Toward Balancing Dynamic Performance and System Stability for DC Microgrids: A New Decentralized Adaptive Control Strategy

In the primary control layer of DC microgrids, engineers usually select the control gains with a robust design strategy (i.e., the worst case study), aiming to ensure stable operation of the system with the presence of large-signal disturbances. However it will inevitably result in degraded nominal control performance. To this end, a compromise between dynamic performance and system stability appears and how to reconcile it is a challenging task. In this context, we propose a novel adaptive control strategy aiming to pursue a balance between the above two properties. Firstly, a higher-order sliding mode observation technique is employed to estimate the disturbance variations within a finite time. Secondly, an adaptive gain regulation mechanism is designed in an easy-implementable fashion. Finally, by combing the feedforward decoupling procedure and the adaptive feedback scheme, the control performance of the DC microgrids can be adjusted adaptively in different working conditions. Through the above design produces, the proposed controller will bring the following new features: 1) The robustness redundancy of existing robust control strategies can be essentially avoided. 2) The balance between dynamic performance and system stability is achieved. 3) The self-tuning regulation facilitates the process of gain selection and the concise adaptive structure can be easily utilized in practical implementation. The efficacy of the proposed controller is verified by both simulation and experiment results.

Automated summary

In the primary control layer of DC microgrids, achieving a balance between dynamic performance and system stability is a challenging task. This study proposes a novel adaptive control strategy that combines higher-order sliding mode observation and adaptive gain regulation to achieve adaptive control performance.