Behavioral validation in Cyber-physical systems: Safety violations and beyond

Abstract

The advances in software and hardware technologies in the last two decades have paved the way for the development of complex systems we observe around us. Avionics, automotive, power grid, medical devices, and robotics are a few examples of such systems which are usually termed as Cyber-physical systems (CPS) as they often involve both physical and software components. Deployment of a CPS in a safety critical application mandates that the system operates reliably even in adverse scenarios. While effective in improving confidence in system functionality, testing can not ascertain the absence of failures; whereas, formal verification can be exhaustive but it may not scale well as the system complexity grows. Simulation driven analysis tends to bridge this gap by tapping key system properties from the simulations. Despite their differences, all these analyses can be pivotal in providing system behaviors as the evidence to the satisfaction or violation of a given performance specification. However, less attention has been paid to algorithmically validating and characterizing different behaviors of a CPS. The focus of this thesis is on behavioral validation of Cyber-physical systems, which can supplement an existing CPS analysis framework. This thesis develops algorithmic tools for validating verification artifacts by generating a variety of counterexamples for a safety violation in a linear hybrid system. These counterexamples can serve as performance metrics to evaluate different controllers during design and testing phases. This thesis introduces the notion of complete characterization of a safety violation in a linear system with bounded inputs, and it proposes a sound technique to compute and efficiently represent these characterizations. This thesis further presents neural network based frameworks to perform systematic state space exploration guided by sensitivity or its gradient approximation in learning-enabled control (LEC) systems. The presented technique is accompanied with convergence guarantees and yields considerable performance gain over a widely used falsification platform for a class of signal temporal logic (STL) specifications.Doctor of Philosoph