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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 presents an application of Gaussian process regression (GPR) to estimate a state of charge (SoC) of Lithium-ion (Li-ion) batteries with different kernel functions. One of the practical advantages of using GPR is that uncertainties in the estimates can be quantified, which enables reliability assessment of the SoC estimate. The inputs of GPR are(More)
The maximum capacity, the amount of maximal electric charge that a battery can store, not only indicates the state of health, but also is assumed in numerous methods for state of charge estimation. This paper proposes an alternative approach to perform the online estimation of the maximum capacity by solving the recursive total least square (RTLS) problem.(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)