Optimal experiment design for identification of linear distributed-parameter systems: Frequency domain approach

DOI10.1109/TAC.1983.1103309zbMath0521.93066OpenAlexW2106954701MaRDI QIDQ3671868

Ewaryst Rafajłowicz

Publication date: 1983

Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tac.1983.1103309

zbMATH Keywords

distributed-parameter systemsexperiment designFisher's information matrixsensors allocation

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Control/observation systems governed by partial differential equations (93C20) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05) Identification in stochastic control theory (93E12) Measures of information, entropy (94A17) Model systems in control theory (93C99)

Related Items (13)

Time-domain optimization of input signals for distributed-parameter systems identification ⋮ Mobile Sensor Routing for Parameter Estimation of Distributed Systems Using the Parallel Tunneling Method ⋮ Optimal experimental design and some related control problems ⋮ Frequency domain sample maximum likelihood estimation for spatially dependent parameter estimation in PDEs ⋮ D-optimal design of a monitoring network for parameter estimation of distributed systems ⋮ Distributed scheduling of sensor networks for identification of spatio-temporal processes ⋮ An Optimal Scanning Sensor Activation Policy for Parameter Estimation of Distributed Systems ⋮ Optimal activation policies for continuous scanning observations in parameter estimation of distributed systems ⋮ Sensor network design for the estimation of spatially distributed processes ⋮ Configuring A Sensor Network for Fault Detection in Distributed Parameter Systems ⋮ Sensors and controllers location in distributed systems - A survey ⋮ Sensor network scheduling for identification of spatially distributed processes ⋮ Decentralized Scheduling of Sensor Networks for Parameter Estimation of Spatio-Temporal Processes

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