Robert R. Tenney. / "February 1985." / Bibliography: p. 48-49. / Office of Naval Research Contract No. N00014-77-0532 (N041-519)

by M. Vidyasagar and N. Viswanadham. / "March, 1983." / Bibliography: p. 15-16. / Natural Sciences and Engineering Research Council of Canada grant no. A-1240

J. Douglas Birdwell, D.A. Castanon, M. Athans. / "December, 1985." Caption title. / Bibliography: p. [35]. / NASA Ames grant NGL-22-009-124 AFOSR grant 77-3281

Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (p. 120-124).

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This thesis describes work on the selection of the optimal control criterion weighting matrices, based on multivariable root loci and frequency domain properties. The case with a crossproduct weighting term in the cost function is examined and a design algorithm is proposed. The frequency domain solution to the finite time optimal control problem for discrete time systems is described and controller expressions in closed loop form are obtained for the regulation and tracking problems. The design of a strip shape control system for a Sendzimir cold rolling steel mill is described and problems of implementation are discussed. Finally, a detailed comparison between an optimal and a multivariable frequency domain design for a dynamic ship positioning system is presented. The effects of using Kalman filters for state estimate feedback in non-optimal systems is discussed.

This thesis considers optimal linear least-squares filtering smoothing prediction and regulation for discrete-time processes. A finite interval smoothing filter is derived in the z domain giving a transfer function solution. The resulting time-invariant smoother can be applied to problems where, a time varying solution using matrix Riccati equations would diverge if the process is modelled inaccurately. A self-tuning algorithm is given for the filtering and fixed lag smoothing problems as applied to square multi-variable ARMA processes when only the order of the process is assumed known. The dynamics of the process can also be slowly time varying. If the dynamics remain constant and unknown, it is shown how the self-tuning filter or smoother algorithm converges asymptotically to the optimal Wiener solutions. LQG self-tuning regulation is considered. The LQG algorithms rely on input-output data rather than from the conventional state-space approach employing the Kalman filter. An explicit algorithm is given which is similar to certain pole placement self-tuning regulators, requiring the solution of a diophantine equation. Following this, an implicit algorithm is shown to overcome the problem of solving a diophantine equation by estimating the regulator parameters directly using recursive least squares. The LQG algorithms are shown to be able to cope with processes which are non-minimum phase, open loop unstable and with an unknown time delay.

Various control schemes are presented in this thesis for dealing with the problems which arise from the tie-line reactance existing between a generator and an infinite-bus system.

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