Optimal Cooperative Guidance Laws for Two UAVs Under Sensor Information Deficiency Constraints.

Area of Science:

• Aerospace Engineering
• Control Theory
• Robotics

Background:

• Cooperative guidance for multiple unmanned aerial vehicles (UAVs) is critical for complex missions.
• Information constraints, such as limited sensor data availability, pose significant challenges in decentralized control.
• Achieving precise relative approach angles is a key requirement for effective UAV cooperation.

Purpose of the Study:

• To derive closed-form optimal cooperative guidance laws for two UAVs.
• To address information constraints within a decentralized optimal control framework.
• To ensure the achievement of required relative approach angles for cooperative missions.

Main Methods:

• Formulation of a two-player partially nested decentralized optimal control problem.
• Application of the state-separation principle to decompose the problem into two centralized subproblems.
• Derivation of explicit, closed-form guidance laws based on the decentralized optimal control solution.

Main Results:

• Closed-form optimal cooperative guidance laws are presented.
• The derived laws effectively manage information constraints and coupled terminal velocity vector constraints.
• Guidance laws are shown to be efficiently implementable on standard guidance hardware.

Conclusions:

• The proposed guidance laws provide an effective solution for cooperative UAV guidance under information constraints.
• The method enables robust performance in networked two-UAV systems with nonlinear engagement kinematics.
• This work contributes to advancing autonomous cooperative control strategies for UAVs.