This paper investigates the injecting power stabilization of nonlinear DC microgrids (MGs) with constant power loads (CPLs). By considering a centralized controller scheme, the limitations of the communication utilities are considered. Therefore, limited information is transferred through the non-ideal noisy communication network. Consequently, a cubature Kalman filter (CKF) with a 3rd degree is proposed to mitigate the effect of the noisy measurement and the noisy network on the system's information. Moreover, an estimationbased robust feedback controller is developed to design an optimal value for the injecting power. The considered CKF algorithm is robust against the system uncertainty and noisy environments and has a low computational time for high-order DC MGs with a high number of sources and CPLs. In addition, a systematic procedure to compute the feedback gain of the controller is presented which can numerically be solved by linear matrix inequality (LMI) techniques. Hardware-in-the-loop (HiL) real-time simulation results verify the simplicity of the controller implementation, enhanced performance for the case of limited information, and better robustness against the noisy measurements compared to the state-of-the-art methods. Index Terms-DC microgrid, constant power load, Cubature Kalman filter (CKF), linear matrix inequality (LMI), non-ideal communication network, hardware-in-the-loop (HiL).

No abstract