Multi-UAV Formation Maneuvering Control Based on Q-Learning Fuzzy Controller
On the basis of the relative motion relations of the formation flight, UAV longitudinal and lateral fuzzy controllers are designed to solve the multi-UAV formation control problem. The relative positions between adjacent UAVs are controlled to meet the desired commands and performance requirements. QLearning method, which is one kind of reinforcement learning, is used to tune the corresponding parameters in output membership functions of fuzzy controller. This auto-tuning avoids the complexity of manual tuning with expert experience and eliminates the steady state errors. Also, different conditions including coordinative turning, tense-loose shape changing, shape sequence changing and collision avoiding are simulated with the formation control methodology, which is comprised of centralized decision and decentralized control. The results prove the correctness of control method and formation control strategy under the circumstances of different formation maneuvering demands.
Reinforcement learning Q-learning fuzzy control UAVs Formation Flight Maneuvering
Pang Rui
School of Automation Northwestern Polytechnical University, Xian China University of Sydney Sydney NSW Australia
国际会议
The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)
沈阳
英文
252-257
2010-03-27（万方平台首次上网日期，不代表论文的发表时间）