Conventional sequential methods are not bound to yield optimal solutions for design of physical systems and their corresponding control systems. However, by managing the interactions, combined physical and control system design (co-design) can produce superior optimal results. Existing Co-design methods are practical for moderate-scale systems; whereas, they can be impractical or impossible to use when applied to large-scale systems and consequently may limit our determination of an optimal solution. This work addresses this issue by developing a novel decomposition-based version of a co-design algorithm to optimize such large-scale dynamic systems. The new formulation implements a decomposition-based optimization strategy known as Analytical Target Cascading (ATC) to a co-design method known as Multidisciplinary Dynamic System Design Optimization (MDSDO) of a large-scale dynamic system. In addition, a new consistency measure was also established to manage time-dependent linking variables. Results substantiate the ability of the new formulation in identifying the optimal dynamic system solution.

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