GMDH neural networks with the bounded-error technique , 2002 .
[26] H. Nijmeijer,et al. New directions in nonlinear observer design , 1999 .
[27] Joseba Quevedo,et al. Introduction to the DAMADICS actuator FDI benchmark study , 2006 .