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- W195214563 abstract "This chapter reviews introductory stochastic estimation and control. The chapter discusses the theory of deterministic multivariable observers. The inclusion of control inputs is trivial and in any case “Kalman filtering” is a recursive estimation procedure that is sufficiently important in its own right. The dual nature of the linear-quadratic control and estimation problems was first observed by Kalman. The dual property holds naturally for the corresponding continuous time case when a matrix-Ricatti differential equation generates the covariance matrix of the estimates. Two extensions of the Kalman estimator are to be noted—the inclusion of deterministic inputs and an approximation for use with nonlinear systems. Deterministic inputs such as control variables or measured disturbances can be included easily. The chapter reviews the extension of the Kalman filter for the approximate estimation of the states of nonlinear systems by means of a local linearization. State estimation and parameter updating can be implemented simultaneously and recursively on-line by the extended Kalman filter." @default.
- W195214563 created "2016-06-24" @default.
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- W195214563 date "1972-01-01" @default.
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- W195214563 title "Introductory Stochastic Estimation and Control" @default.
- W195214563 doi "https://doi.org/10.1016/b978-0-08-016820-3.50009-6" @default.
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