Learn More
Optimal feedback solutions to the innnite horizon LQR problem with state and input constraints based on receding horizon real-time quadratic programming are well known. In this paper we develop an explicit solution to the same problem, eliminating the need for real-time optimization. A suboptimal strategy, based on a suboptimal choice of a nite horizon and(More)
A wheel slip controller for Anti-lock Brake Systems (ABS) is designed using LQ-optimal control. The controller gain matrices are gain scheduled on the vehicle speed. A parameter dependent Lyapunov function for the nominal linear parameter varying (LPV) closed loop system is found by solving a linear matrix inequality (LMI) problem. This Lyapunov function is(More)
A wheel slip controller is developed and experimentally tested in a car equipped with electromechanical brake actuators and a brake-by-wire ABS system. A gain scheduling approach is taken, where the vehicle speed is viewed as a slowly time-varying parameter and the model is linearized about the nominal wheel slip. Gain matrices for the different operating(More)
The object of the study was to develop a method for automatic evaluation of the vigilance level using the EEG frequency pattern. Forty-one EEG records were selected as training material, being considered representative of either a fully alert EEG, or sleep stage I. In the same epochs, 22 different variables based on EEG spectral analysis were calculated.(More)
A wheel slip controller for ABS brakes is formulated using an explicit constrained LQR design. The controller gain matrices are designed and scheduled on the vehicle speed based on local linearizations. A Lyapunov function for the nonlinear control system is dervied using the Riccati equation solution in order to prove stability and robustness with respect(More)