Trajectory Generation Using Sum-of-Norms Regularization
2010 (English)In: Proceedings of the 49th IEEE Conference on Decision and Control, 2010, 540-545 p.Conference paper (Refereed)
Many tracking problems are split into two sub-problems, first a smooth reference trajectory is generated that meet the control design objectives, and then a closed loop control system is designed to follow this reference trajectory as well as possible. Applications of this kind include (autonomous) vehicle navigation systems and robotics. Typically, a spline model is used for trajectory generation and another physical and dynamical model is used for the control design. Here we propose a direct approach where the dynamical model is used to generate a control signal that takes the state trajectory through the waypoints specified in the design goals. The strength of the proposed formulation is the methodology to obtain a control signal with compact representation and that changes only when needed, something often wanted in tracking. The formulation takes the shape of a constrained least-squares problem with sum-of-norms regularization, a generalization of the ℓ1-regularization. The formulation also gives a tool to, e.g. in model predictive control, prevent chatter in the input signal, and also select the most suitable instances for applying the control inputs.
Place, publisher, year, edition, pages
2010. 540-545 p.
Closed loop systems, Control system synthesis, Least squares approximations, Predictive control
IdentifiersURN: urn:nbn:se:liu:diva-60983DOI: 10.1109/CDC.2010.5717368ISBN: 978-1-4244-7745-6OAI: oai:DiVA.org:liu-60983DiVA: diva2:360023
49th IEEE Conference on Decision and Control, Atlanta, GA, USA, 15-17 December, 2010