META2010 META2010 Application of metaheuristics through MATLAB - - PowerPoint PPT Presentation

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META2010 META2010 Application of metaheuristics through MATLAB - - PowerPoint PPT Presentation

May 09, 2023 189 likes •451 views

META2010 META2010 Application of metaheuristics through MATLAB optimization toolboxes for the design of coupled resonator filters Jos-Ceferino Ortega Domingo Gimnez University of Murcia Alejandro lvarez-Melcn Fernando D. Quesada

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META2010 META2010 Application of metaheuristics through MATLAB optimization toolboxes for the design of coupled resonator filters

José-Ceferino Ortega Domingo Giménez

University of Murcia

Alejandro Álvarez-Melcón Fernando D. Quesada

Polytechnic University of Cartagena

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Content

Introduction Synthesis of coupled resonator filters MATLAB optimization toolboxes Experimental results Conclusions and future research

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  • Design problems in telecommunications
  • Optimization of design parameters
  • Design of coupled resonator filters
  • Used in microwave-based communications
  • Several phases:
  • Phase 1: obtain couplings matrix (design

technology)

  • Phase 2: obtain geometry (physical

design)

  • Hybridize local and global search methods
  • Environment: MATLAB

Introduction

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Content

Introduction Synthesis of coupled resonator filters MATLAB optimization toolboxes Experimental results Conclusions and future research

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Synthesis of filters (I)

  • Analysis of the problem of synthesis
  • f coupled resonators filters

 Filters based on coupled microwave

resonators

 Technological design: couplings matrix  Characteristics of the filters:

 Transfer function  Topology (Kite, Transversal, 2-Trisection

  • rd. 3)

 Number of design parameters (8 or 9)  Range of values (from -5 to 5)

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Synthesis of filters (II)

2 Trisection ord. 3, zeros

  • 5 and -3

Kite, zeros -3 and 3

  • 10
  • 8
  • 6
  • 4
  • 2

2 4 6 8 10

  • 100
  • 90
  • 80
  • 70
  • 60
  • 50
  • 40
  • 30
  • 20
  • 10

In s11 In s21

  • 10
  • 8
  • 6
  • 4
  • 2

2 4 6 8 10

  • 70
  • 60
  • 50
  • 40
  • 30
  • 20
  • 10

In s11 In s21

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Synthesis of filters (III)

Kite, Kite, fitness fitness 10 10-13

  • 13

Kite, Kite, fitness

fitness 10

10-5

  • 5

Kite, Kite, fitness fitness 10 10-1

  • 1
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Content

Introduction Synthesis of coupled resonator filters MATLAB optimization toolboxes Experimental results Conclusions and future research

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MATLAB optimization toolboxes

  • MATLAB Optimization Toolboxes

 Optimization Toolbox

 fmincon

 Genetic Algorithm and Direct Search

Toolbox

 Direct search (patternsearch)  Genetic algorithms (ga)  Simulated annealing (simulannealbnd)

  • and Scatter Search
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Content

Introduction Synthesis of coupled resonator filters MATLAB optimization toolboxes Experimental results Conclusions and future research

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Experimental results: fmincon

  • fmincon

 Part of the MATLAB Optimization Toolbox  Local search  Parameters to study:

 LargeScale  Algorithm

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Experimental results: fmincon

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Experimental results: patternsearch

  • patternsearch (Direct search)

 MATLAB Direct Search and Genetic

Algorithm Toolbox

 Local search  Parameters to study:

 InitialMeshSize  MeshContraction  MeshExpansion  ScaleMesh  PollMethod  CompletePoll  PollingOrder  SearchMethod  CompleteSearch

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Experimental results: patternsearch

SearchMethod & CompleteSearch PollMethod CompletePoll

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Experimental results: genetic algorithm

  • ga (Genetic algorithms)

 MATLAB Direct Search and Genetic

Algorithm Toolbox

 Global search  Parameters to study:

 PopulationSize and Generations  EliteCount and CrossoverFraction  FitnessScalingFcn and SelectionFcn  CrossoverFcn and MutationFcn  CreationFcn and HybridFcn

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Experimental results: genetic algorithm

standard functions

SelectionFnc CrossoverFnc

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Experimental results: genetic algorithm

personalized functions

CreationFnc CrossoverFnc MutationFnc HybridFnc

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Experimental results: genetic algorithm

personalized functions exec. time –

HybridFnc CreationFnc MutationFnc

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Experimental results: simulated annealing

  • simulannealbnd (Simulated

annealing)

 MATLAB Direct Search and Genetic

Algorithm Toolbox

 Local search  Parameters to study:

 AnnealingFcn  InitialTemperature  ReannealInterval  TemperatureFcn  HybridFcn and HybridInterval

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Experimental results: simulated annealing

fitness

AnnealingFnc TemperatureFnc HybridFnc & HybridInterval

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Experimental results: comparison

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Content

Introduction Synthesis of coupled resonator filters MATLAB optimization toolboxes Experimental results Conclusions and future research

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Conclusions

  • Evaluated the application to the

design of coupled resonator filters of available tools in the toolboxes of MATLAB

  • Local and global search methods

hybridation, with Genetic algorithms and Scatter Search

  • The best: ga (Genetic algorithm)

personalized

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Future research

  • Application to the physical design (2nd

phase), with more computational cost. The 1st phase simplifies the physical design.

  • Application of other metaheuristics and

implementation in MATLAB.

  • Study of relation between technological

and physical design, to divide the physical design in smaller problems.

  • Application of parallelism, specially in the

2nd phase: parallel metaheuristics and parallelism in the computation of the fitness function (matricial computation).

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Thanks

Questions? Questions?