Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Fuzzy adaptive control for a class of nonlinear systems
Fuzzy Sets and Systems
Stable Adaptive Neural Network Control
Stable Adaptive Neural Network Control
Journal of Intelligent and Robotic Systems
A fast learning algorithm for parismonious fuzzy neural systems
Fuzzy Sets and Systems - Information processing
Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximation Techniques
Direct Adaptive Fuzzy Control with Less Restrictions on the Control Gain
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
Direct adaptive self-structuring fuzzy controller for nonaffine nonlinear system
Fuzzy Sets and Systems
An approach to online identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
Stable multi-input multi-output adaptive fuzzy/neural control
IEEE Transactions on Fuzzy Systems
Adaptive fuzzy-based tracking control for nonlinear SISO systems via VSS and H∞ approaches
IEEE Transactions on Fuzzy Systems
Self-constructing fuzzy neural network speed controller for permanent-magnet synchronous motor drive
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Adaptive neural/fuzzy control for interpolated nonlinear systems
IEEE Transactions on Fuzzy Systems
Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems
IEEE Transactions on Fuzzy Systems
Structure identification of generalized adaptive neuro-fuzzy inference systems
IEEE Transactions on Fuzzy Systems
Two-Mode Adaptive Fuzzy Control With Approximation Error Estimator
IEEE Transactions on Fuzzy Systems
Direct adaptive NN control of a class of nonlinear systems
IEEE Transactions on Neural Networks
Direct adaptive controller for nonaffine nonlinear systems using self-structuring neural networks
IEEE Transactions on Neural Networks
Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems
IEEE Transactions on Neural Networks
Mean-based fuzzy identifier and control of uncertain nonlinear systems
Fuzzy Sets and Systems
Nonlinear identification and adaptive control based on self-structuring fuzzy systems
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
International Journal of Applied Mathematics and Computer Science - Special Section: Robot Control Theory Cezary Zielinski
Robust L2-gain compensative control for direct-adaptive fuzzy-control-system design
IEEE Transactions on Fuzzy Systems
An algorithm for online self-organization of fuzzy controllers
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Survey paper: A survey on industrial applications of fuzzy control
Computers in Industry
Information Sciences: an International Journal
New Online Self-Evolving Neuro Fuzzy controller based on the TaSe-NF model
Information Sciences: an International Journal
Fuzzy model reference control with adaptation of input fuzzy sets
Knowledge-Based Systems
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This paper presents a direct self-structuring adaptive fuzzy control (DSAFC) scheme for affine nonlinear single-input-single-output systems. We show that the only restriction on the control gain is that it be positive. No upper bound on this gain nor its derivative needs to be known. From an initial fuzzy system with a small number of rules, the self-structuring algorithm adds membership functions and rules when needed. To limit the size of the fuzzy system from growing indefinitely, the self-structuring algorithm replaces old membership functions by new ones instead of adding more membership functions so that the number of rules never exceeds a predefined upper bound. The stability of the closed loop system is guaranteed using the Lyapunov synthesis approach. The proposed control scheme is demonstrated by application to an inverted pendulum and a magnetic levitation system.