Dynamic Coordinated Control for Multiconverter Systems via a Multistep Prediction Scheme

Modular dc–dc converters are popular in dc power systems, such as demagnetization systems due to their advantages of high efficiency, high reliability, and low current stress on components. However, the dynamic consensus of output currents of the multiple converter degaussing systems (MCDSs) has not been well solved yet, especially when communication delay is considered. In this article, a novel coordinated control method based on multistep state predictions with active compensation of delay is proposed to address the poor dynamic consensus performance of currents in MCDSs. The implementation of the scheme consists of the following two main phases: the design of a multistep state predictor for MCDSs and the optimization of the coordinating cost of currents. The multistep state predictor can estimate immeasurable future states of converters over a large horizon length, which presents a novel approach to the current regulator design. The optimal control protocol is derived by minimizing a distributed coordinating performance index function (PIF) for the output currents. This optimization of the PIF minimizes the consensus error between output currents for converters and compensates for communication constraints. Furthermore, the conditions for simultaneous stability and consensus of the closed-loop degaussing system with the distributed multistep state prediction controller are given. Finally, the performance of the proposed scheme is verified by numerous case studies in an experimental testbed.