Motorized Testbed for Automated Rc Vehicle Control

Open Access
Author:
Fernando, Raveen Lasantha
Area of Honors:
Mechanical Engineering
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
  • Sean Brennan, Thesis Supervisor
  • Sean Brennan, Honors Advisor
  • Hosam Kadry Fathy, Faculty Reader
Keywords:
  • Control
  • scale vehicle
  • testbed
  • proportional control
  • PURRS
  • rolling roadway simulator
Abstract:
This research focuses on structural modifications to the Pennsylvania State University Rolling Roadway Simulator (PURRS). Operated within the Intelligent Vehicles and Systems Group, the PURRS is a large treadmill for testing automated control algorithms on small scale vehicles before they are implemented on full scale vehicles. Testbeds with scaled vehicles have a number of benefits compared to testing on full scale vehicles, which is a strong motivation for the completion of this project. For example, algorithm testing on a scale vehicle is more cost effective, convenient, and significantly reduces safety concerns in the event of failure. One of the major modifications undertaken in this thesis ws the installation of a new air bearing under the running belt. Like an air hockey table, the air bearing uses air flow to lift the treadmill belt, reducing the friction between the deck and the belt and improving motor efficiency. Speed tests were performed with and without the air bearing, to provide conclusive results on the benefits of adding the air bearing to the system. Additionally, a new small scale vehicle for the PURRS was also used to test position-based feedback control algorithms. Specifically, the vehicle was tested with the use of proportional and proportional-derivative control algorithms. High resolution encoders were used to determine vehicle position relative to a centerline and lateral position errors were used as inputs for controlling the vehicle steering. Perturbation analysis of controller performance was done by manually offsetting vehicle and then enabling control algorithm to correct the position, and both the P- and PD-controlled vehicles were able to maintain centerline position while driving on the roadway.