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Journal of Intelligent & Robotic Systems

, Volume 68, Issue 1, pp 69–85 | Cite as

Terrain Avoidance Nonlinear Model Predictive Control for Autonomous Rotorcraft

  • Bruno J. N. Guerreiro
  • Carlos Silvestre
  • Rita Cunha
Article

Abstract

This paper describes a terrain avoidance control methodology for autonomous rotorcraft applied to low altitude flight. A simple nonlinear model predictive control (NMPC) formulation is used to adequately address the terrain avoidance problem, which involves stabilizing a nonlinear and highly coupled dynamic model of a helicopter, while avoiding collisions with the terrain as well as preventing input and state saturations. The physical input saturations are made intrinsic to the model, such that the control is always admissible and the MPC design is simplified. A comparison of several optimization approaches is provided, where the performance of the traditional gradient method with fixed step is compared with the quasi-Newton method and a line search algorithm. The simulation results show that the adopted strategy achieves good performance even when the desired path is on collision course with the terrain.

Keywords

Helicopter control Obstacle avoidance Model-based control Predictive control Nonlinear models 

Mathematics Subject Classification (2010)

49J15 49N90 

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Bruno J. N. Guerreiro
    • 1
  • Carlos Silvestre
    • 1
    • 2
  • Rita Cunha
    • 1
  1. 1.Institute for Systems and Robotics (ISR), Instituto Superior Técnico (IST)LisbonPortugal
  2. 2.Faculty of Science and TechnologyUniversity of MacauTaipaMacau

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