Performance Analysis of SMDO Method with Benchmark Functions with Matlab Toolbox

Year 2020, Volume: 10 Issue: 4, 2451 - 2460, 15.12.2020

Mehmet Akpamukçu , Abdullah Ateş , Barış Baykant Alagöz

https://doi.org/10.21597/jist.722427

Abstract

SMDO method is a set and trial based optimization algorithm that is developed for online fine-tuning of controller parameters. SMDO method is implemented for several controller tuning applications. It can search parameter space with random backward and forward steps of each parameter. This property reduces risk of testing unstable control system configurations in controller design and thus makes the SMDO method more suitable for online parameter tuning of experimental systems. However, performance of SMDO has not been evaluated previously for benchmark functions in comparison with other well known heuristic optimization methods. This study aims to compare performances of Artificial Bee Colony (ABC), Cuckoo Search Optimization (CK), Particle Swarm Optimization (PSO) and Stochastic Multi-parameters Divergence Optimization (SMDO) methods for benchmark functions. Therefore, a benchmark tests program that is a user-friendly MATLAB GUI is introduced for user. This program can be downloaded from https://www.mathworks.com/matlabcentral/fileexchange/75043-smdo-method-with-benchmark-functions

Keywords

SMDO, optimization, stochastic, benchmark functions

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