Universal approximation using radial-basis-function networks
Neural Computation
Nonlinear black-box modeling in system identification: a unified overview
Automatica (Journal of IFAC) - Special issue on trends in system identification
Fuzzy Modeling for Control
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
Dynamic system identification via recurrent multilayer perceptrons
Information Sciences—Informatics and Computer Science: An International Journal
Local Linear Model Trees for On-Line Identification of Time-Variant Nonlinear Dynamic Systems
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Fuzzy Model Identification for Control
Fuzzy Model Identification for Control
Survey paper: Optimal experimental design and some related control problems
Automatica (Journal of IFAC)
Nonlinear system identification: From multiple-model networks to Gaussian processes
Engineering Applications of Artificial Intelligence
Total least squares in fuzzy system identification: An application to an industrial engine
Engineering Applications of Artificial Intelligence
Predictive control of the heat exchanger using Local Model Network
MED '09 Proceedings of the 2009 17th Mediterranean Conference on Control and Automation
Data-driven fuzzy modeling for Takagi-Sugeno-Kang fuzzy system
Information Sciences: an International Journal
Identification of neurofuzzy models using GTLS parameter estimation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Editorial: Special issue on interpretable fuzzy systems
Information Sciences: an International Journal
Modified Gath-Geva fuzzy clustering for identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An approach to online identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On the interpretation and identification of dynamic Takagi-Sugeno fuzzy models
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
FLEXFIS: A Robust Incremental Learning Approach for Evolving Takagi–Sugeno Fuzzy Models
IEEE Transactions on Fuzzy Systems
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Local Model Network Identification With Gaussian Processes
IEEE Transactions on Neural Networks
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In this paper an evolving local model network (LMN) which is especially suited for engine modelling is presented and discussed. The incremental construction of the model tree allows to gradually increase the model complexity while a proper initialisation of new model parameters is easily possible when the LMN is extended. Especially in dynamic system identification the computational speed is an important requirement for online training. Therefore, a new evolving optimisation algorithm for the online training of the LMN is proposed which allows for a recursive computation of the model parameters. while the local interpretability of the consequent parameters is conserved. The decision when to grow the tree is based on an effective statistical criterion. The proposed concepts are validated by means of an illustrative example and by real dynamic measurement data from a state-of-the-art 4-cylinder EURO5 diesel engine.