Causal Signal Temporal Logic for the Environmental Control and Life Support System’s Fault Analysis and Explanation

Abstract

Modern cyber-physical systems would often fall victim to unanticipated anomalies. Humans are still required in many operations to troubleshoot and respond to such anomalies, such those in future deep space habitats. To maximize the effectiveness and efficiency of the anomaly response process, the information provided by anomaly response technologies to their human operators must be epistemically accessible or explainable. This paper offers a first step towards developing explainable anomaly response systems. It proposes a logic, Causal Signal Temporal Logic (CaSTL), which can formally describe causeeffect relationships pertaining to fault explanation. Moreover, it develops an algorithm to infer a CaSTL formula that explains why a fault has happened in a system, given the model of the system and an observation about the fault. The effectiveness of the proposed algorithm is demonstrated with a simulated Environmental Control and Life Support System (ECLSS).

Automated Testing With Temporal Logic Specifications for Robotic Controllers Using Adaptive Experiment Design

“…return pams via Eqn (12) stage. To replenish those discarded trajectories, lines (14-16) copy one of the remaining un-discarded τ (i) up until the first time step j where the robustness value of the partial trajectory falls below γ m .…”

“…We then re-simulate starting from j to produce a new trajectory. We repeat this process until the discard threshold γ m falls below the desired failure threshold γ, then calculate a final estimate pams using Eq (12).…”

“…Yet recent advances in online monitoring could be leveraged within AMS to discard infeasible trajectories early. For example, incorporating system dynamics, or causality [50], [12].…”