Several estimation methods have been proposed for identifying errors-invariables systems, where both input and output measurements are corrupted by noise. One of the promising approaches is the so called Frisch scheme. In its standard form it is designed to handle white measurement noise on the input and output sides. As the output noise comprises both effects of measurement errors and of proce...

The paper considers the task of identifying a causal linear dynamic system excited by stationary gaussian zero mean noise of unknown spectrum, and given measurements of the system input and output contaminated by independent additive stationary noise 91g0813 of unknown spectra. While the solution is normally not unique, finite-dimensional parameterizations of the solution set are given (in some...

One of the problems associated with iterative learning control algorithms is the selection of a “proper” learning gain matrix for every discrete-time sample and for all successive iterations. This problem becomes more difficult in the presence of random disturbances such as measurement noise, reinitialization errors, and state disturbance. In this paper, the learning gain, for a selected learni...

In this paper, the problem of identifying linear discrete-time systems from noisy input and output data is addressed. Several existing methods based on higher-order statistics are presented. It is shown that they stem from the same set of equations and can thus be united from the viewpoint of extended instrumental variable methods. A numerical example is presented which confirms the theoretical...

Variable structure strategy is widely used for the control of sensor-actuator systems modeled by Euler-Lagrange equations. However, accurate knowledge on the model structure and model parameters are often required for the control design. In this paper, we consider model-free variable structure control of a class of sensor-actuator systems, where only the online input and output of the system ar...

Abstract. Reference crop evapotranspiration (ETo) is calculated using a standard formula with temperature, vapor pressure, solar radiation, and wind speed as input variables. ETo forecasts can be produced when of these variables from numerical weather prediction (NWP) models are available. As raw often subject to systematic errors, statistical calibration needed for improving forecast quality. ...