Optimal experiment designs with respect to the intended model application
Automatica (Journal of IFAC)
Computer-controlled systems: theory and design (2nd ed.)
Computer-controlled systems: theory and design (2nd ed.)
For model-based control design, closed-loop identification gives better performance
Automatica (Journal of IFAC)
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Paper: Unprejudiced optimal open loop input design for identification of transfer functions
Automatica (Journal of IFAC)
Identification for control: Optimal input intended to identify a minimum variance controller
Automatica (Journal of IFAC)
Survey paper: Optimal experimental design and some related control problems
Automatica (Journal of IFAC)
Closed loop experiment design for linear time invariant dynamical systems via LMIs
Automatica (Journal of IFAC)
Excitation signal design for closed-loop system identification
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Parametric and nonparametric curve fitting
Automatica (Journal of IFAC)
Least costly identification experiment for control
Automatica (Journal of IFAC)
Position Paper: A general framework for Dynamic Emulation Modelling in environmental problems
Environmental Modelling & Software
Bias of indirect non-parametric transfer function estimates for plants in closed loop
Automatica (Journal of IFAC)
From experiment design to closed-loop control
Automatica (Journal of IFAC)
Hi-index | 22.16 |
The problem of designing the identification experiments to make them maximally informative with respect to the intended model use is studied. The focus is on how to identify models that are good for control, so called ''Identification for Control''. A main result is that we derive explicit expressions for the optimal controller and the optimal reference signal spectrum to use in the identification experiment for the case that only the misfit in the dynamics model is penalized and when a linear combination of the input and output variances is constrained.