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Enhanced Multi-UAV Formation Control and Obstacle Avoidance Using IAAPF-SMC
by
Wang, Zhongliu
, Luo, Jiangyu
, Zhang, Pengfei
, Zhu, Ziwen
, Liang, Qinyang
in
artificial potential field
/ Collision avoidance
/ Control algorithms
/ Control stability
/ Control systems
/ Cooperative control
/ cooperative obstacle avoidance
/ Design
/ Drone aircraft
/ Effectiveness
/ Fault tolerance
/ Feedback control
/ IAAPF
/ leader-follower formation control
/ Methods
/ Obstacle avoidance
/ Potential fields
/ Robust control
/ Sensors
/ Sliding mode control
/ SMC
/ Stability augmentation
/ Tracks (paths)
/ Unmanned aerial vehicles
/ virtual force
2024
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Enhanced Multi-UAV Formation Control and Obstacle Avoidance Using IAAPF-SMC
by
Wang, Zhongliu
, Luo, Jiangyu
, Zhang, Pengfei
, Zhu, Ziwen
, Liang, Qinyang
in
artificial potential field
/ Collision avoidance
/ Control algorithms
/ Control stability
/ Control systems
/ Cooperative control
/ cooperative obstacle avoidance
/ Design
/ Drone aircraft
/ Effectiveness
/ Fault tolerance
/ Feedback control
/ IAAPF
/ leader-follower formation control
/ Methods
/ Obstacle avoidance
/ Potential fields
/ Robust control
/ Sensors
/ Sliding mode control
/ SMC
/ Stability augmentation
/ Tracks (paths)
/ Unmanned aerial vehicles
/ virtual force
2024
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Do you wish to request the book?
Enhanced Multi-UAV Formation Control and Obstacle Avoidance Using IAAPF-SMC
by
Wang, Zhongliu
, Luo, Jiangyu
, Zhang, Pengfei
, Zhu, Ziwen
, Liang, Qinyang
in
artificial potential field
/ Collision avoidance
/ Control algorithms
/ Control stability
/ Control systems
/ Cooperative control
/ cooperative obstacle avoidance
/ Design
/ Drone aircraft
/ Effectiveness
/ Fault tolerance
/ Feedback control
/ IAAPF
/ leader-follower formation control
/ Methods
/ Obstacle avoidance
/ Potential fields
/ Robust control
/ Sensors
/ Sliding mode control
/ SMC
/ Stability augmentation
/ Tracks (paths)
/ Unmanned aerial vehicles
/ virtual force
2024
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Enhanced Multi-UAV Formation Control and Obstacle Avoidance Using IAAPF-SMC
Journal Article
Enhanced Multi-UAV Formation Control and Obstacle Avoidance Using IAAPF-SMC
2024
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Overview
In response to safety concerns pertaining to multi-UAV formation flights, a novel obstacle avoidance method based on an Improved Adaptive Artificial Potential field (IAAPF) is presented. This approach enhances UAV obstacle avoidance capabilities by utilizing segmented attraction potential fields refined with adaptive factors and augmented with virtual forces for inter-UAV collision avoidance. To further enhance the control and stability of multi-UAV formations, a Sliding Mode Control (SMC) method is integrated into the IAAPF-based obstacle avoidance framework. Renowned for its robustness and ability to handle system uncertainties and disturbances, the SMC method is combined with a feedback control system that utilizes inner and outer loops. The outer loop generates the desired path based on the leader’s state and control commands, while the inner loop tracks these trajectories and adjusts the follower UAVs’ motions. This design ensures that obstacle feedback is accounted for before the desired state information is received, enabling effective obstacle avoidance while maintaining formation integrity. Integrating leader-follower formation control techniques with SMC-based multi-UAV obstacle avoidance strategies ensures the effective convergence of the formation velocity and spacing to predetermined values, meeting the cooperative obstacle avoidance requirements of multi-UAV formations. Simulation results validate the efficacy of the proposed method in reaching otherwise unreachable destinations within obstacle-rich environments, while ensuring robust collision avoidance among UAVs.
Publisher
MDPI AG
Subject
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