Analysis of Drifting for a Remotely Controlled Car
By restricting a vehicle to the linear region of operation, with a small sideslip angle, a vehicle
cannot achieve its full potential. By entering the nonlinear region of operation tighter
corners can be achieved and some accidents could be prevented. Research is currently being
conducted to introduce drifting into vehicle safety systems, which currently restrict the
vehicle to the linear region of operation. Vehicle drifting has been shown to have unstable
equilibria, while still maintaining controllability.
In this thesis, equilibria with sideslip angles ranging from -30 degrees to 30 are found for
a nonlinear two-track model simulator. Analysis showed that simple mappings could be
made between the states and the inputs, and between the states themselves. All the linearised
systems in these equilibria were found to be unstable, which coincides with current
In addition, this thesis presents an adaptive backstepping controller, which is used for converge
to an arbitrary sideslip angle, and when the drift is being initialised the controller
mimics the behaviour of Power Over drifting technique. The adaptive part of the backstepping
controller is used as integral action that, by the use of adaptation, finds the stationary
deviation between the yaw rate and the desired yaw rate, which is added to the control law.
A mapping between the desired sideslip angle and the desired yaw rate is used in a feed
forward term such that the desired sideslip angle is achieved when the yaw rate converges.
The controller has been tested with a modified Line Of Sight guidance system which provided
the controller with a desired sideslip angle. Robust response with respect to changes
in vehicle mass and inertia was observed.
Place, publisher, year, edition, pages
Institutt for teknisk kybernetikk , 2012. , 116 p.
ntnudaim:7042, MTTK teknisk kybernetikk,
IdentifiersURN: urn:nbn:no:ntnu:diva-16829Local ID: ntnudaim:7042OAI: oai:DiVA.org:ntnu-16829DiVA: diva2:536496
Fossen, Thor Inge, Professor