This paper proposes a method for multiple-aircraft conflict avoidance. We assume that aircraft cruise at constant altitude with varying velocities and that conflicts are resolved in the horizontal plane using heading change, velocity change, or a combination thereof. We assume that each aircraft’s position, heading, and velocity are available to all aircraft involved in the conflict, we constrain the maneuver to be two straight paths of equal length, and we assume that all aircraft initiate conflict resolution maneuvers at the same time and that once an aircraft has initiated a maneuver, its velocity along the maneuver remains constant. Our multiple-aircraft conflict resolution methodology is presented in two steps; first, we consider an unrealistic but geometrically simple exact conflict, in which the original trajectories of all aircraft collide at a point, in order to derive a closed-form analytic solution for the required heading change, and then we consider a realistic inexact conflict, in which conflict points of multiple aircraft do not coincide. Heading change is a main control input for conflict resolution, yet velocity change is also used for an inexact conflict. We then construct a finite partition of the airspace around the conflict, and using our analytic solution, we derive a protocol for resolving the worst-case conflict within each partition. The result is a multiple-aircraft conflict resolution protocol, or a simple rule which is easily understandable and

This paper proposes a protocol-based multiple aircraft conflict resolution for a finite information horizon, in which the communication range of an aircraft is finite. A protocol for multiple aircraft conflict resolution for an infinite information horizon is presented and then this protocol is extended to a finite information horizon problem using graph theory. Communication topology among aircraft is important for the finite information horizon problem and is modeled by a graph called communication graph. We develop a protocol for multiple aircraft conflict resolution based on the communication graph and show the safety of the protocol. Finally, we validate our protocol through simulations with a dynamic aircraft model.

Recent developments in actuator technology have resulted in small, simple flow control devices capable of affecting the flow field over flight vehicles sufficiently to generate control forces. One of the devices which has been under investigation is the Micro-Trailing Edge Effector (MiTE), which consists of a small, 1-5 % chord, vertically sliding flap mounted at the trailing edge. The high bandwidth and good control authority with little required power makes the device an ideal candidate for active control of flutter in high aspect ratio wings. Unfortunately traditional control techniques do not address the non-linear nature of the device or the competing performance goals arising from large numbers of distributed devices. Novel approaches to control design, such as reinforcement learning, are therefore required. To demonstrate the aeroelastic control capability of the MiTEs and to explore reinforcement learning techniques, an experimental model has been designed, fabricated, and tested. This paper details the experimental model and the accompanying analytical model. Design, manufacturing and open loop testing of the experimental model and comparisons with the analytical predictions are presented. This paper also covers the controller design for flutter suppression using reinforcement learning policy search techniques. The results of closed loop testing, resulting in successful flutter suppression with the MiTEs, is presented.

A new laboratory test bed is introduced that enables the hardware-in-the-loop simulation of the autonomous approach and docking of a chaser spacecraft to a target spacecraft of similar mass. The test bed consists of a chaser spacecraft and a target spacecraft simulator floating via air pads on a flat floor. The prototype docking interface mechanism of the Defense Advanced Research Projects Agency’s Orbital Express mission is integrated on the spacecraft simulators. Relative navigation of the chaser spacecraft is obtained by fusing the measurements from a single-camera vision sensor and an inertial measurement unit, through Kalman filters. The target is collaborative in the sense that a pattern of three infrared light emitting diodes is mounted on it as reference for the relative navigation. Eight cold-gas on–off thrusters are used for the translation of the chaser vehicle. They are commanded using a nonlinear control algorithm based on Schmitt triggers. Furthermore, a reaction wheel is used for the vehicle rotation with a proportional derivative linear control. Experimental results are presented of both an autonomous proximity maneuver and an autonomous docking of the chaser simulator to the nonfloating target. The presented results validate the proposed estimation and control methods and demonstrate the capability of the test bed. Nomenclature a = distance of LED 1 and LED 3 from CoM tg

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