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.

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.

Decentralized robust evolving cloud-based controller for two input two output systems

2021 ◽  
pp. 014233122110492
Author(s):  
J Vijay Anand ◽  
PS Manoharan
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Fuzzy Rule ◽  
Single Input Single Output ◽  
Point Tracking ◽  
Single Output ◽  
Tito Systems

The fuzzy logic controller (FLC) makes it possible to control a system using IF-THEN rules through human intellect. It tackles parameter uncertainty using imprecise reasoning. The fuzzy logic controller is usually tuned using offline methods. An online evolving adaptation of fuzzy controller design is a recent trend in fuzzy rule-based systems. The robust evolving cloud-based controller (RECCo) is one such controller implemented for single-input-single-output (SISO) systems. The membership functions and consequent rules are automatically updated in real time based on the input data. In this paper, a decentralized robust evolving cloud-based controller (DRECCo) is proposed for two-input-two-output (TITO) systems. It consists of two independent loops with RECCos having a nonparametric premise facet and an adaptive proportional-integral-derivative (PID) model consequent facet. The effectiveness of the proposed method is validated for the benchmark interacting two-tank process (ITTP) and quadruple-tank process (QTP) by simulation and in real time. The results indicate that with the information of loop pairing and the forward-acting/reverse-acting nature of the process, the proposed controller can adapt itself to ensure set-point tracking and disturbance rejection.

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.

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