Optimal experiment designs with respect to the intended model application
Automatica (Journal of IFAC)
Adaptive algorithms and stochastic approximations
Adaptive algorithms and stochastic approximations
Rate of convergence of recursive estimators
SIAM Journal on Control and Optimization
Control of uncertain systems: a linear programming approach
Control of uncertain systems: a linear programming approach
Identification and control—closed-loop issues
Automatica (Journal of IFAC) - Special issue on trends in system identification
Multivariable Feedback Control: Analysis and Design
Multivariable Feedback Control: Analysis and Design
SIAM Journal on Control and Optimization
A Representation Theorem for the Error of Recursive Estimators
SIAM Journal on Control and Optimization
Survey paper: Optimal experimental design and some related control problems
Automatica (Journal of IFAC)
From experiment design to closed-loop control
Automatica (Journal of IFAC)
Input design as a tool to improve the convergence of PEM
Automatica (Journal of IFAC)
Hi-index | 22.15 |
An adaptive algorithm, consisting of a recursive estimator for a finite impulse response model having two non-zero lags only, and an adaptive input are presented. The model is parametrized in terms of the first impulse response coefficient and the model zero. For linear time-invariant single-input single-output systems with real rational transfer functions possessing at least one real-valued non-minimum phase zero of multiplicity one, it is shown that the model zero converges to such a zero of the true system. In the case of multiple non-minimum phase zeros, the algorithm can be tailored to converge to a particular zero. The result is shown to hold for systems and noise spectra of arbitrary degree. The algorithm requires prior knowledge of the sign of the high frequency gain of the system as well as an interval to which the non-minimum phase zero of interest belongs.