Safety Analysis of Longitudinal Motion Controllers during Climb Flight

During the climb flight of big passenger airplanes, the airplane’s vertical movement, i.e. its pitch angle, results from the elevator deflection angle chosen by the pilot. If the pitch angle becomes too large, the airplane is in danger of an airflow disruption at the wings, which can cause the airplane to crash. In some airplanes, the pilot is assisted by a software whose task is to prevent airflow disruptions. When the pitch angle becomes greater than a certain threshold, the software overrides the pilot’s decisions with respect to the elevator deflection angle and enforces presumably safe values. While the assistance software can help to prevent human failures, the software itself is also prone to errors and is - generally - a risk to be assessed carefully. For example, if software designers have forgotten that sensors might yield wrong data, the software might cause the pitch angle to become negative. Consequently, the airplane loses height and can - eventually - crash.In this paper, we provide an executable model written in Matlab/Simulink® for the control system of a passenger airplane. Our model takes also into account the software assisting the pilot to prevent airflow disruptions. When simulating the climb flight using our model, it is easy to see that the airplane might lose height in case the data provided by the pitch angle sensor are wrong. For the opposite case of correct sensor data, the simulation suggests that the control system works correctly and is able to prevent airflow disruptions effectively.The simulation, however, is not a guarantee for the control system to be safe. For this reason, we translate the Matlab/Simulink® -model into a hybrid program (HP), i.e. into the input syntax of the theorem prover KeYmaera. This paves the way to formally verify safety properties of control systems modelled in Matlab/Simulink®. As an additional contribution of this paper, we discuss the current limitations of our transformation. For example, it turns out that simple proportional (P) controllers can be easily represented by HP programs, but more advanced PD (proportional-derivative) or PID (proportional-integral-derivative) controllers can be represented as HP programs only in exceptional cases.