Fuzzy Model Predictive Formation Maneuver Control of Multi-AAVs With Interval Output-Constrained
Zhixu Du, Hao Zhang, Zhuping Wang, Huaicheng Yan
Abstract
This article considers the formation control of multiple autonomous aerial vehicles (AAVs), where the AAVs operate in dynamic environments with multiple obstacles and narrow (constrained) areas. A new fuzzy model predictive interval output-constrained maneuver formation control method for AAVs is proposed. The interval output constraint algorithm utilizes the distance information to implement output constraints and formation changes, which are more practical but more challenging than the output constraint problem based on user-assigned settling time, especially in narrow areas. One of the distinctive advantages of the proposed output-constrained model predictive controller is that it can activate formation changes and output constraints for AAVs when passing through narrow space, and it can automatically restore the formation of AAVs and deactivate the output constraints when the AAVs are far away from the narrow space. Unlike most nonlinear model predictive control strategy, where predictive control relies on the accurate underlying dynamical system, the article introduces adaptive fuzzy updating law to receding horizon optimization algorithm to estimate and compensate unknown dynamics and external disturbances. Two potential field functions are designed to safely track in 3-D environments with obstacles. Finally, several examples are provided to illustrate the effectiveness of the proposed controller.