A Dendrite Net based decoupled framework for the reliability‐based control co‐design problem

Abstract

To improve the reliability of the dynamic system including physical and control design, the reliability‐based control co‐design (RB‐CCD) problem has been studied to account for the uncertainty stemming from the random physical design. However, when encountering RB‐CCD in the sophisticated system in which the dynamic model simulation is time‐consuming or the state equation is expressed implicitly, the available RB‐CCD methods will consume significant computational effort to perform numerous system simulations for the reliability analysis and deterministic optimization. Therefore, this work proposes a Dendrite Net‐based decoupled framework for RB‐CCD to alleviate the computational burden. Specifically, the Dendrite (DD) model constructed by the suggested training scheme integrated with an adaptive sampling strategy is used to approximate the state equation in the dynamic system. After that, the sequential optimization and reliability assessment method decouples RB‐CCD into the control co‐design (CCD) problem and time‐dependent reliability assessment problem, which are solved sequentially based on the cheap estimations of DD model, rather than the expensive simulations of the original system. Furthermore, two numerical examples and an engineering example of 3‐DOF robot system are applied to demonstrate the feasibility and efficiency of the proposed framework.