Results 311 to 320 of about 399,950 (349)

Fuzzy T-S Modeling and Fuzzy Control Research on Networked Control Systems

2007 IEEE International Conference on Automation and Logistics, 2007
To solve the stability control problem of Networked Control Systems (NCS) with time delay, a new method of building a discrete fuzzy T-S model is proposed for NCS generalized plant, and the model is proved theoretically to be able to approach a real plant at an arbitrary precision.
Huiling Mu, Guimei Cui, Zhichun Mu, Xiaoli Li   +3 more
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Fuzzy modeling of control systems

IEEE Transactions on Aerospace and Electronic Systems, 1995
A new approach is described for fuzzy modeling of control systems. It is shown that conventional concepts and criteria of stability and controllability of a control system can be extended to a fuzzy setting. More precisely, we establish a fuzzy dynamical model for nonlinear control system, that can be consistently applied to all linear multiinput ...
J.J. Weiss, T.T. Pham, Guanrong Chen
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Averaging in fuzzy controlled systems

Nonlinear Oscillations, 2012
We consider the applicability of the scheme of complete averaging to control problems with terminal quality criterion in the case where the behavior of the system is described by a controlled fuzzy differential equation.
N. V. Skripnik, Tatyana A. Komleva, L. I. Plotnikova, Andrej V. Plotnikov   +3 more
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Stability of fuzzy control systems

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), 2002
Stability of a class of fuzzy control systems is analyzed by replacing the fuzzy controller with an appropriate describing function. Nonlinear analytical expressions for fuzzy controllers are derived. These expressions are numerically approximated by describing functions.
Celal Batur, Thananchai Leephakpreeda
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Impulsive Control of T-S Fuzzy Systems

Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007
This paper provides a new viewpoint for fuzzy systems via an impulsive technique, i.e. the impulsive control is introduced into the fuzzy systems based on T-S model and the fuzzy system model with impulsive control is established. The main difference between the proposed control strategy and PDC lies in that the subsystems are the linear impulsive ones
Dan Yang, Xiaohong Zhang, Dong Li
openaire   +1 more source

Expert Systems and Fuzzy Control

1985
During the last two centuries the potential of electronic data processing (EDP) has been used to an increasing degree to support human decision making in different ways. In the sixties the management informations systems (MIS) created probably exaggerated hopes of managers. Since the late 1970s and early 1980s decision support systems (DSS) found their
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Fuzzy systems and fuzzy expert control: An overview

The Knowledge Engineering Review, 1994
AbstractThis paper presents an overview of fuzzy set theory and its application to the analysis and design of fuzzy expert control systems. Starting with a short account of the basic concepts and properties of fuzzy sets and fuzzy reasoning, a few fuzzy rule-based controllers, viz, basic single-input singleoutput fuzzy control, self-organizing fuzzy ...
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Robust Control for T-S Fuzzy Systems

2019
T-S fuzzy models with actuator saturation and norm-bounded uncertainties have been used to describe nonlinear systems subject to actuator saturation in [10]. An overhead crane model has been described by a class of T-S fuzzy systems with input delays and actuator saturation in [193].
Hongjiu Yang, Yuanqing Xia, Qing Geng
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Calibration of fuzzy control systems

Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference, 2002
Fuzzy control systems (FCS) are usually designed through linguistic control rules and the operations among the fuzzy sets that define the fuzzy controller deal with fuzzy logic. However, the configuration and tuning of this kind of system represents a problem, although the modelling of the expert knowledge seems easy.
Agustín Jiménez, G. Martinez, Fernando Matía   +2 more
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Modelling on fuzzy control systems

Science China Mathematics, 2002
A kind of modelling method for fuzzy control systems is first proposed here, which is called modelling method based on fuzzy inference (MMFI). It should be regarded as the third modelling method that is different from two well-known modelling methods, that is, the first modelling method, mechanism modelling method (MMM), and the second modelling method,
Wang Jiayin, Miao Zhihong, LI Hong-xing
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