Model-based fault tolerant control and fault isolation through bipartite graph approach

This paper presents an integrated fault detection and diagnosis (FDD) and fault tolerant control (FTC) approach. The fault is detected and transmitted to the fault-tolerant control block, where a predefined bank of controllers is designed based on the quasi model predictive control approach. A bipartite graph of system equations, variables, and faults is introduced to detect the faults. Upon a fault detection and based on the fault detection and diagnosis block's information, the controller is switched to the appropriate mode. This proposed fault detection approach is subject to structural analysis. No hardware is necessary for this proposed approach, which is considered as its advantage. This approach is applicable without having a deep knowledge of the physical system. The contribution of this paper is two-fold. First, the proposed integrated FDD/FTC can simultaneously detect and diagnose the faults. Moreover, the proposed FTC block guarantees the stability of the closed-loop system. The simulation results indicate that this approach accurately detects and isolates the faults. The fault-tolerant controller preserves the stability and performance of the system upon fault occurrence.