Improving the Performance of a Vibration Neutraliser by Controlling Its Stiffness and Damping

2000 ◽  
Author(s):  
M. J. Brennan ◽  
M. R. F. Kidner
Keyword(s):  
Experimental Study ◽  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Feedback System ◽  
Real Time Control ◽  
Velocity Feedback ◽  
Time Control ◽  
Operational Frequency ◽  
Stiffness And Damping

Abstract This paper is concerned with improving the performance of a vibration neutraliser (absorber) by making it adaptive. To achieve this, the stiffness and damping of the device has to be controlled so that the impedance of the neutraliser is optimised at its operational frequency. The results of an experimental study are presented where real-time control of such a device is demonstrated. The stiffness is adjusted by changing the geometry, and damping is controlled with a velocity feedback system. Both these actions are achieved using a fuzzy logic controller.

scholarly journals Innovative Strategy to Improve Precision and to Save Power of a Real-Time Control Process Using an Online Adaptive Fuzzy Logic Controller

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
R. Lasri ◽  
I. Rojas ◽  
H. Pomares ◽  
O. Valenzuela
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Control Process ◽  
Control Area ◽  
Real Time Control ◽  
Innovative Strategy ◽  
Adaptive Fuzzy ◽  
Time Control ◽  
Adaptive Fuzzy Logic

The main objective of this paper is to prove the great advantage that brings our novel approach to the intelligent control area. A set of various types of intelligent controllers have been designed to control the temperature of a room in a real-time control process in order to compare the obtained results with each other. Through a training board that allows us to control the temperature, all the used algorithms should present their best performances in this control process; therefore, our self-organized and online adaptive fuzzy logic controller (FLC) will be required to present great improvements in the control task and a real high control performance. Simulation results can show clearly that the new approach presented and tested in this work is very efficient. Thus, our adaptive and self-organizing FLC presents the best accuracy compared with the remaining used controllers, and, besides that, it can guarantee an important reduction of the power consumption during the control process.

scholarly journals An Optimized Multi-Output Fuzzy Logic Controller for Real-Time Control

2008 ◽  
Vol 12 (4) ◽  
pp. 370-376
Author(s):  
Noel S. Gunay ◽  
◽  
Elmer P. Dadios
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Time Lag ◽  
Real Time Control ◽  
Single Output ◽  
Time Control ◽  
Object Oriented Approach ◽  
Control Application

Any real-time control application run by a digital computer (or any sequential machine) demands a very fast processor in order to make the time-lag from data sensing to issuance of a control action closest to zero. In some instances, the algorithm used requires a relatively large primary memory which is crucial especially when implemented in a microcontroller. This paper presents a novel implementation of a multi-output fuzzy controller (which is known in this paper as MultiOFuz), which utilizes lesser memory and executes faster than a type of an existing multiple single-output fuzzy logic controllers. The design and implementation of the developed controller employed the object-oriented approach with program level code optimizations. MultiOFuz is a reusable software component and the simplicity of how to interface this to control applications is presented. Comparative analyses of algorithms, memory usage and simulations are presented to support our claim of increased efficiency in both execution time and storage use. Future directions of MultiOFuz are also discussed.

Fuzzy logic-based real-time control for a twin-rotor MIMO system using GA-based optimization

2018 ◽  
Vol 15 (2) ◽  
pp. 192-204 ◽  
Author(s):  
Arpit Jain ◽  
Satya Sheel ◽  
Piyush Kuchhal
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Mimo System ◽  
System Optimization ◽  
Mathematical Function ◽  
Real Time Control ◽  
Content Type ◽  
Time Control ◽  
Non Linear System ◽  
Twin Rotor

Purpose The purpose of this paper is to study the application of entropy based optimized fuzzy logic control for a real-time non-linear system. Optimization of the fuzzy membership function (MF) is one of the most explored areas for performance improvement of the fuzzy logic controllers (FLC). Conversely, majority of previous works are motivated on choosing an optimized shape for the MF, while on the other hand the support of fuzzy set is not accounted. Design/methodology/approach The proposed investigation provides the optimal support for predefined MFs by using genetic algorithms-based optimization of fuzzy entropy-based objective function. Findings The experimental results obtained indicate an improvement in the performance of the controller which includes improvement in error indices, transient and steady-state parameters. The applicability of proposed algorithm has been verified through real-time control of the twin rotor multiple-input, multiple-output system (TRMS). Research limitations/implications The proposed algorithm has been used for the optimization of triangular sets, and can also be used for the optimization of other fussy sets, such as Gaussian, s-function, etc. Practical implications The proposed optimization can be combined with other algorithms which optimize the mathematical function (shape), and a potent optimization tool for designing of the FLC can be formulated. Originality/value This paper presents the application of a new optimized FLC which is tested for control of pitch and yaw angles in a TRMS. The performance of the proposed optimized FLC shows significant improvement when compared with standard references.

On the Application of Fuzzy Logic in the Design of Supervisors for Real-Time Control Systems

1997 ◽  
Vol 30 (23) ◽  
pp. 9-14
Author(s):  
A. Fernández ◽  
M. Marcos ◽  
F. Artaza ◽  
N. Iriondo ◽  
D. Orive
Keyword(s):  
Fuzzy Logic ◽  
Control Systems ◽  
Real Time ◽  
Real Time Control ◽  
Time Control
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