Diagnostic-constrained fault-tolerant control of bi-directional AGV transport systems with fault-prone sensors

This paper explores a novel challenge regarding bidirectional Automated Guided Vehicles (AGVs): supervisory control amidst potential sensor faults. The proposed approach uses an event-based control architecture, guided by Supervisory Control Theory (SCT), to achieve non-blocking routing of AGVs. Unlike most routing approaches assuming full event observability, this paper investigates scenarios where events might become unobservable due to sensor faults or disturbances, which may affect the supervisor efficiency. The paper addresses two new key issues regarding AGV systems. First, it examines the diagnosis problem of automated transport systems from a discrete-event systems perspective. Secondly, it presents a control architecture enhanced with a diagnostic layer to improve fault tolerance. The theory of automata and languages is used to address control and diagnostic issues. The proposed methodology offers a systematic approach to design specification and diagnostic automata for routes shared by AGVs. The new specification automata integrate information from the diagnostic automata via synchronized transition guards, guaranteeing the synthesis of a robust supervisor that avoids deadlocks even when observability is compromised. The efficiency of the proposed architecture is examined and showcased by simulation. In addition, a modelling framework based on stochastic timed automata is introduced, applying model checking to assess system reliability which is redefined as the probability of deadlock avoidance.