| Abstract: |
| This paper proposes a data-driven distributed fault-tolerant control (DFTC) method based on the unified stable kernel representation (SKR) and stable image representation (SIR) framework. Firstly, for each multi-input multi-output subsystem, a class of multi-dimensional residual generators is constructed based on data-driven distributed observers. Then, a distributed representation of the interconnected system is established within the SKR and SIR framework. In this representation, the input-output signal space of each subsystem is decomposed into the nominal image subspace and the residual subspace that characterizes the combined effects of faults, uncertainties and coupling dynamics. This decomposition offers a structured representation that integrates monitoring and control perspectives, enabling systematic integration of fault information into controller design. Based on Youla parameterization, a distributed controller reconfiguration scheme is developed, where residual-driven compensators are designed via a model matching formulation. Sufficient conditions for global closed-loop stability are derived using the small-gain theorem. The developed control architecture is fully distributed and allows plug-and-play implementation. Simulation results on a benchmark power system validate the effectiveness of the proposed method in achieving fault compensation and performance recovery. |
|