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How to Apply Generalized Eigenvalue Minimization to Processes That Can Be Described by a First-Order Plus Time-Delay Model

By: ISA Transactions
31 October, 2014
1 min read
How to Apply Generalized Eigenvalue Minimization to Processes That Can Be Described by a First-Order Plus Time-Delay Model
How to Apply Generalized Eigenvalue Minimization to Processes That Can Be Described by a First-Order Plus Time-Delay Model
An algorithm to transform the uncertain first-order plus time delay model into a state-space model with uncertainty polyhedron is detailed in this technical paper.

This post is an excerpt from the journal ISA Transactions. All ISA Transactions articles are free to ISA members, or can be purchased from Elsevier Press.

Fragment of illuminated ship control panel in the dark. Selectiv

Abstract:

This paper shows how to apply generalized eigenvalue minimization to processes that can be described by a first-order plus time-delay model with uncertain gain, time constant and delay. An algorithm to transform the uncertain first-order plus time delay model into a state-space model with uncertainty polyhedron is firstly described. The accuracy of the transformation is studied using numerical examples. Then, the uncertainty polyhedron is rewritten as a linear-matrix-inequality constraint and generalized eigenvalue minimization is adopted to calculate a feedback control law. Case studies show that even if uncertainties associated with the first-order plus time delay model are significant, a stable feedback control law can be found.

The proposed control is tested by comparing with a robust internal model control. It is also tested by applying it to the temperature control of air-handing units.

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