As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …

The field of identification and process-parameter estimation has developed rapidly during
the past decade. In this survey paper the state-of-the-art/science is presented in a systematic …

This unified treatment of linear and nonlinear filtering theory presents material previously
available only in journals, and in terms accessible to engineering students. Its sole …

The definitive textbook and professional reference on Kalman Filtering–fully updated,
revised, and expanded This book contains the latest developments in the implementation …

This paper considers the problem of estimating the states of linear dynamic systems in the
presence of additive Gaussian noise. Difference equations relating the estimates for the …

least squares identificâtion of a parometric rtodel a probabilis¡ íc interpretation cornparison
with correlation nechods correlated residì¡ als-repeaÈed least squares-g-eneralized least …

The extended Kalman filter is an approximate filter for nonlinear systems, based on first-
order linearization. Its use for the joint parameter and state estimation problem for linear …

State estimator design for a nonlinear discrete-time system is a challenging problem, further
complicated when additional physical insight is available in the form of inequality constraints …

Developments in the theory of linear least-squares estimation in the last thirty years or so are
outlined. Particular attention is paid to early mathematica [work in the field and to more …

This book is an outgrowth of class notes of a graduate level seminar on optimization of
stochastic systems. Most of the material in the book was taught for the first time during the …