A neurocomputing approach for solving the algebraic matrix Riccati equation

This paper presents a neurocomputing approach for solving the algebraic matrix Riccati equation. This approach is able to utilize a good initial condition to reduce the computation time in comparison to standard methods for solving the Riccati equation. The repeated solutions of closely related Ricc...

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Bibliographic Details
Published inProceedings of International Conference on Neural Networks (ICNN'96) Vol. 1; pp. 617 - 622 vol.1
Main Authors Ham, F.M., Collins, E.G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Adaptive control
Computer networks
Cost function
Electronic mail
IEEE members
Matrices
Mechanical engineering
Modems
Riccati equations
Robust control
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Summary:This paper presents a neurocomputing approach for solving the algebraic matrix Riccati equation. This approach is able to utilize a good initial condition to reduce the computation time in comparison to standard methods for solving the Riccati equation. The repeated solutions of closely related Riccati equations appears in homotopy algorithms to solve certain problems in fixed-architecture control. Hence, the new approach has the potential to significantly speed-up these algorithms. It also has potential applications in adaptive control.
ISBN:0780332105
9780780332102
DOI:10.1109/ICNN.1996.548966