No abstract

Abstract-The problem of modeling and controlling vehicle longitudinal motion is addressed for front wheel propelled vehicles. The chassis dynamics are modeled using relevant fundamental laws taking into account aerodynamic effects and road slop variation. The longitudinal slip, resulting from tire deformation, is captured through Kiencke"s model. A highly nonlinear model is thus obtained and based upon in vehicle longitudinal motion simulation. A simpler, but nevertheless accurate, version of that model proves to be useful in vehicle longitudinal control. For security and comfort purpose, the vehicle speed must be tightly regulated, both in acceleration and deceleration modes, despite unpredictable changes in aerodynamics efforts and road slop. To this end, a nonlinear controller is developed using the Lyapunov design technique and formally shown to meet its objectives i.e. perfect chassis and wheel speed regulation.

No abstract

State estimators for induction motors are generally designed based on standard simplified models, assuming linear magnetic characteristics. Since they are actually nonlinear, especially for high power machines, the mentioned state estimators are likely not able to achieve the estimation accuracy they have been designed for. In this paper, a new state estimator is developed for a (uniform air-gap) AC machine, based on a more accurate model that appropriately accounts for the saturation feature in the magnetic characteristics. The proposed estimator is a high-gain full-order nonlinear observer designed using Lyapunov stability tools. The resulting estimation errors are shown to asymptotically vanish, if their initial values belong to a well defined attraction region. Supremacy of the new observer over standard ones is illustrated by simulation using a 7.5 KW AC machine.

No abstract