论文信息 - Increasing Predictability and Performance in UAS Flight Contingencies using AIDL and MPC - 字舞流文

Increasing Predictability and Performance in UAS Flight Contingencies using AIDL and MPC

Eduardo F. Camacho | Antonio J. Gallego | Francisco Gavilan | Rafael Vazquez | Alberto Lobato | Mario de la Rosa | Michael W. Hardt | Francisco A. Navarro | A. J. Gallego | M. Hardt | E. Camacho | R. Vázquez | Francisco Gavilan | A. Lobato | Mario de la Rosa | F.A. Navarro

[1] Shahriar Keshmiri,et al. Online artificial neural network model‐based nonlinear model predictive controller for the meridian UAS , 2013 .

[2] Eduardo F. Camacho,et al. An iterative model predictive control algorithm for UAV guidance , 2015, IEEE Transactions on Aerospace and Electronic Systems.

[3] Marko Bacic,et al. Model predictive control , 2003 .

[4] Eduardo F. Camacho,et al. Chance-constrained model predictive control for spacecraft rendezvous with disturbance estimation , 2012 .

[5] Sergio Esteban,et al. Trajectory tracking for fixed-wing UAV using model predictive control and adaptive backstepping , 2015 .

[6] Jonathan P. How,et al. Cooperative Distributed Robust Trajectory Optimization Using Receding Horizon MILP , 2011, IEEE Transactions on Control Systems Technology.

[7] João Borges de Sousa,et al. Receding horizon flight control for trajectory tracking of autonomous aerial vehicles , 2013 .

[8] E. Gagnon,et al. UAV Guidance with Control of Arrival Time , 2007, 2007 American Control Conference.

[9] Jonathan P. How,et al. Model predictive control of vehicle maneuvers with guaranteed completion time and robust feasibility , 2003, Proceedings of the 2003 American Control Conference, 2003..