Youkyung Hong

Integrated Design of Rotary UAV Guidance and Control Systems Utilizing Sliding Mode Control Technique

In this paper, the Integrated Guidance and Control (IGC) law is proposed for the Rotary Unmanned Aerial Vehicle (RUAV). The objective of the IGC law is to consider the nonlinear dynamic characteristics of the RUAV and to design a guidance law which takes into consideration the nonlinear relationship between kinematics and dynamics. In order to control the RUAV system, sliding mode control scheme is adopted. As the RUAV is an under-actuated system, a slack variable approach is used to generate the available control inputs. Through the Lyapunov stability theorem, the stability of the proposed IGC law is proved. In order to verify the performance of the IGC law, numerical simulations are performed for waypoint tracking missions.

Conflict Management in Air Traffic Control Using Complexity Map

This study proposes a new method of conflict management in air traffic control that ensures a safe distance between aircraft while minimizing the workload for sector controllers. When an aircraft approaches a sector, the proper entry point is determined based on the concept of a complexity map. Using detailed information on how the traffic responds to an entering aircraft provided by the complexity map, its entry point can be modified to minimize the conflicts inside the sector. To compute the complexity map efficiently, the reachable entry points on the sector boundary are defined considering the maneuverability of the entering aircraft. Next, the variance quadtree algorithm is utilized to construct a grid of the complexity map in a coarse-to-fine manner. The performance of the proposed algorithm is verified by numerical simulations.

Conflict Management Considering a Smooth Transition of Aircraft Into Adjacent Airspace

A new framework for conflict resolution in air traffic control is studied using air traffic complexity, which ensures conflict avoidance among aircraft and smooth transition of aircraft into adjacent airspace. The air traffic complexity is modeled as deviations in heading angle or speed of the aircraft inside a sector to resolve any conflict induced by the entering aircraft. For conflict management in multisector planning, a two-level hierarchical architecture is proposed. In the higher level, the maneuver constraints of the aircraft are constructed to minimize complexity for the neighboring sectors. In the lower level, the conflict avoidance problem is formulated as a mixed integer linear programming considering the maneuver constraints, which are defined in the higher level. With the two-level hierarchical architecture, the aircraft can find the optimal solution to resolve conflicts among the aircraft and reduce the air traffic complexity of the neighboring sectors. The performance of the proposed conflict management is demonstrated using numerical simulations.

Nonlinear Conflict Resolution and Flow Management Using Particle Swarm Optimization

A new optimization problem to resolve conflicts by allowing aircraft to change both their heading angle and speed is considered. The performance index in the optimization problem is formulated to reduce the variation of the aircraft arrival time that is caused by conflict resolution maneuvers. To achieve both conflict resolution and flow management, metering constraints are introduced together with separation constraints. Even though the performance index and constraints are nonlinear, the optimal solution can be easily obtained by utilizing particle swarm optimization. Numerical simulations are performed to evaluate the performance of the proposed algorithm, and the numerical experimental results showed a significant reduction in the variation of the aircraft arrival time as well as the magnitude of heading angle and speed changes.

Application of Complexity Map to Reduce Air Traffic Complexity in a Sector

A decision making procedure for an aircraft entering a sector is proposed to reduce the degree of air traffic complexity. The entering aircraft determines the proper entry point based on a complexity map to minimize the influence of the entering aircraft on other aircraft inside the sector. The variance quadtree (VQT) algorithm is adopted to make a grid in a coarse-to-fine manner, and therefore the complexity map can be constituted efficiently. In this procedure, considering the maneuver limitation of the entering aircraft, Dubins path is utilized to generate a feasible flight path. The effect of the shortest lookahead distance allowed for the entering aircraft is analyzed using Monte Carlo simulation, and the performance of the proposed algorithm is demonstrated by numerical simulation.

Optimal Scheduling Algorithm for Air Traffic Point Merge System Using MILP

This study proposes an optimal scheduling algorithm for air traffic Point Merge System (PMS) which is a new arrival flow integration technique. Performance index and constraint equations are derived with consideration for the characteristics of PMS. Mixed integer linear programming formulation is used to design arrival procedures conducted in PMS. Through numerical simulations, the effect of the number of points constituting PMS on performance index is investigated, and an example is introduced where the entering or final merging time of a particular flight in PMS is predetermined.

Dynamic Robust Sequencing and Scheduling Under Uncertainty for the Point Merge System in Terminal Airspace

This paper proposes a new sequencing and scheduling algorithm for the point merge system based on mixed integer linear programming considering the uncertain flight time of aircraft. In the first stage of the proposed algorithm, for a static environment, deterministic robust solutions are determined. To consider the uncertainty, an extra buffer is introduced in the sequencing and scheduling algorithm, and the buffer size is analytically derived by generating a deterministic robust counterpart problem. In the second stage, to compensate for unforeseen situations under a dynamic environment, the static solution determined in the first stage is adjusted by using the proposed heuristic algorithm, with a sliding time window to reduce the computational load. The performances of the proposed algorithm are verified via numerical simulations based on historical data analysis.