Advertisement

LiDAR-Based Control of Autonomous Rotorcraft for Inspection of Pole-Shaped Structures

  • Bruno J. Guerreiro
  • Carlos Silvestre
  • Rita Cunha
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 417)

Abstract

This paper addresses the problem of trajectory tracking control of autonomous rotorcraft relative to pole-shaped structures using LiDAR sensors. The proposed approach defines an alternative kinematic model, directly based on LiDAR measurements, and uses a trajectory-dependent error space to express the dynamic model of the vehicle. An LPV representation with piecewise affine dependence on the parameters is adopted to describe the error dynamics over a set of predefined operating regions. The synthesis problem is stated as a continuous-time \(\mathcal {H}_2\) control problem, solved using LMIs and implemented within the scope of gain-scheduling control theory. The performance of the proposed control method is validated with comprehensive simulation results.

Keywords

Trajectory tracking Sensor-based control LiDAR UAV 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cunha, R.: Advanced Motion Control for Autonomous Air Vehicles. Ph.D. thesis, Instituto Superior Técnico, Universidade Técnica de Lisboa, Lisbon, Portugal, June 2007Google Scholar
  2. 2.
    Cunha, R., Antunes, D., Gomes, P., Silvestre, C.: A path-following preview controller for autonomous air vehicles. In: AIAA Guidance, Navigation and Control Conference. AIAA, Keystone, CO, August 2006Google Scholar
  3. 3.
    Frazzoli, E., Dahleh, M., Feron, E.: Trajectory tracking control design for autonomous helicopters using a backstepping algorithm. In: Proceedings of the 2000 American Control Conference, vol. 6, pp. 4102–4107 (2000)Google Scholar
  4. 4.
    Ghaoui, L., Niculescu, S.I.: Advances in Linear Matrix Inequality Methods in Control. Society for Industrial and Applied Mathematics, SIAM, Philadelphia, PA (1999)Google Scholar
  5. 5.
    Guerreiro, B.J., Silvestre, C., Cunha, R.: Terrain avoidance nonlinear model predictive control for autonomous rotorcraft. Journal of Intelligent & Robotic Systems 68(1), 69–85 (2012)CrossRefzbMATHGoogle Scholar
  6. 6.
    Guerreiro, B.J.: Sensor-based Control and Localization of Autonomous Systems in Unknown Enviornments. Ph.D. thesis, Instituto Superior Técnico, University of Lisbon (2013) (unpublished)Google Scholar
  7. 7.
    Kaminer, I., Pascoal, A., Khargonekar, P.P., Coleman, E.E.: A velocity algorithm for the implementation of gain-scheduled controllers. Automatica 31(8), 1185–1191 (1995)CrossRefMathSciNetzbMATHGoogle Scholar
  8. 8.
    Padfield, G.D.: Helicopter Flight Dynamics: The Theory and Application ofFlying Qualities and Simulation Modeling. AIAA Education Series, AIAA, Washington DC (1996)Google Scholar
  9. 9.
    Rugh, W.J., Shamma, J.S.: Research on gain scheduling. Automatica 36(10), 1401–1425 (2000). Survey PaperCrossRefMathSciNetzbMATHGoogle Scholar
  10. 10.
    Scherer, C., Weiland, S.: Lecture notes on linear matrix inequality methods in control. Dutch Institute of Systems and Control (2000)Google Scholar
  11. 11.
    Silvestre, C., Pascoal, A., Kaminer, I.: On the design of gain-scheduled trajectory tracking contollers. International Journal of Robust and Nonlinear Control 12(9), 797–839 (2002)CrossRefMathSciNetzbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Bruno J. Guerreiro
    • 1
    • 3
  • Carlos Silvestre
    • 1
    • 2
  • Rita Cunha
    • 3
  1. 1.Department of Electrical and Computer Engineering, Faculty of Science and TechnologyUniversity of MacauTaipaMacau, China
  2. 2.Instituto Superior TécnicoUniversidade de LisboaLisboaPortugal
  3. 3.Institute for Systems and Robotics, Instituto Superior TécnicoUniversidade de LisboaLisboaPortugal

Personalised recommendations