Adaptive decentralized control of DC-DC converter systems

In this paper, we develop a robust controller for parallel DC-DC converter system by combining the adaptive backstepping technique and decentralized control. The voltages and currents of all converters are coupled with each other. The parallel DC-DC converter system is modeled as a large scaled state-space system with interconnection between subsystems. Each local controller, designed simply based on the local model of each subsystem by using adaptive backstepping technique, only employs local information to generate control signals. Each of them is robust against the interactions, such that each local controller does not need full knowledge of the overall network and operates as a single power converter providing power to the load. The robustness of decentralized adaptive controllers is established. It is shown that the designed decentralized adaptive backstepping controllers can globally stabilize the overall interconnected system asymptotically, such as to drive the system to a reference point and eliminate the disturbance. The load is properly shared between the power converters. The L₂ norm of the system outputs is also established as functions of design parameters. This implies that the transient system performance can be adjusted by choosing suitable design parameters.