State Space Identification and Minimal State Space Realization of Max-Plus Linear Systems
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We present a method to identify the parameters of a state space model for a maxplus linear system based on the data from input-output sequences. This method is based on modeling the system as a mixed-integer program. We show that this method is computationally more efficient compared to existing methods, given the assumption that the system and data are not corrupted by noise. Furthermore, we present a linear program that could be used for state space identification in certain cases. This method is even more computationally efficient and allows us to identify max-plus linear systems of a higher order. Additionally, we will show that the same mixed-integer programming formulation can be used to find the minimal state space realization of a max-plus linear system and present an algorithm to find this minimal realization. Moreover, we will present a method to model capacity constraints in a max-plus linear system.
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TNO Identifier
1005572
Publisher
University of Twente
Collation
VIII, 50 p.
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