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This paper presents a scalable method to design large-scale Kalman-like filters for a class of linear systems. In particular, we consider systems for which both the propagation of dynamics through the plant and the exchange of information between estimators/sensors is subject to delays. Under suitable assumptions on these delays, our proposed Kalman-like(More)
This paper proposes a simplified space vector modulation (SVM) scheme for multilevel converters. Compared with earlier SVM methods, the proposed scheme simplifies the detection of the nearest three vectors and the generation of switching sequences, and therefore is computation-ally more efficient. Particularly, for the first time, the proposed scheme(More)
As a holistic approach, optimal co-design of a control system determines both the plant and controller simultaneously to optimize certain performance metrics. Prior co-design work typically assume a control system in the classic state space form, and thus compromise the range of applicability. This paper considers co-design for control systems in the linear(More)
For speed sensorless induction motors under field-oriented control (FOC), where the motor speed and angle are not measured, the speed control tracking bandwidth is mainly limited by the convergence rate of the state estimator. Prevailing speed-sensorless induction motors suffer significant performance degradation from removing the encoder, which limits(More)
In this paper, a diagnosis algorithm for arteriovenous fistula (AVF) stenosis is developed based on auscultatory features, signal processing, and machine learning. The AVF sound signals are recorded by electronic stethoscopes at pre-defined positions before and after percutaneous transluminal angioplasty (PTA) treatment. Several new signal features of(More)