Formal Technique for Fault Detection and Identification of Control Intensive Application of Stall Warning System Using System Theoretic Process Analysis

Abstract

Faults if not detected and processed will create catastrophe in closed loop system for safety critical applications in automotive, space, medical, nuclear, and aerospace domains. In aerospace applications such as stall warning and protection/prevention system (SWPS), algorithms detect stall condition and provide protection by deploying the elevator stick pusher. Failure to detect and prevent stall leads to loss of lives and aircraft. Traditional Functional Hazard and Fault Tree analyses are inadequate to capture all failures due to the complex hardware-software interactions for stall warning and protection system. Hence, an improved methodology for failure detection and identification is proposed. This paper discusses a hybrid formal method and model-based technique using System Theoretic Process Analysis (STPA) to identify and diagnose faults and provide monitors to process the identified faults to ensure robust design of the indigenous stall warning and protection system (SWPS). The technique is implemented for the SWPS system to ensure the detection of faults due to electric, sensor and computational integrity. Once a fault is detected, a graceful degradation of system functionality is ensured, and appropriate caution/warning annunciations are provided to alert the crew. This has been analyzed and demonstrated on the simulated platform. Proposed Methodology uses the Concept of Operations and STPA to derive the control logic model for monitors for fault detection and identification. These monitors analyze data from angle of attack sensors, Air data computational units and Attitude heading reference system for developing a robust logic for SWPS to minimize both false positives and false negatives. The efficacy of the proposed hybrid technique has been demonstrated on the real time flight simulator with aircraft flight data