Biblio

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.

The split-cycle constant-period frequency modulation for flapping wing micro air vehicle control in two degrees of freedom has been proposed and its theoretical viability has been demonstrated in previous work. Further consecutive work on developing the split-cycle based physical control system has been targeted towards providing on-the-fly configurability of all the theoretically possible split-cycle wing control parameters with high fidelity on a physical Flapping Wing Micro Air Vehicle (FWMAV). Extending the physical vehicle and wing-level control modules developed previously, this paper provides the details of the FWMAV platform, that has been designed and assembled to aid other researchers interested in the design, development and analysis of high level flapping flight controllers. Additionally, besides the physical vehicle and the configurable control module, the platform provides numerous external communication access capabilities to conduct and validate various sensor fusion study for flapping flight control.

This chapter describes triggered control approaches for the coordination of networked cyber-physical systems. Given the coverage of the other chapters of this book, our focus is on self-triggered control and a novel approach we term team-triggered control.