An explicit optimal input design for first order systems identification
Résumé
This paper focuses on the problem of closed loop online identification of the time
constant in the single input single output (SISO) first order linear model. A new explicit
approach for the simultaneous online optimal experiment design (OED) and model parameter
identification is presented. Based on the observation theory and a model based predictive
control (MPC) algorithm, this approach aims to solve an optimal control problem where input
and output constraints may be specified. This constrained control objective aims to maximize
the sensitivity of the model output with respect to the unknown model parameter (the time
constant). The control law is derived explicitly offline and simple to be implemented: the input
may be computed fast online while the unknown model time constant is estimated at the same
time.
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duf15 IFAC SYSID15 paper.pdf (376.31 Ko)
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duf15 IFAC SYSID15 slides.pdf (1.87 Mo)
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