The formation maintenance of multiple unmanned aerial vehicles(UAVs)based on proximity behavior is explored in this study.Individual decision-making is conducted according to the expected UAV formation structure and t...The formation maintenance of multiple unmanned aerial vehicles(UAVs)based on proximity behavior is explored in this study.Individual decision-making is conducted according to the expected UAV formation structure and the position,velocity,and attitude information of other UAVs in the azimuth area.This resolves problems wherein nodes are necessarily strongly connected and communication is strictly consistent under the traditional distributed formation control method.An adaptive distributed formation flight strategy is established for multiple UAVs by exploiting proximity behavior observations,which remedies the poor flexibility in distributed formation.This technique ensures consistent position and attitude among UAVs.In the proposed method,the azimuth area relative to the UAV itself is established to capture the state information of proximal UAVs.The dependency degree factor is introduced to state update equation based on proximity behavior.Finally,the formation position,speed,and attitude errors are used to form an adaptive dynamic adjustment strategy.Simulations are conducted to demonstrate the effectiveness and robustness of the theoretical results,thus validating the effectiveness of the proposed method.展开更多
The design of an L_1 adaptive controller for hypersonic formation flight is presented. The traditional leader/wingman formation control problem is considered, with focused attention on dealing with the input disturban...The design of an L_1 adaptive controller for hypersonic formation flight is presented. The traditional leader/wingman formation control problem is considered, with focused attention on dealing with the input disturbance and parametric variations, both of which are intrinsic properties of the system that result in undesired control performance. A proportional-derivative control scheme based on nonlinear dynamic inversion is implemented as the baseline controller, and an L_1 adaptive controller is augmented to the baseline controller to attenuate the effects of input disturbance and parametric variations. Simulation results illustrate the effectiveness of the proposed control scheme.展开更多
文摘The formation maintenance of multiple unmanned aerial vehicles(UAVs)based on proximity behavior is explored in this study.Individual decision-making is conducted according to the expected UAV formation structure and the position,velocity,and attitude information of other UAVs in the azimuth area.This resolves problems wherein nodes are necessarily strongly connected and communication is strictly consistent under the traditional distributed formation control method.An adaptive distributed formation flight strategy is established for multiple UAVs by exploiting proximity behavior observations,which remedies the poor flexibility in distributed formation.This technique ensures consistent position and attitude among UAVs.In the proposed method,the azimuth area relative to the UAV itself is established to capture the state information of proximal UAVs.The dependency degree factor is introduced to state update equation based on proximity behavior.Finally,the formation position,speed,and attitude errors are used to form an adaptive dynamic adjustment strategy.Simulations are conducted to demonstrate the effectiveness and robustness of the theoretical results,thus validating the effectiveness of the proposed method.
文摘The design of an L_1 adaptive controller for hypersonic formation flight is presented. The traditional leader/wingman formation control problem is considered, with focused attention on dealing with the input disturbance and parametric variations, both of which are intrinsic properties of the system that result in undesired control performance. A proportional-derivative control scheme based on nonlinear dynamic inversion is implemented as the baseline controller, and an L_1 adaptive controller is augmented to the baseline controller to attenuate the effects of input disturbance and parametric variations. Simulation results illustrate the effectiveness of the proposed control scheme.
