Intelligent vehicle braking and steering control systems
Abstract
State-of-the-art vehicle dynamics control systems integrate the driver's steering and braking inputs together with the antilock braking system (ABS) and the four wheel steering system (4WS) in order to control the vehicle's yaw rate, lateral acceleration, longitudinal acceleration, and body sideslip angle. The goal of this project is to develop intelligent controllers for vehicle steering and braking maneuvers. In the first stage of the project, a simulation model of a vehicle is developed. Then, using this model several design models are constructed. Intelligent controllers are developed using the design models. The controller's performance is tested using the simulation model. Five different controllers are proposed. First, a Lyapunov based model reference steering controller is constructed. Its performance is tested by simulating an emergency lane change maneuver. The simulation results illustrate the improvement of the path tracking of the compensated vehicle over the uncompensated one. Then, a fuzzy logic based ABS wheel slip controller is proposed. Its performance is evaluated by simulating straight line emergency braking on dry pavement with no steering. The fuzzy logic controller results in a superior vehicle performance compared with a conventional brake control system. Next, a PID sliding mode based ABS controller is synthesized and analyzed. This controller performs an on-line search that determines the optimal wheel slip over any smooth road surface type. The fourth controller is developed for a 4WS system using a fuzzy modeling approach. Finally, a distributed neural brake controller is proposed to improve the vehicle's handling and stability during combined steering and braking maneuvers.
Degree
Ph.D.
Advisors
Zak, Purdue University.
Subject Area
Automotive materials|Electrical engineering|Mechanical engineering
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