Comparative Study of Co-Design Strategies for Mission-Specific Design of Quadcopters using Differential Flatness and Bayesian Optimization

Up until recently a sequential approach has been pursued for model-based design of dynamic mechatronic systems, where first the system is optimized for static performance measures after which its functionality is enhanced by optimizing its control trajectory. However, this impedes finding systems with concurrent optimal design and trajectory. Therefore multi-disciplinary integrated design methods–co-design–have appeared that treat design and trajectory optimization at the same time. In this paper we examine two strategies for co-design, namely the simultaneous approach and the nested approach, for the optimal design of a quadcopter to perform a predefined task. To enable the former, Bayesian optimization is introduced in the nested framework to account for the computational cost. In regards to the latter, we rely on a flatness-based description of the dynamics of the aerial vehicle. Comparison of the two approaches with a sequential approach shows the added value of co-design to the design phase of dynamical systems and the impact of objective and constraint function formulation.