DEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION

In this manuscript, we present an approach for selecting appropriate weighting matrices for optimal tracking control design using adaptive particle swarm optimization (APSO), applied to landing flare system. First, we develop a linearized state space model based on longitudinal motion of aircraft...

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Main Author:	Mu'tamar, Khozin
Format:	Theses
Language:	Indonesia
Online Access:	https://digilib.itb.ac.id/gdl/view/34149
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Institution:	Institut Teknologi Bandung
Language:	Indonesia

id	id-itb.:34149
spelling	id-itb.:341492019-02-04T15:40:51ZDEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION Mu'tamar, Khozin Indonesia Theses adaptive particle swarm optimization, multi global best, weighting matrices, optimal tracking control INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/34149 In this manuscript, we present an approach for selecting appropriate weighting matrices for optimal tracking control design using adaptive particle swarm optimization (APSO), applied to landing flare system. First, we develop a linearized state space model based on longitudinal motion of aircraft. Next, based on LQR, controller for optimal tracking is developed. APSO is used to improve control performance by selecting appropriate weighting matrices. APSO is modified standard PSO which have multi global best that weighted using Mamdani fuzzy model. Simulation is given to illustrate the design procedure and to show comparation of tracking performance between APSO and standard PSO. text
institution	Institut Teknologi Bandung
building	Institut Teknologi Bandung Library
continent	Asia
country	Indonesia Indonesia
content_provider	Institut Teknologi Bandung
collection	Digital ITB
language	Indonesia
description	In this manuscript, we present an approach for selecting appropriate weighting matrices for optimal tracking control design using adaptive particle swarm optimization (APSO), applied to landing flare system. First, we develop a linearized state space model based on longitudinal motion of aircraft. Next, based on LQR, controller for optimal tracking is developed. APSO is used to improve control performance by selecting appropriate weighting matrices. APSO is modified standard PSO which have multi global best that weighted using Mamdani fuzzy model. Simulation is given to illustrate the design procedure and to show comparation of tracking performance between APSO and standard PSO.
format	Theses
author	Mu'tamar, Khozin
spellingShingle	Mu'tamar, Khozin DEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION
author_facet	Mu'tamar, Khozin
author_sort	Mu'tamar, Khozin
title	DEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION
title_short	DEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION
title_full	DEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION
title_fullStr	DEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION
title_full_unstemmed	DEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION
title_sort	defining weighting matrices on optimal tracking control using adaptive particle swarm optimization
url	https://digilib.itb.ac.id/gdl/view/34149
_version_	1821996682343088128

DEFINING WEIGHTING MATRICES ON OPTIMAL TRACKING CONTROL USING ADAPTIVE PARTICLE SWARM OPTIMIZATION

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