Search Paper
  • Home
  • Login
  • Categories
  • Post URL
  • Academic Resources
  • Contact Us

 

State Drift and Gait Plan in Feedback Linearization Control of A Tilt Vehicle

google+
Views: 396                 

Author :  Zhe Shen, Takeshi Tsuchiya

Affiliation :  The University of Tokyo

Country :  Japan

Category :  Robotics

Volume, Issue, Month, Year :  12, 5, March, 2022

Abstract :


To stabilize a conventional quadrotor, simplified equivalent vehicles (e.g., autonomous car) are developed to test the designed controller. Based on that, various controllers based on feedback linearization have been developed. With the recently developed concept of tilt-rotor, there lacks the simplified/equivalent model, however. Indeed, the tilt structure is relatively unusual in vehicles. In this research, we put forward a unique fictional vehicle with tilt structure, which is to help evaluate the property of the tilt-structure-aimed controllers. One phenomenon (state drift) in controlling an over-actuated tilt structure by feedback linearization is presented subsequently. State drift can be easily neglected and is not paid attention to in the current researches in tilt-rotor controllers’ design so far. We report this phenomenon and provide a potential approach to avoid this behavior.

Keyword :  Feedback Linearization, State Drift, Over-actuated System, Gait Plan, Stability

Journal/ Proceedings Name :  Computer Science & Information Technology (CS & IT)

URL :  https://aircconline.com/csit/papers/vol12/csit120501.pdf

User Name : Shen
Posted 24-03-2022 on 23:45:40 AEDT



Related Research Work

  • Edge Detection Algorithm For Yoruba Character Recognition
  • Pursuit-evasion Game Modelling In A Graph Using Petri Nets
  • Performance Evaluation On Unipolar Pwm Strategies For Three Phase Diode Clamped Multilevel Inverter
  • Design And Development Of A Lead Screw Gripper For Robotic Application

About Us | Post Cfp | Share URL Main | Share URL category | Post URL
All Rights Reserved @ Call for Papers - Conference & Journals