Autonomous Drift Modeling, Planning and Control

碩士 === 國立成功大學 === 航空太空工程學系 === 106 === Drifting represents an extreme maneuver that is beyond the skill set of the average people, requiring skillful timing of pedal brake, handbrake and steering wheel. Driver causes the vehicle to rotate rapidly and slide, into the unstable situation. This paper in...

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Main Authors: Ya-DeHsieh, 謝雅德
Other Authors: Jiun-Haur Tarn
Format: Others
Language:en_US
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/t2r67n
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spelling ndltd-TW-106NCKU52950532019-05-16T01:07:59Z http://ndltd.ncl.edu.tw/handle/t2r67n Autonomous Drift Modeling, Planning and Control 自主飄移的建模,規劃與控制 Ya-DeHsieh 謝雅德 碩士 國立成功大學 航空太空工程學系 106 Drifting represents an extreme maneuver that is beyond the skill set of the average people, requiring skillful timing of pedal brake, handbrake and steering wheel. Driver causes the vehicle to rotate rapidly and slide, into the unstable situation. This paper investigates the analysis of unstable drifting condition, equilibrium point analysis and identify the slip vehicle model, in order to propose a control strategy to make automatically drifting possible. The parameters for the model are identified in Chapter 3 & 4 and the simulation results of the modelled vehicle are compared to measured experimental data. When talking about the high side-slip maneuvers, it falls into one of two categories: sustained drift and transient drift. Sustained drift focuses on stabilizing the vehicle around an unstable equilibrium (also call steady state circular drifting), while transient drift focuses on entirely maintaining a drift state. To the authors’ knowledge, all experimental validation for drift control algorithms have used a motion capture system or a differential GPS system. However, due to the reality consideration, here use only the Extended Kalman Filter with necessary sensors to estimate the system state. For the purpose of presenting a steady state drifting, the modelled vehicle equilibrium point analysis is discussed in Chapter 5. Then a Linear Quadratic Regulator control algorithm is designed to control the system from normal stable situation into unstable drifting condition in simulation. In experiment, the Model Predictive Control is implement on the 1:10 RC car to achieve transient autonomous drift, and the details will be discussed in Chapter 6. Jiun-Haur Tarn 譚俊豪 2018 學位論文 ; thesis 60 en_US
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description 碩士 === 國立成功大學 === 航空太空工程學系 === 106 === Drifting represents an extreme maneuver that is beyond the skill set of the average people, requiring skillful timing of pedal brake, handbrake and steering wheel. Driver causes the vehicle to rotate rapidly and slide, into the unstable situation. This paper investigates the analysis of unstable drifting condition, equilibrium point analysis and identify the slip vehicle model, in order to propose a control strategy to make automatically drifting possible. The parameters for the model are identified in Chapter 3 & 4 and the simulation results of the modelled vehicle are compared to measured experimental data. When talking about the high side-slip maneuvers, it falls into one of two categories: sustained drift and transient drift. Sustained drift focuses on stabilizing the vehicle around an unstable equilibrium (also call steady state circular drifting), while transient drift focuses on entirely maintaining a drift state. To the authors’ knowledge, all experimental validation for drift control algorithms have used a motion capture system or a differential GPS system. However, due to the reality consideration, here use only the Extended Kalman Filter with necessary sensors to estimate the system state. For the purpose of presenting a steady state drifting, the modelled vehicle equilibrium point analysis is discussed in Chapter 5. Then a Linear Quadratic Regulator control algorithm is designed to control the system from normal stable situation into unstable drifting condition in simulation. In experiment, the Model Predictive Control is implement on the 1:10 RC car to achieve transient autonomous drift, and the details will be discussed in Chapter 6.
author2 Jiun-Haur Tarn
author_facet Jiun-Haur Tarn
Ya-DeHsieh
謝雅德
author Ya-DeHsieh
謝雅德
spellingShingle Ya-DeHsieh
謝雅德
Autonomous Drift Modeling, Planning and Control
author_sort Ya-DeHsieh
title Autonomous Drift Modeling, Planning and Control
title_short Autonomous Drift Modeling, Planning and Control
title_full Autonomous Drift Modeling, Planning and Control
title_fullStr Autonomous Drift Modeling, Planning and Control
title_full_unstemmed Autonomous Drift Modeling, Planning and Control
title_sort autonomous drift modeling, planning and control
publishDate 2018
url http://ndltd.ncl.edu.tw/handle/t2r67n
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