Abstract

Recent research has led to the design of effective steering control strategies that employ, as controlled variables, the steering velocity and the yaw rate. The yaw rate can be measured by an inertial platform, which is usually already installed on modern motorcycles for advanced traction and braking control systems. Thus, there is an interest in developing effective steering angle estimators to implement single-sensor control strategies without introducing any additional cost for the semi-active steering damper control system. This paper proposes a robust minimum variance linear time-invariant filter and a linear parametrically varying observer to estimate the steering angle based on yaw rate and vehicle speed measurements, the performance of which is compared both via simulation and experimental data. The closed-loop performance of the single-sensor control strategies is finally evaluated and compared with that obtained with the two-sensor algorithm.

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