This work presents a new approach for identification experiment design where the objective
is to design the least costly experimental conditions such that the controller designed with …

In this paper we establish the equivalence between least costly and traditional experiment
design for control. We consider experiment design problems for both open and closed loop …

This paper tackles the problems of simple and robust experiment design for system
identification using elementary fractional models. It is based on a frequency domain …

In optimal input design input sequences are typically generated without paying attention to
the correlations between the regressors of the model to be estimated. In fact, in many cases …

The closed-loop identification of second-order plus time delay (SOPTD) transfer function
models of multivariable systems is presented based on optimization method using the …

One obstacle in connecting robust control with models generated from prediction error
identification is that very few control design methods are able to directly cope with the …

Robust optimal experiment design is an infinite dimensional optimisation problem. Typically
it is solved by discretisation of the design space resulting in a discrete semi-infinite convex …

This paper deals with quantification of noise induced errors in identified discrete-time
models of causal linear time-invariant systems, where the model error is described by the …

A common approach for dealing with non-linear systems is to describe the system by a
model with parameters that vary as a function of the operating point. Consequently, the non …

In the next decades wind energy is expected to secure a firm share of the total energy
production capacity in many countries. To increase competitiveness of wind power with …