Nonlinear model predictive tracking control for rotorcraft-based unmanned aerial vehicles
- 1 January 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 5 (07431619) , 3576-3581 vol.5
- https://doi.org/10.1109/acc.2002.1024483
Abstract
We investigate the feasibility of a nonlinear model predictive tracking control (NMPTC) for autonomous helicopters. We formulate a NMPTC algorithm for planning paths under input and state constraints and tracking the generated position and heading trajectories, and implement an on-line optimization controller using a gradient-descent method. The proposed NMPTC algorithm demonstrates superior tracking performance over conventional multi-loop proportional-derivative (MLPD) controllers especially when nonlinearity and coupling dominate the vehicle dynamics. Furthermore, NMPTC shows outstanding robustness to parameter uncertainty, and input saturation and state constraints are easily incorporated. When the cost includes a potential function with a possibly moving obstacle or other agents' state information, the NMPTC can solve the trajectory planning and control problem in a single step. This constitutes a promising one-step solution for trajectory generation and regulation for RUAVs, which operate under various uncertainties and constraints arising from the vehicle dynamics and environmental contingencies.Keywords
This publication has 3 references indexed in Scilit:
- Model predictive neural control with applications to a 6 DOF helicopter modelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2001
- Hierarchical control system synthesis for rotorcraft-based unmanned aerial vehiclesPublished by American Institute of Aeronautics and Astronautics (AIAA) ,2000
- CONDUIT - A new multidisciplinary integration environment for flight control developmentPublished by American Institute of Aeronautics and Astronautics (AIAA) ,1997