Hierarchical adaptive techniques for optimizing control of large-scale steady-state systems. Optimality, iterative strategies and their convergence

M. A. Brdys, Normah Abdullah, P. D. Roberts

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

A hierarchical structure for on-line steady-state optimizing control of interconnected systems is discussed which utilizes the available mathematical model more efficiently than in previous techniques, in spite of large model-reality differences. The structure is of an iterative type and uses both the mathematical model of the system and the system output measurements. The structure produces a control which satisfies necessary optimality conditions, provided that the system mathematical model is point-parametric. Several iterative strategies for finding a solution are presented. Detailed convergence analysis is presented, and simulation results are illustrated, in three numerical examples.

Original languageEnglish
Pages (from-to)199-233
Number of pages35
JournalIMA Journal of Mathematical Control and Information
Volume7
Issue number3
Publication statusPublished - 1990

Fingerprint

Adaptive Techniques
Optimality
Theoretical Models
Mathematical Model
Mathematical models
Interconnected Systems
Necessary Optimality Conditions
Hierarchical Structure
Convergence Analysis
government supervision
Large scale systems
Numerical Examples
Output
simulation
Strategy
Simulation
Model

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Mathematics (miscellaneous)
  • Control and Optimization
  • Molecular Biology
  • Statistics and Probability
  • Computational Mathematics
  • Development
  • Control and Systems Engineering
  • Applied Mathematics

Cite this

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AB - A hierarchical structure for on-line steady-state optimizing control of interconnected systems is discussed which utilizes the available mathematical model more efficiently than in previous techniques, in spite of large model-reality differences. The structure is of an iterative type and uses both the mathematical model of the system and the system output measurements. The structure produces a control which satisfies necessary optimality conditions, provided that the system mathematical model is point-parametric. Several iterative strategies for finding a solution are presented. Detailed convergence analysis is presented, and simulation results are illustrated, in three numerical examples.

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