Air traffic controller

Summary

Air traffic control specialists, abbreviated ATCs, are personnel responsible for the safe, orderly, and expeditious flow of air traffic in the global air traffic control system. Usually stationed in air traffic control centers and control towers on the ground, they monitor the position, speed, and altitude of aircraft in their assigned airspace visually and by radar, and give directions to the pilots by radio. The position of air traffic controller is one that requires highly specialized knowledge, skills, and abilities. Controllers apply separation rules to keep aircraft at a safe distance from each other and within proper airspace in their area of responsibility and move all aircraft safely and efficiently through their assigned sector of airspace, as well as on the ground. Because controllers have an incredibly large responsibility while on duty (often in aviation, "on position") and make countless real-time decisions on a daily basis, the ATC profession is consistently regarded a

Official source

https://en.wikipedia.org/wiki/Air_traffic_controller

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (12)

Related publications

Related people

Related units

Related concepts (5)

Related concepts

Related courses (1)

Related courses

Related lectures (1)

Related lectures

Plug-and-Play Model Predictive Control based on robust control invariant sets

Marcello Farina, Giancarlo Ferrari Trecate

We consider the problem of designing decentralized controllers for large-scale linear constrained systems composed by a number of interacting subsystems. As in (Riverso et al., 2013) (i) the design of local controllers requires limited transmission of information from other subsystems and (ii) the addition/removal of a subsystem triggers the design of local controllers for child subsystems only. These properties enable Plug-and-Play (PnP) operations, and we show how to perform them while preserving global stability of the origin and constraint satisfaction. We improve several aspects of the PnP design procedure proposed in (Riverso et al., 2013) and, using recent results in the computation of Robust Control Invariant (RCI) sets, we show that all critical steps in the design of a local controller can be solved through Linear Programming (LP). Finally, an application of the proposed design procedure to a large-scale mechanical system is presented.

2014

In this paper we consider a linear system represented by subsystems coupled through states and propose a distributed control scheme for guaranteeing asymptotic stability and satisfaction of constraints on system inputs and states. Our design procedure enables Plug-and-Play (PnP) operations, meaning that (i) the addition or removal of subsystems triggers the synthesis of local controllers associated to successors to the subsystem only and (ii) the synthesis of a local controller for a subsystem requires information only from predecessors of the subsystem and it can be performed using only local computational resources. Our method, that is based on Model Predictive Control (MPC) advances the PnP design procedure proposed in (Riverso et al., 2013) in several directions. Notably, we show how critical steps in the design of a local controller can be solved through linear programming.

2013

Plug-and-Play Decentralized Model Predictive Control for Linear Systems

Marcello Farina, Giancarlo Ferrari Trecate

In this paper we consider a linear system structured into physically coupled subsystems and propose a decentralized control scheme capable to guarantee asymptotic stability and satisfaction of constraints on system inputs and states. The design procedure is totally decentralized, since the synthesis of a local controller uses only information on a subsystem and its neighbors, i.e. subsystems coupled to it. We show how to automatize the design of local controllers so that it can be carried out in parallel by smart actuators equipped with computational resources and capable to exchange information with neighboring subsystems. In particular, local controllers exploit tube-based Model Predictive Control (MPC) in order to guarantee robustness with respect to physical coupling among subsystems. Finally, an application of the proposed control design procedure to frequency control in power networks is presented.

2013