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Lateral guidance control of a low-speed vehicle

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  1. Tez No: 708898
  2. Yazar: HAYDAR ŞAHİN
  3. Danışmanlar: PROF. DR. MİCHAEL P. HENNESSEY
  4. Tez Türü: Yüksek Lisans
  5. Konular: Makine Mühendisliği, Mechanical Engineering
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 1997
  8. Dil: İngilizce
  9. Üniversite: Rochester Institute of Technology
  10. Enstitü: Yurtdışı Enstitü
  11. Ana Bilim Dalı: Makine Mühendisliği Ana Bilim Dalı
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 119

Özet

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Özet (Çeviri)

This thesis examines the lateral guidance control of a low-speed vehicle. Several topics are studied in detail: (1) vehicle error-state model for lateral guidance based on Ackerman steering and (2) lateral guidance control of a low-speed vehicle using fuzzy logic. Independently written research papers address each topic. The first paper presents a second order“error-state”kinematic model based on Ackerman steering appropriate for studying the lateral guidance control of low-speed vehicles traversing on roads of constant curvature. Lateral guidance control of vehicles is of great interest to the Advanced Vehicle Control Systems (AVCS) Division of the Intelligent Transportation System (ITS) community. Both linear and nonlinear models are derived in detail. The error states considered are the vehicle's lateral error and heading error measured with respect to the instantaneous road centerline tangent. In addition to the derivation, both simulation and experimental results are presented with very good correspondence being achieved. The second paper investigates the performance of several different controllers used to perform lateral guidance control of a low-speed vehicle described as a linear nonminimum-phase“error-state”bicycle model based on Ackerman steering. Both a conventional type I proportional-integral (PI) controller and a fuzzy logic controller (FLC) are considered. The PI controller is designed using standard techniques and the two-level FLC / PI controller adjusts both proportional and integral feedback control gains around the baseline values based on heuristics and the current conditions as measured by the lateral error. Time-based simulations using MATLAB / SIMULINK permit a comparison between both controllers for several different simulation scenarios of interest. Primary performance metrics considered were percent overshoot and settling time in response to a step input. In general, the two-level FLC / PI controller performed better; 6 % reduction in overshoot and 21 % reduction in settling time.

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