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Complementary control for robots with actuator redundancy: an underwater vehicle application

Published online by Cambridge University Press:  06 March 2015

Giovanni Indiveri  and
Alessandro Malerba
Giovanni Indiveri*
Affiliation:
Dipartimento Ingegneria Innovazione, Università a del Salento, via Monteroni, 73100 Lecce, Italy
Alessandro Malerba
Affiliation:
Dipartimento Ingegneria Innovazione, Università a del Salento, via Monteroni, 73100 Lecce, Italy
*
*Corresponding author. E-mail: giovanni.indiveri@unisalento.it
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Summary

Complementary filtering is a frequency based method used to design data processing algorithms exploiting signals with complementary spectra. The technique is mostly used in sensor fusion architectures, but it may also be effective in the design of state estimators. In spite of its potential in several areas of robotics, the complementary filtering paradigm is poorly used as compared to alternative time domain methods. The first part of the paper aims at reviewing the basics of complementary filtering in sensor data processing and linear systems state estimation. The second part of the paper describes how to exploit the main ideas of complementary filtering to design a depth controller for an actuator redundant autonomous underwater vehicle (AUV). Unlike with alternative state space methods commonly used to address the design of control solutions for actuator redundant systems, the proposed approach allows to fully exploit the knowledge of frequency characteristics of actuators. Simulation results are reported to demonstrate the effectiveness of the proposed solution.

Keywords

Redundant actuation robot controlMarine systemsMotion controlRobot controlAutonomous vehiclesComplementary filtering
Type
Articles
Information
Robotica , Volume 35 , Issue 1 , January 2017 , pp. 206 - 223
Copyright
Copyright © Cambridge University Press 2015 

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References

1. Alvarez, A., Caffaz, A., Caiti, A., Casalino, G., Gualdesi, L., Turetta, A. and Viviani, R., “Folaga: A low-cost autonomous underwater vehicle combining glider and AUV capabilities,” Ocean Eng. 36, 24–38 (2008).Google Scholar
2. Åström, K. and Hägglund, T., PID Controllers: Theory, Design, and Tuning, 2nd ed. (ISA: The Instrumentation, Systems, and Automation Society, USA, 1995).Google Scholar
3. Caccia, M., Bono, R., Bruzzone, G. and Veruggio, G., “Bottom-following for remotely operated vehicles,” Control Eng. Pract. 11, 461–470 (2003).Google Scholar
4. Caffaz, A., Caiti, A., Casalino, G. and Turetta, A., “The hybrid glider/AUV folaga,” IEEE Robot. Autom. Mag. 17 (1), 31–44 (2010).Google Scholar
5. Cristi, R., Papoulias, F. A. and Healey, A. J., “Adaptive sliding mode control of autonomous underwater vehicles in the dive plane,” IEEE J. Ocean. Eng. 15 (3), 152–160 (1990).Google Scholar
6. Fossen, T. I., Guidance and Control of Ocean Vehicles, 1st ed. (Wiley, England, 1994).Google Scholar
7. Härkegård, O. and Glad, S. T., “Resolving actuator redundancy – optimal control versus control allocation,” Automatica 41 (1), 137–144 (2005).Google Scholar
8. Higgins, W., “A comparison of complementary and Kalman filtering,” IEEE Trans. Aerospace Electron. Syst. AES–11 (3), 321–325 (1975).CrossRefGoogle Scholar
9. Kurtz, R. and Hayward, V., “Multiple-goal kinematic optimization of a parallel spherical mechanism with actuator redundancy,” IEEE Trans. Robot. Autom. 8 (5), 644–651 (1992).Google Scholar
10. Lin, C. F., Modern Navigation, Guidance, and Control Processing, (Prentice Hall, USA, 1991).Google Scholar
11. Mahony, R., Hamel, T. and Pflimlin, J. M., “Nonlinear complementary filters on the special orthogonal group,” IEEE Trans. Autom. Control 53 (5), 1203–1218 (2008).Google Scholar
12. Malerba, A. and Indiveri, G. “Complementary Control of the Depth of an Underwater Robot,” Proceedings of the 2014 IFAC World Congress, IFAC, Cape Town, South Africa, vol. 19 (2014) pp. 8971–8976.Google Scholar
13. Salvucci, V., Kimura, Y., Oh, S., Koseki, T. and Hori, Y., “Comparing approaches for actuator redundancy resolution in biarticularly-actuated robot arms,” IEEE/ASME Trans. Mechatronics 19 (2), 765–776 (2014).Google Scholar
14. Silvestre, C. and Pascoal, A. “Depth control of the INFANTE AUV using gain-scheduled reduced order output feedback,” Control Eng. Pract. 15 (7), 883–895 (2007).Google Scholar
15. Sørdalen, O., “Optimal thrust allocation for marine vessels,” Control Eng. Pract. 5 (9), 1223–1231 (1997).Google Scholar
16. Steenson, L. V., Wang, L., Phillips, A. B., Turnock, S. R., Furlong, M. E. and Rogers, E., “Experimentally Verified Depth Regulation for AUVs using Constrained Model Predictive Control,” Proceedings of the 2014 IFAC World Congress, IFAC, Cape Town, South Africa, vol. 19 (2014) pp. 11974–11979.Google Scholar
17. Zanoli, S. and Conte, G. “Remotely operated vehicle depth control,” Control Eng. Pract. 11, 453–459.Google Scholar