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Slip-ratio-based methods are commonly used to control the wheel torque such that the wheel dynamics is stabilized and the desired traction/braking force is attained; however, slip-ratio-based controllers are incompetent for precise longitudinal tire force tracking due to nonparametric tire model uncertainties. Force tracking performance further deteriorates whenever the tire is under combined longitudinal and lateral motion. In this paper, we propose an observer-based tire force control scheme that guarantees to achieve the desired longitudinal tire force accurately and robustly with respect to tire model uncertainties, changes in road conditions, and simultaneous lateral motion. Convergence of the force estimation and tracking errors is rigorously proved by the Lyapunov method. Then, simulations are conducted to verify the robust and accurate performance in longitudinal tire force estimation and tracking under a series of severe driving conditions. [ABSTRACT FROM PUBLISHER]

Due to increasingly demanding requirements for driving safety, precise and robust control of tire traction forces is essential to implement high-performance vehicle-control systems. However, traditional slip-ratio-based methods cannot guarantee achievement of desired traction forces due to a lack of tire force feedback. This paper proposes an observer-based traction force control scheme that is robust with respect to variations of road conditions and tire model uncertainties. Moreover, achievement of desired traction forces is guaranteed. Simulation results verify the robust and satisfactory performance, even under suddenly changing road conditions, as well as parametric and nonparametric tire model uncertainties. [ABSTRACT FROM PUBLISHER]

Active noise cancellation in ducts using multiple feedforward sensors have been investigated by many researchers. When adaptive algorithms were applied, usually a lumped parameter model was assumed and the model includes the dynamics of the duct, sensors and actuators (e.g., microphone and loudspeaker). The distributed nature of the duct usually leads to a large parameter space and is difficult to implement direct adaptive control. This brief presents a control architecture which separates the duct's dynamics from those of sensors and actuators. An adaptive control algorithm is proposed to cope with the unknown dynamics of sensors and actuators. Experiments were conducted to show the effectiveness of the control law. [ABSTRACT FROM AUTHOR]