Robust Fault Diagnosis of Hybrid Systems with Interval-Valued Uncertainties using Hybrid Bond Graph

In this paper, a new robust fault diagnosis procedure for an uncertain hybrid system based on the hybrid bond graph model is proposed. The main objective is to enhance the robustness in the presence of uncertainties in order to minimize the non-detection and false alarm. The scientific interest of the present work remains in integrating the benefits of Hybrid bond graph and Interval analysis properties for effective diagnosis of uncertain hybrid systems. For this task, first, the Interval-valued Analytical redundancy relations which may undergo discrete mode changes are derived from diagnosis hybrid bond graph with controlled junctions. Secondly, the uncertainties are modelled directly in the hybrid bond graph as interval models for interval-valued thresholds generation. The limitations of the existing methods are alleviated by the proposed method. The effectiveness of the proposed method is demonstrated through simulation on a controlled two-tank hybrid system.