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Journal ArticleDOI

A self-organizing fuzzy logic controller for the active control of flexible structures using piezoelectric actuators

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TLDR
The validity of the proposed fuzzy logic control has been demonstrated experimentally in a steel cantilever test beam and a set of experimental tests are made in the system to verify the efficiency of the on-line self-organizing fuzzy controller.
About
This article is published in Applied Soft Computing.The article was published on 2002-05-01. It has received 47 citations till now. The article focuses on the topics: Fuzzy logic & Fuzzy control system.

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Citations
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Journal ArticleDOI

Active Structural Vibration Control: A Review

TL;DR: In this article, the authors present a generic procedure to the design process and give selective examples from the literature on relevant ma- terial, together with examples of their applications, such as structure modeling, model reduction, feedback control, feedforward control, con- trollability and observability, spillover, eigenstructure assign- ment (pole placement), coordinate coupling control, robust control, optimal control, state observers (estimators), intelli- gent structure and controller, adaptive control, time delay, actuator-structure interaction, and optimal placement of actuators
Journal ArticleDOI

Experimental evaluation of a piezoelectric vibration absorber using a simplified fuzzy controller in a cantilever beam

TL;DR: In this article, a resonant fuzzy logic controller (FLC) was proposed to minimize structural vibration using collocated piezoelectric actuator/sensor pairs, which increases the damping of the structures to minimize certain resonant responses.
Journal ArticleDOI

A vibration absorber of smart structures using adaptive networks in hierarchical fuzzy control

TL;DR: The proposed controller in this research combines the strength of fuzzy systems, the able to deal with uncertainties, with the advantage of neural nets, the ability to learn.
Journal ArticleDOI

An active vibration absorber of smart panel by using a decomposed parallel fuzzy control structure

TL;DR: This study attempts to demonstrate the general methodology by decomposing a large-scale system into smaller subsystems in a parallel structure so that the proposed fuzzy control methodology developed here can be applied for studying a complex system.
Journal ArticleDOI

Feedforward neural network position control of a piezoelectric actuator based on a BAT search algorithm

TL;DR: A combined approach by using a feedforward neural network jointly with a BAT search algorithm in order to improve the positional control of an X-PEA mechanism model by also taking into account the hysteresis behavior is applied.
References
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Book

Numerical Analysis

TL;DR: This report contains a description of the typical topics covered in a two-semester sequence in Numerical Analysis, and describes the accuracy, efficiency and robustness of these algorithms.
Journal ArticleDOI

Fuzzy logic in control systems: fuzzy logic controller. II

TL;DR: The basic aspects of the FLC (fuzzy logic controller) decision-making logic are examined and several issues, including the definitions of a fuzzy implication, compositional operators, the interpretations of the sentence connectives 'and' and 'also', and fuzzy inference mechanisms, are investigated.
Journal Article

Fuzzy logic in control systems : fuzzy logic controller. Part II

TL;DR: The fuzzy logic controller (FLC) based on fuzzy logic provides a means of converting a linguistic control strategy based on expert knowledge into an automatic control strategy.
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Use of piezoelectric actuators as elements of intelligent structures

TL;DR: In this paper, a scaling analysis is performed to demonstrate that the effectiveness of actuators is independent of the size of the structure and evaluate various piezoelectric materials based on their effectiveness in transmitting strain to the substructure.
Journal ArticleDOI

Fuzzy self-organizing controller and its application for dynamic processes

TL;DR: A new self-organizing control algorithm which modifies the fuzzy control decision table is presented in this paper, which shows that the controller can be applied to some processes, such as processes with time lag and non-linearity or one whose parameter or running conditions are varied.