## 1 Introduction
### Related Research
Moreover, they considered some uncertainties in the general nonlinear model. Finally, they utilized the adaptive fuzzy logic control (FLC) to stabilizing the containment of multi general nonlinear systems. [PERSON] et al. [24] proposed a containment control of multi general linear systems with time-varying. They studied the multi general linear systems with directed network topology. Besides, they utilized the graph theory for the directed network topology. Furthermore, they studied the containment control of multi general linear systems under bounded communication network delays. Moreover,they utilized linear matrix inequalities (LMIs) controller to stabilizing the containment control of multi general linear systems. [PERSON], et al. [25] proposed a multi second-order systems formation control with time-varying. They studied the formation of second-order systems under bounded disturbances. In addition, the fixed network topology of the followers depended on the leader position. Furthermore, they used the graph theory method for the multi second-order systems consensus. Moreover, they utilized a classical proportional-integral controller to stabilize the formation of multi-second order systems. [PERSON] et al. [26] proposed a robust leader-follower control of multi under-actuated UAVs. They utilised the back-stepping controller to stabilizing the UAVs nonlinear model. They handled the UAVs under-actuation using a neural network. Moreover, they used the size reduction matrix for the formation between the UAVs. [PERSON] et al. [27] proposed adaptive leader-follower containment control of multi heterogeneous general linear dynamical systems with unknown leader's. The fixed network topology of the followers depended on the leader's positions. Besides, they used the graph theory method for the multi-heterogeneous general linear dynamics systems consensus. Moreover, they utilized the classical state feedback controller and dynamic output feedback controller to stabilizing the containment control of multi heterogeneous general linear dynamics systems. [PERSON] et al. [28] proposed a super-twisting sliding mode control scheme for multi-robot formation control based on the leader-follower approach. The stability of the closed-loop formation system was investigated using Lyapunov. The presented system showed a good performance against uncertainties and external disturbances. [PERSON] et al. [29] investigated the consensus for second-order multiple robot systems considering both noise and time delay. Based on the frequency domain analysis a consensus algorithm was proposed where the system's characteristic equation was mapped to a quadratic polynomial with purely imaginary eigenvalues. The algorithm had low conservativeness and it could be extended to multi-robot systems with higher-order dynamics. [PERSON] et al. [30] studied the problem of formation control for underactuated surface vessels subjected to modeling uncertainties and external disturbances. Furthermore, the input saturation, collision avoidance, and limited communication scale was considered. For each vessel, a distributed control law was formulated. [PERSON] et al. [31] proposed a distributed dynamic event-triggered control algorithm for the class of second-order agents. These gents have limited communication and can only exchange information locally. The algorithm allows agents to track a time-varying trajectory with a stable performance. In this article, we are proposing multi-UAVs containment control. In an uncertain area some UAVs lead the others. Every UAV throughout the group has to coordinate and establish the required forms concerning their leaders and each other. The distributed method suggests utilizing an \(\mathcal{L}_{1}\) adaptive to stabilize all of the UAVs and using the DDS middleware to share the information among all the UAVs. Last, the graph theory approach is used for the UAV's navigation. The contributions of this paper are:  
* A robust architecture for containment control of multi UAVs is designed.