Local feedback multilayered networks
Neural Computation
Neural networks for control systems: a survey
Automatica (Journal of IFAC)
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Fuzzy Modeling for Control
Neuro-Control and Its Applications
Neuro-Control and Its Applications
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Diagrammatic derivation of gradient algorithms for neural networks
Neural Computation
Conditions of output stabilization for nonlinear models in the Takagi--Sugeno's form
Fuzzy Sets and Systems
A recurrent fuzzy-neural model for dynamic system identification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Stabilizing controller design for uncertain nonlinear systems using fuzzy models
IEEE Transactions on Fuzzy Systems
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
Memory neuron networks for identification and control of dynamical systems
IEEE Transactions on Neural Networks
Non-model self-learning control of nonlinear system
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Multiple fuzzy neural networks modeling with sparse data
Neurocomputing
Engineering Applications of Artificial Intelligence
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
A library of nonlinearities for modeling and simulation of hybrid systems
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Indirect adaptive control with fuzzy neural networks via kernel smoothing
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Computational Intelligence - Volume Part II
Fuzzy model reference control with adaptation of input fuzzy sets
Knowledge-Based Systems
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The paper proposed to apply a hierarchical fuzzy-neural multi-model and Takagi-Sugeno (T-S) rules with recurrent neural procedural consequent part for systems identification, states estimation and adaptive control of complex nonlinear plants. The parameters and states of the local recurrent neural network models are used for a local direct and indirect adaptive trajectory tracking control systems design. The designed local control laws are coordinated by a fuzzy rule-based control system. The upper level defuzzyfication is performed by a recurrent neural network. The applicability of the proposed intelligent control system is confirmed by simulation examples and by a DC-motor identification and control experimental results. Two main cases of a reference and plant output fuzzyfication are considered-a two membership functions without overlapping and a three membership functions with overlapping. In both cases a good convergent results are obtained.