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Duality of linear estimation and control with constraints

  • V. Sankaran
  • M. D. Srinath
Contributed Papers

Abstract

This paper considers the duality of linear estimation and control with constraints. Specifically, the dual of the optimal filter, where the mean-squared values of the optimal estimates are constrained, is shown to be an optimal control problem with constraints on the control, and the dual of the estimation of stochastic signals in the presence of multiplicative noise in addition to measurement noise is shown to be a control problem with constraints on the states, with the boundary conditions specified at opposite ends of the extremals in time. Algorithms are presented to establish the duality concept.

Keywords

Boundary Condition Control Problem Optimal Control Problem Linear Estimation Measurement Noise 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Kalman, R. E., andBucy, R. S.,New Results in Linear Filtering and Prediction Theory, Journal of Basic Engineering, Vol. 83, No. 1, 1961.Google Scholar
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    Rajasekaran, P. K., Satyanarayana, N., andSrinath, M. D.,Optimal Linear Estimation of Stochastic Signals in the Presence of Multiplicative Noise, IEEE Transactions on Aerospace and Electronic Systems (to appear).Google Scholar

Additional Bibliography

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    Kailath, T.,An Innovations Approach to Least Squares Estimation—Part I: Linear Filtering with Additive Noise, IEEE Transactions on Automatic Control, Vol. 13, No. 6, 1968.Google Scholar
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    Nahi, N. E.,Optimal Recursive Estimation with Uncertain Observation, IEEE Transactions on Information Theory, Vol. 15, No. 4, 1969.Google Scholar
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    Sage, A. P.,Optimum Systems Control, Prentice-Hall, Englewood Cliffs, New Jersey, 1968.Google Scholar

Copyright information

© Plenum Publishing Corporation 1972

Authors and Affiliations

  • V. Sankaran
    • 1
  • M. D. Srinath
    • 1
  1. 1.Information and Control Sciences Center, Institute of TechnologySouthern Methodist UniversityDallas

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