Fuzzy Controller for MIMO Systems using Defuzzification based on Boolean Relations (DBR)

Soriano, Jairo; Olarte, A.; Melgarejo, Miguel

doi:10.1109/fuzzy.2005.1452405

Cited by 10 publications

(7 citation statements)

References 8 publications

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“…The difference between (1) and (2) is that the consequent is a function f i (x) in where the same variables of the antecedent take part, this allows one to apply in static and dynamic fuzzy systems multi-input-multi-output MIMO. The functions of the consequent f i (x) are chosen typically in terms of an appropriate parametric function, whose structure is equal for all the rules and they only vary the parameters.…”

Section: A Takagi-sugeno Modelsmentioning

confidence: 99%

“…Two cases appear, one: when in the function of equation 3 the terms of the consequent are null (b i =0), case that is called commonly homogenous model TS, and two: when the constant terms b i only are considered, to this model is denominated singleton model [7], or Sugeno model [3]. [2], [11] The algebra of Boole has been a powerful tool for the design of automatic systems [5]. Boolean logic basically evaluates the true predicates as one, and the false with a value of zero.…”

Section: A Takagi-sugeno Modelsmentioning

confidence: 99%

“…According to the annotation given by Soriano et al [2] the symbolÃ is A when it has a value of 1 andĀ when it is zero, reason why the global output (transfer characteristic) [16], can be expressed of compact way as:…”

Section: B Defuzification Based On Boolean Relations Dbrmentioning

confidence: 99%

See 2 more Smart Citations

Proposal of a minimal expression for nonlinear fuzzy approximation for the vapor liquid equilibrium VLE of the ethanol-water system at 560 mm Hg using defuzification based on Boolean Relations DBR and Singleton model.

Soriano

2009

NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society

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A novel methodology is presented in order to obtain a nonlinear correlation the vapor liquid equilibrium VLE of ethanol-water system at Bogotá conditions, using as nonlinear approximators the defuzification based on Boolean relations DBR, based on data obtained by thermodynamical correlations and compared with polynomial and Sugeno model in order to apply to the simulation of the distillation process.

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Section: A Takagi-sugeno Modelsmentioning

confidence: 99%

Section: A Takagi-sugeno Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Proposal of a minimal expression for nonlinear fuzzy approximation for the vapor liquid equilibrium VLE of the ethanol-water system at 560 mm Hg using defuzification based on Boolean Relations DBR and Singleton model.

Soriano

2009

NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society

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“…DBR (Defuzzification based on Boolean Relations) methodology used in this case, just as a defuzzification technique could be seen detailed in [1], now is applied to the VSC (Voltage Source Converter) HVDC system due to its simplicity and previous tests in other systems [10,11,12].…”

Section: Introductionmentioning

confidence: 99%

Active and reactive power flow fuzzy controller for VSC HVDC using DBR and DBR type 2

Chamorro¹,

Díaz²,

Soriano³

et al. 2010

2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-La)

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This document proposes a new defuzzfication methodology known as DBR (Defuzzification based on Boolean Relations), which is applied in this case, to a VSC HVDC system in order to control the active and reactive power flow. First, a brief dynamic study is presented in order to show the nonlinearities and the work operation range, next, is justified the theory application system of DBR and DBR type 2. These two methods are compared with a typical fuzzy logic controller in simulation and in a hardware power electronics prototype to verify the reliability of the controllers. Some performance indexes are evaluated in the time response of the system.

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“…The simulated results justified the performance of their proposed controller. Soriano 12 , et al presented a methodology for controlling a MIMO system using fuzzy logic controller. They developed the defuzzification based on Boolean relations (DBR) and showed that DBR allows implementing fuzzy controller with less computational cost.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of an Integrated Fuzzy Logic Controller for a Multi-input Multi-output System

Patil¹,

Bhaskar²,

Sudheer³

2011

DSJ

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The design and real time implementation of an integrated fuzzy logic controller (IFLC) for a multipleinput multiple-output (MIMO) system is presented. The design of IFLC for an uncoupled MIMO system has been discussed. This study develops a combination of fuzzy and PID controllers (PIDC) to improve the control performance of a two-input-two-output (TITO: angular position, and rotational speed) system. These parameters play a vital role in radar-tracking system for military applications. To verify the applicability of proposed controller, two-motor unit plant along with indigenously designed multi-channel analog interface board of 16-bit precision is used. The proposed MIMO control system is interfaced to a PC through its parallel port. The performance of the system is studied by subjecting it to various standard test signals. The IFLC performs better than the other two controllers in tracking the input command for linear as well as nonlinear inputs such as step, square, triangular, and sine waves is observed.

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Fuzzy Controller for MIMO Systems using Defuzzification based on Boolean Relations (DBR)

Cited by 10 publications

References 8 publications

Proposal of a minimal expression for nonlinear fuzzy approximation for the vapor liquid equilibrium VLE of the ethanol-water system at 560 mm Hg using defuzification based on Boolean Relations DBR and Singleton model.

Proposal of a minimal expression for nonlinear fuzzy approximation for the vapor liquid equilibrium VLE of the ethanol-water system at 560 mm Hg using defuzification based on Boolean Relations DBR and Singleton model.

Active and reactive power flow fuzzy controller for VSC HVDC using DBR and DBR type 2

Design and Implementation of an Integrated Fuzzy Logic Controller for a Multi-input Multi-output System

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