Abstract. Although the parameters of hydrological models are usually regarded as constant, temporal variations can occur in a changing environment. Thus, effectively estimating time-varying becomes significant challenge. Two methods, including split-sample calibration (SSC) and data assimilation, have been used to estimate parameters. However, SSC is unable consider parameter continuity, while ...

This paper presents the design method a proportional integral derivative (PID) controller with time-varying parameters for trajectory tracking of mecanum-wheeled robot minor error. First, nonlinear kinematic error model is established and linearized around working point. Then PID designed based on this linear model. The coefficients KP, KI, KD control are determined by trial technique to ensure...

A new insight into vanadium redox flow batteries (VRFB) parameter estimation is presented. Driven by the electric vehicles proliferation, a hybrid fast-charging station with grid and renewable energy connection particularly considered. In this stationary application, VRFB operating as buffering module. This topology could contribute to reduce cost of charging station. However, make viable techn...

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. I...

There are a number of estimators of a long-memory process' long-memory parameter when the parameter is assumed to hold constant over the entire data set, but currently no estimator exists for a time-varying long-memory parameter. In this paper we construct an estimator of the time-varying long-memory parameter that is based on the time-scale properties of the wavelet transform. Because wavelets...