UAV formation control based on distributed Kalman model predictive control algorithm

To address the perturbation of formation of multiple unmanned aerial vehicles (UAVs) subject to external disturbances, an algorithm of distributed Kalman model predictive control is proposed in this paper to improve the accuracy of maintaining a formation in flight. A UAV two-order discrete-time system model was built before devising a Kalman prediction model based on the standard prediction model. The desired formation configuration and neighbor Kalman optimal state estimation were conducted to determine the reference state of UAVs. While taking into account the formation tracking error and input stability, a logarithmic barrier function was introduced in the design of the overall cost function to ensure flight safety. Meanwhile, information was exchanged with neighbors with the directed and time-invariant communication topological structure. With the Lyapunov stability theorem, sufficient conditions were defined for the asymptotic stability of the formation system. Simulation results revealed that the algorithm could effectively suppress the perturbation in the formation of UAVs arising from external disturbances, allowing the formation to cope with the conflicts between individual UAVs. (C) 2022 Author(s).

Automated summary

This paper proposes a distributed Kalman model predictive control algorithm to address the perturbation of formation of multiple unmanned aerial vehicles (UAVs) subject to external disturbances and improve the accuracy of maintaining a formation in flight. The algorithm builds a UAV two-order discrete-time system model and devises a Kalman prediction model based on the standard prediction model. It determines the reference state of UAVs through desired formation configuration and neighbor Kalman optimal state estimation. A logarithmic barrier function is introduced to ensure flight safety considering the formation tracking error and input stability. Information is exchanged with neighbors using a directed and time-invariant communication topological structure. Sufficient conditions for the asymptotic stability of the formation system are defined using the Lyapunov stability theorem. Simulation results show that the algorithm effectively suppresses perturbations in the formation of UAVs caused by external disturbances, enabling the formation to handle conflicts between individual UAVs.