# Speed-Gradient Adaptive Control for Parametrically Uncertain UAVs in Formation
A joint optimization design for a non-orthogonal multiple access-based satellite-terrestrial integrated network was proposed and studied in [14], and it was shown that the suggested algorithm can improve the computational efficiency of the iterative algorithm in comparison with habitual randomly generated initial points. For networked UAVs, [PERSON] and [PERSON] [15] developed a search and tracking scheme using an adaptive hybrid grouping controller. For search, antennas were placed on at least four UAVs while keeping the system \"+\" in the \(XY\)-plane (east-west/north-south). UAVs on the abscissa axis were controlled by the difference in the signal powers of the eastern and western groups, and along the y-axis by the difference in the respective signal powers of the northern and southern groups. A backstepping controller was derived using the Lyapunov stability criteria to allow the UAV to fly in a \"+\" shape at a fixed altitude. Based on the example of a quadrotor troop formation, [16] proposed a number of approaches for assigning UAV targets using time optimization and gain maximization in two stages. In the first stage, urgently desired targets are selected from the detected target group using the proposed objective function. In the second, appropriate UAVs are assigned for the selected desired targets, taking into account coverage factors, adaptive limitations, and constraints. The problem of cooperative control of a UAV group with finite-time orientation under conditions of external disturbances and parametric uncertainty was considered by [PERSON] et al. [17]. Using a quaternion model of UAV dynamics, a non-singular sliding mode terminal surface was constructed for the event-triggered controller. An adaptive neural network was used to estimate disturbances. Simulation examples were presented illustrating the efficacy of the proposed control algorithm. [PERSON] et al. [18] considered the problem of control over a rigid formation with fixed time for a class of nonlinear multi-agent systems with indefinite dynamics and external disturbances. To compensate for the uncertainty of the system dynamics and disturbances for a fixed time, an adaptive observer was introduced for the state and disturbances. Next, a fixed-time formation control strategy was proposed. The authors proved that the designed controller implements the boundedness of closed-system errors with a fixed time independently of the initial state based on stiffness theory and the Lyapunov approach. Results based on simulations implemented on the UE4 simulation platform confirmed the control of both a single agent and a UAV formation. A distributed adaptive fault-tolerant formation control for heterogeneous multiagent systems with faults in the communication channel was discussed in [19], where a group of heterogeneous multi-agent systems consisting of UAVs and unmanned ground vehicles (UGVs) was considered taking into account parametric uncertainties and failures in communication channels. An adaptive fault-tolerant formation control protocol was developed that uses information about local states for each slave UAV and UGV with different gains, meaning that all slave vehicles track the dynamic trajectory of the virtual leader and simultaneously provide the specified formation in case of communication channel failures or actions due to external disturbances. [PERSON] et al. [20] considered the problem of forming and maintaining the formation of small satellites in near-earth projected circular orbits. In [21], a two-stage algorithm for group UAV guidance was proposed. In the first stage, a consensus algorithm was employed for decentralized multi-agent UAV control. In the second, each UAV was independently guided to the target using a modified proportional 3D guidance law. [PERSON] and [PERSON] [22] presented a geometric adaptive position control system for a quadrotor UAV. The thrust direction, which is critical for position tracking, was controlled irrespective of the yaw direction.