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Applying Mission‐Based Adaptability to Discipline Designs
Author(s) -
Zhu Haifeng
Publication year - 2019
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2019.00627.x
Subject(s) - adaptability , scope (computer science) , hvac , term (time) , controller (irrigation) , computer science , control engineering , systems engineering , function (biology) , air conditioning , engineering , mechanical engineering , ecology , agronomy , physics , quantum mechanics , evolutionary biology , biology , programming language
Mission‐based adaptability is an important metric in developing sustainable systems and can be used to guide system architecture designs. In this work, it was found such a method can be used in a much broader scope, including guiding detailed system designs. Specifically, this paper has two contributions. First, it applies mission‐based adaptability theory to control systems, and provides two system design flows using mapping techniques, to allow the controller to be conveniently designed. Second, it is shown that theoretically the Model Predictive Control (MPC) optimization can be treated as being equivalent to optimizing Mission Effectiveness Function (MEF) on a single mission in the short‐term case and optimizing on multiple missions in the long‐term case. The effectiveness is shown through two example cases, an aircraft engine and an HVAC (Heating, Ventilation, and Air Conditioning) system.