LAPSE:2019.0486
Published Article
LAPSE:2019.0486
FFANN Optimization by ABC for Controlling a 2nd Order SISO System’s Output with a Desired Settling Time
April 9, 2019
In this study, a control strategy is aimed to ensure the settling time of a 2nd order system’s output value while its input reference value is changed. Here, Feed Forward Artificial Neural Network (FFANN) nonlinear structure has been chosen as a control algorithm. In order to implement the intended control strategy, FFANN’s normalization coefficient (K), learning coefficients (ŋ), momentum coefficients (μ) and the sampling time (Ts) were optimized by Artificial Bee Colony (ABC) but FFANN’s values of weights were chosen arbitrary on start time of control system. After optimization phase, the FFANN behaves as an adaptive optimal discrete time non-linear controller that forces the system output to take the same value with the input reference for a desired settling time (ts). The success of the optimization algorithm was proved with close loop feedback control simulations on Matlab’s Simulink platform based on 2nd order transfer functions. Also, the success was proved with a 2nd order physical system (buck converter) that was structured with power electronics elements on Simulink platform. Finally, the success of the control process was discussed by observing results.
Record ID
Keywords
ABC, buck converter, control, FFANN, Modelling, Optimization, settling time
Subject
Suggested Citation
Mühürcü A. FFANN Optimization by ABC for Controlling a 2nd Order SISO System’s Output with a Desired Settling Time. (2019). LAPSE:2019.0486
Author Affiliations
Journal Name
Processes
Volume
7
Issue
1
Article Number
E4
Year
2018
Publication Date
2018-12-21
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr7010004, Publication Type: Journal Article
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Published Article
LAPSE:2019.0486
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doi:10.3390/pr7010004
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[v1] (Original Submission)
Apr 9, 2019
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Apr 9, 2019
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v1
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https://psecommunity.org/LAPSE:2019.0486
Original Submitter
Calvin Tsay
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