Recurrent Neuro-Fuzzy Modeling and Fuzzy MDPP Control for Flexible Servomechanisms
Journal of Intelligent and Robotic Systems
Optimal Control of Fed-Batch Processes Based on Multiple Neural Networks
Applied Intelligence
Evolution of Voronoi based fuzzy recurrent controllers
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
State-Space Recurrent Fuzzy Neural Networks for Nonlinear System Identification
Neural Processing Letters
A self-organizing feature map-driven approach to fuzzy approximate reasoning
Expert Systems with Applications: An International Journal
An adaptive recurrent fuzzy system for nonlinear identification
Applied Soft Computing
Nonlinear active noise control using EKF-based recurrent fuzzy neural networks
International Journal of Hybrid Intelligent Systems
Nonlinear Systems Identification via Two Types of Recurrent Fuzzy CMAC
Neural Processing Letters
A Model Predictive Control of a Grain Dryer with Four Stages Based on Recurrent Fuzzy Neural Network
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Recurrent Fuzzy CMAC for Nonlinear System Modeling
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
A new pseudo-Gaussian-based recurrent fuzzy CMAC model for dynamic systems processing
International Journal of Systems Science
Dynamic programming prediction errors of recurrent neural fuzzy networks for speech recognition
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Recurrent neuro fuzzy control design for tracking of mobile robots via hybrid algorithm
Expert Systems with Applications: An International Journal
Recurrent neuro-fuzzy system for fault detection and isolation in nuclear reactors
Advanced Engineering Informatics
Fundamentals of a fuzzy-logic-based generalized theory of stability
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
A recurrent fuzzy filter for the analysis of lung sounds
Fuzzy Sets and Systems
A recurrent self-evolving interval type-2 fuzzy neural network for dynamic system processing
IEEE Transactions on Fuzzy Systems
A locally recurrent fuzzy neural network with support vector regression for dynamic-system modeling
IEEE Transactions on Fuzzy Systems
Qualitative modeling of dynamical systems employing continuous-time recurrent fuzzy systems
Fuzzy Sets and Systems
Recurrent fuzzy system design using elite-guided continuous ant colony optimization
Applied Soft Computing
Intelligent optimal control in rare-earth countercurrent extraction process via soft-sensor
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Identification of dynamic systems using recurrent fuzzy wavelet network
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
A multi-model approach for long-term runoff modeling using rainfall forecasts
Expert Systems with Applications: An International Journal
Recurrent wavelet-based neuro fuzzy networks for dynamic system identification
Mathematical and Computer Modelling: An International Journal
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A type of recurrent neuro-fuzzy network is proposed in this paper to build long-term prediction models for nonlinear processes. The process operation is partitioned into several fuzzy operating regions. Within each region, a local linear model is used to model the process. The global model output is obtained through the centre of gravity defuzzification which is essentially the interpolation of local model outputs. This modeling strategy utilizes both process knowledge and process input/output data. Process knowledge is used to initially divide the process operation into several fuzzy operating regions and to set up the initial fuzzification layer weights. Process I/O data are used to train the network. Network weights are such trained so that the long-term prediction errors are minimized. Through training, membership functions of fuzzy operating regions are refined and local models are learnt. Based on the recurrent neuro-fuzzy network model, a novel type of nonlinear model-based long range predictive controller can be developed and it consists of several local linear model-based predictive controllers. Local controllers are constructed based on the corresponding local linear models and their outputs are combined to form a global control action by using their membership functions. This control strategy has the advantage that control actions can be calculated analytically avoiding the time consuming nonlinear programming procedures required in conventional nonlinear model-based predictive control. The techniques have been successfully applied to the modeling and control of a neutralization process