Unit memory repetitive processes and iterative optimal control algorithms

Because of the existence of mixed boundary conditions, the solution of nonlinear dynamic optimal control problems via the maximum principle often requires an algorithm which updates a trial solution from iteration to iteration. This paper analyses this procedure in the form of an unit memory repetit...

Full description

Saved in:
Bibliographic Details
Published inInternational Conference on Control '94 pp. 454 - 459
Main Author Roberts, P.D
Format Conference Proceeding
LanguageEnglish
Published London IEE 1994
Subjects
Algebra
Control system analysis and synthesis methods
Discrete control systems
Interpolation and function approximation (numerical analysis)
Optimal control
Stability in control theory
iterative methods
unit memory repetitive processes
local stability
discrete time systems
convergence
model reality differences
iterative optimal control
optimal control
mixed boundary conditions
maximum principle
matrix algebra
nonlinear dynamic optimal control
discrete optimal control
control system analysis
stability
Online AccessGet full text
ISBN0852966105
9780852966105
DOI10.1049/cp:19940174

Cover

More Information
Summary:Because of the existence of mixed boundary conditions, the solution of nonlinear dynamic optimal control problems via the maximum principle often requires an algorithm which updates a trial solution from iteration to iteration. This paper analyses this procedure in the form of an unit memory repetitive process. Particular emphasis is given to a novel algorithm for the solution of discrete optimal control problems subject to model-reality differences. Unit memory linear repetitive process theory is employed to analyze the local stability of the algorithm and to show that the technique converges to the correct optimal control solution in spite of model-reality differences.
ISBN:0852966105
9780852966105
DOI:10.1049/cp:19940174