Modelling and Control of a Scaled Car In and Beyond Stable Limit Handling

Over the past century, cars have become the most important means of transportation. With the increasing number of vehicles on the road, safety has become an important topic. The introduction of driver assistance systems, like Electronic Stability Control, has led to a significant decrease in fatal accidents. By preventing the vehicle from entering unstable behaviour, it remains controllable for the average driver. In rally racing, though, unstable manoeuvres, like drifting, are widely used for improved agility on low friction surfaces and in sharp corners. The average driver, however, is unable to perform such a manoeuvre safely.With the development of autonomous driving systems, steps are taken to increase driver safety by removing the effects of human error. By taking over full control of the vehicle, these systems do not need to consider the driving skills of the average driver. Furthermore, the driving skills of the autonomous driving system are a result of its design. The autonomous driving system could, therefore, be designed to use advanced driver techniques, like drifting, to increase the safety of the passengers and other road users.The objective of this research is to develop a vehicle controller that is capable of path-tracking within and beyond the limits of stable handling. To reduce the costs of testing, the controller is developed for an experimental platform in the form of a 1/10 scale radio controlled car. A nonlinear vehicle model of the scaled vehicle is developed and analysed regarding unstable vehicle behaviour. Since the behaviour and actuation of a vehicle differ in typical cornering and limit handling conditions, two separate controllers are used. In typical cornering conditions, a steering controller is used for path-tracking. Beyond stable limit handling, the lateral motion is actuated by both the steering angle and throttle input. A drift controller is used to determine the appropriate actuator inputs to sustain the drift, based on the yaw rate and direction of motion. The main contribution of this research is an extension of that controller to add path-tracking capabilities. Simulation analysis shows the controller can enter and sustain a drift, while successfully tracking the given path. Implementation of the controller in the scaled car shows great path-tracking performance in typical cornering conditions. Furthermore, the controller is able to, on command, make the vehicle enter sustain a drift