The main focus of this work is on the problem of existence of nonlinear optimal controllers
realizable by artificial neural networks. Theoretical justification, currently
available for control applications of neural networks, is rather limited. For example,
it is unclear which neural architectures are capable of performing which control
tasks. This work addresses applicability of neural networks to the synthesis of approximately
optimal state feedback. Discrete-time setting is considered, which brings
extra regularity into the problem and simplifies mathematical analysis. Two classes
of optimal control problems are studied: time-optimal control and optimal control
with summable quality index. After appropriate relaxation of the optimization problem,
the existence of a suboptimal feedback mapping is demonstrated in both cases.
It is shown that such a feedback may be realized by a multilayered network with
discontinuous neuron activation functions. For continuous networks, similar results
are obtained, with the existence of suboptimal feedback demonstrated, except for
a set of initial states of an arbitrarily small measure. The theory developed here
provides basis for an attractive approach of the synthesis of near-optimal feedback
using neural networks trained on optimal trajectories generated in open loop. Potential
advantages of control based on neural networks are illustrated on application
to stabilization of interconnected power systems. A nearly time-optimal controller is
designed for a single-machine system using neural networks. The obtained controller
is then utilized as an element of a hierarchical control architecture used for stabilization
of a multimachine power transmission system. This example demonstrates
applicability of neural control to complicated, nonlinear dynamic systems. / Graduation date: 1995
Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/35015 |
Date | 21 December 1994 |
Creators | Zakrzewski, Radoslaw Romuald |
Contributors | Mohler, Ronald R. |
Source Sets | Oregon State University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
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