ANTI-JACKKNIFE CONTROL FOR AUTONOMOUS TRUCK TRAILER PATH FOLLOWING USING PARTICLE SWARM OPTIMIZATION (PSO) AND GENETIC ALGORITHM (GA)

Controlling an autonomous trailer truck system is difficult due to the two rigid parts of the truck (Head and Trailer) and the high probability of a jackknife effect occurring. One of the causes of the jackknife effect is because the speed of the truck is too high or the truck's aggressive beha...

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Main Author: Afghan Fadillah R, M
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/62250
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:62250
spelling id-itb.:622502021-12-23T09:31:54ZANTI-JACKKNIFE CONTROL FOR AUTONOMOUS TRUCK TRAILER PATH FOLLOWING USING PARTICLE SWARM OPTIMIZATION (PSO) AND GENETIC ALGORITHM (GA) Afghan Fadillah R, M Indonesia Theses autonomous truck-trailler, PSO, GA, pinalty function, jack-knife effect. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/62250 Controlling an autonomous trailer truck system is difficult due to the two rigid parts of the truck (Head and Trailer) and the high probability of a jackknife effect occurring. One of the causes of the jackknife effect is because the speed of the truck is too high or the truck's aggressive behavior when turning. The purpose of this research is to design a control that can avoid the jackknife effect. The method used to avoid this effect is to find the variable value from the tuning results using the constrained optimization method. The optimization methods used are Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) with the objective function being the minimum of Integral Absolute Error (IAE) which has a limit value of maximum steering angle, ?????5?????? ?????????5 and maximum angle between head and trailer, ?????5?????? ????,????? ?????5. A penalty method is proposed to turn a constrained problem into an unconstrained problem. The results showed that by selecting the correct penalty parameter value (?_k), the objective function using the penalty method was able to obtain the value of [???????????? ????????,???????? ????????,?????]????, which caused the system to not have a jackknife effect (it does not exceed the specified limit value). Based on the performance value, that the best result of the value of [???????????? ????????,???????? ????????,?????]????obtained is using the Genetic Algorithm (GA) method with the IAE performance index value of 3688,56, ISE of 3406,79 and ITAE for 2872914 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 Controlling an autonomous trailer truck system is difficult due to the two rigid parts of the truck (Head and Trailer) and the high probability of a jackknife effect occurring. One of the causes of the jackknife effect is because the speed of the truck is too high or the truck's aggressive behavior when turning. The purpose of this research is to design a control that can avoid the jackknife effect. The method used to avoid this effect is to find the variable value from the tuning results using the constrained optimization method. The optimization methods used are Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) with the objective function being the minimum of Integral Absolute Error (IAE) which has a limit value of maximum steering angle, ?????5?????? ?????????5 and maximum angle between head and trailer, ?????5?????? ????,????? ?????5. A penalty method is proposed to turn a constrained problem into an unconstrained problem. The results showed that by selecting the correct penalty parameter value (?_k), the objective function using the penalty method was able to obtain the value of [???????????? ????????,???????? ????????,?????]????, which caused the system to not have a jackknife effect (it does not exceed the specified limit value). Based on the performance value, that the best result of the value of [???????????? ????????,???????? ????????,?????]????obtained is using the Genetic Algorithm (GA) method with the IAE performance index value of 3688,56, ISE of 3406,79 and ITAE for 2872914
format Theses
author Afghan Fadillah R, M
spellingShingle Afghan Fadillah R, M
ANTI-JACKKNIFE CONTROL FOR AUTONOMOUS TRUCK TRAILER PATH FOLLOWING USING PARTICLE SWARM OPTIMIZATION (PSO) AND GENETIC ALGORITHM (GA)
author_facet Afghan Fadillah R, M
author_sort Afghan Fadillah R, M
title ANTI-JACKKNIFE CONTROL FOR AUTONOMOUS TRUCK TRAILER PATH FOLLOWING USING PARTICLE SWARM OPTIMIZATION (PSO) AND GENETIC ALGORITHM (GA)
title_short ANTI-JACKKNIFE CONTROL FOR AUTONOMOUS TRUCK TRAILER PATH FOLLOWING USING PARTICLE SWARM OPTIMIZATION (PSO) AND GENETIC ALGORITHM (GA)
title_full ANTI-JACKKNIFE CONTROL FOR AUTONOMOUS TRUCK TRAILER PATH FOLLOWING USING PARTICLE SWARM OPTIMIZATION (PSO) AND GENETIC ALGORITHM (GA)
title_fullStr ANTI-JACKKNIFE CONTROL FOR AUTONOMOUS TRUCK TRAILER PATH FOLLOWING USING PARTICLE SWARM OPTIMIZATION (PSO) AND GENETIC ALGORITHM (GA)
title_full_unstemmed ANTI-JACKKNIFE CONTROL FOR AUTONOMOUS TRUCK TRAILER PATH FOLLOWING USING PARTICLE SWARM OPTIMIZATION (PSO) AND GENETIC ALGORITHM (GA)
title_sort anti-jackknife control for autonomous truck trailer path following using particle swarm optimization (pso) and genetic algorithm (ga)
url https://digilib.itb.ac.id/gdl/view/62250
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