Formation of policies guided by multivariable control theory

Joe J. Khalife, Mohammad Al Abbas and Samer S. Saab

Operations Research Perspectives, 2020, vol. 7, issue C

Abstract: The literature associated with system modeling and decision-making falls short in automating policy formation for correlated multiple-policy multiple-objective (MPMO) processes. Enthused by the effectiveness of multivariable control theory, this paper proposes the implementation of a multiple-input multiple-output (MIMO) controller as a guidance tool for designing policies. System dynamics is considered for modeling the dynamic behavior of MPMO systems. The model is then converted to a state-space system where objectives and policies are mapped to time-varying reference trajectories and inputs, respectively. Subsequently, the design of policies driving the system outputs to meet certain objective profiles is converted to a multivariable control problem. This paper also recommends a class of multivariable controllers that is suitable for this domain of applications. Numerical simulations are included to illustrate the effectiveness of the proposed systematic approach.

Keywords: Control theory; Multivariable control; Policy design; Strategic planning; System dynamics; Iterative learning control (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:oprepe:v:7:y:2020:i:c:s2214716020300385

DOI: 10.1016/j.orp.2020.100148

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