Adaptive distributed parameter and input estimation in linear parabolic PDEs
Online Publication Date2016-01-14
Print Publication Date2016-04
Permanent link to this recordhttp://hdl.handle.net/10754/593664
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AbstractIn this paper, we discuss the on-line estimation of distributed source term, diffusion, and reaction coefficients of a linear parabolic partial differential equation using both distributed and interior-point measurements. First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.
CitationAdaptive distributed parameter and input estimation in linear parabolic PDEs 2016:n/a International Journal of Adaptive Control and Signal Processing