This paper examines the problem of designing a robust H∞ output-feedback yaw controller with both input and output constraints for four-wheel independently driven in-wheel electric vehicles (EVs) with differential steering. Specifically, the controller aims are to ensure the stability and improve the performance of the EV despite variations in the road adhesion coefficient, longitudinal velocity, and external disturbance. Based on the linear matrix inequalities approach, sufficient conditions for the existence of an H∞ output-feedback controller for linear systems with polytopic uncertainties, and input and control output constraints, are derived. Then those sufficient conditions are utilized to design an H∞ output-feedback yaw controller that guarantees the robust performance and stability of an EV over a wider range of road conditions. Finally, the capability of the developed controller is simulated on a vehicle model with uncertain road conditions and longitudinal velocities.
In this paper, a novel method is proposed to recover and extract the original signal parameters from the saturated multifrequency sinusoid wave signals. It makes use of the zerocrossing characteristics of the multifrequency sinusoid signals, to collect valid samples in unsaturated parts of the signals. On these valid samples, the amplitudes and phases of the specific original ac sensing signals can be linearly computed by applying the least square method. The simulation results show that the proposed method has satisfactory accuracy even with very large saturation (∼10 times of the saturation limit) and large dc offset, which frees us from the restriction to avoid the signal saturation problem in the signal acquisition. The method is realized by the software algorithm, and no longer requires the common used hardware-the phase sensitive detection circuit. Hence when it is applied to the magnetic coupling system, we will obtain much simpler system composition, higher accuracy, and high execution speed.Index Terms-Multifrequency signal processing, amplitude and phase extraction, magnetic coupling, least square fitting method.
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