Design of an Adaptive Cruise Control Model for Hybrid Systems Fault Diagnosis

Abstract

<p>Driver Assistance Systems like Adaptive Cruise Control (ACC) can help prevent accidents by reducing the workload on the driver. However, this can only be accomplished if the driver can rely on the system to perform safely even in the presence of faults.</p> <p>In this thesis we develop an Adaptive Cruise Control model that will be used to investigate Hybrid Systems Fault Diagnosis techniques. System Identification is performed upon an electric motor to obtain its transfer function. This electric motor belongs to a 1/10th scale RC car that is being used as part of a test bench for the Adaptive Cruise Control system. The identified model is then used to design a hybrid controller which will switch between a set of LQR controllers to create an example Adaptive Cruise Controller. The model of the controller is then used to generate fixed point code for implementation on the testbed and validation against the model controller. Finally a detailed hazard analysis of the resulting system is performed using Leveson's STPA.</p>