Biblio

Since the late 1990s the sales of processors targeted for embedded systems has exceeded sales for the PC market. Some embedded systems tightly link the computing resources to the physical world. Such systems are called cyber-physical systems. Autonomous cyber-physical systems often have safety-critical missions, which means they must be fault tolerant. Unfortunately fault recovery options are limited; adapting the physical system behavior may be the only viable option. Consequently, autonomous cyber-physical systems are a class of adaptive systems. The evolvable hardware field has developed a number of techniques that should prove to be useful for designing cyber-physical systems although work along those lines has only recently begun. In this paper we provide an overview of cyber-physical systems and then describe how two evolvable hardware techniques can be used to adapt the physical system behavior in real-time. The goal is to introduce cyber-physical systems to the evolvable hardware community and encourage those researchers to begin working in this emerging field.

This paper proposes a model checking method for a trajectory tracking controller for a flapping wing micro-air-vehicle (MAV) under disturbance. Due to the coupling of the continuous vehicle dynamics and the discrete guidance laws, the system is a hybrid system. Existing hybrid model checkers approximate the model by partitioning the continuous state space into invariant regions (flow pipes) through the use of reachable set computations. There are currently no efficient methods for accounting for unknown disturbances to the system. Neglecting disturbances for the trajectory tracking problem underestimates the reachable set and can fail to detect when the system would reach an unsafe condition. For linear systems, we propose the use of the H-infinity norm to augment the flow pipes and account for disturbances. We show that dynamic inversion can be coupled with our method to address the nonlinearities in the flapping-wing control system.