L1 Adaptive Output Feedback Controller with Operating Constraints for Solid Oxide Fuel Cells

Lei Pan, Chengyu Cao, Jiong Shen

2014

Abstract

Control on solid oxide fuel cells (SOFC) is challenging due to its nonlinearity, time-varying uncertainties, tight operating constraints and modeling difficulties. The L1 adaptive output feedback controller for systems of unknown relative degree is introduced for the SOFC output voltage control in this paper. It allows for fast and robust adaptation, and provides improved transient performance. Its advantages of not enforcing a strictly positive real condition along with the low-pass filtered control signal bring it the potential to be applied in wide industrial processes. In the study of the SOFC control, a dynamic SOFC model is first built; then a L1 adaptive output feedback controller is designed only using the nominal working conditions of the SOFC model. Through setting the operating constraints at proper locations, the closed-loop stability is maintained in the presence of hard constraints by the symmetric structure of the L1 adaptive control loop. A simulation comparison is made in the SOFC constant voltage control process between the L1 adaptive controller and a linear disturbance model predictive controller (DMPC) for their almost equal complexity in designs. The result shows the advantage of the L1 adaptive controller in disturbance rejections for its faster transient response.

References

  1. Aguiar, P., Adjiman, C., Brandon, N., 2005. Anodesupported intermediate temperature direct internal reforming solid oxide fuel cell: II. Model-based dynamic performance and control. J. Power Sources, 147(1-2), 136-147.
  2. Cao, C., Hovakimyan, N., 2007. Guaranteed transient performance with L1 adaptive controller for systems with unknown time-varying parameters: part I. Proceedings of American Control Conference, New York.
  3. Cao, C., Hovakimyan, N., 2008. L1 adaptive controller for a class of systems with unknown nonlinearities: part I. American Control Conference, Seattle, WA.
  4. Cao, C., Hovakimyan, N., 2008. L1 adaptive controller for nonlinear systems in the presence of unmodelled dynamics: Part II. American Control Conference, Seattle, WA.
  5. Cao, C., Hovakimyan, N., 2008. L1 adaptive controller for systems with unknown time-varying parameters and disturbances in the presence of non-zero trajectory initialization error. International Journal of Control, 81(7), 1147-1161.
  6. Cao, C., Hovakimyan, N., 2009. L1 adaptive output feedback controllers for non-strictly positive real reference systems: missile longitudinal autopilot design. Journal of Guidance, Control, and Dynamics, 32(3), 717-726.
  7. Huo, H. B., Zhu X.J., Hu, W. Q., Tu, H. Y., Li, J., Yang, J., 2008. Nonlinear model predictive control of SOFC based on a Hammerstein model. J. Power Sources, 185(1), 338-344.
  8. Li Y. G., Shen J., Lu J. H., 2011. Constrained model predictive control of a solid oxide fuel cell based on genetic optimization. J. Power Sources, 196, 5873- 5880.
  9. Muske, K. R., Badgwell, T. A., 2002. Disturbance modeling for offset-free linear model predictive control. J. process control, 12(5), 617-632.
  10. Padullés, G. W., Ault, J. R., 2000. An integrated SOFC plant dynamic model for power systems simulation. J. Power Sources, 86(1-2), 495-500.
  11. Pan, L., Shen, J., 2012. Disturbance modeling and offsetfree predictive control for solid oxide fuel cell. 55th ISA POWID Symposium, 492, 293-307.
  12. Pannocchia, G., Rawlings, J. B., 2003. Disturbance models for offset-Free model-predictive control. AIChE Journal, 49(2),426-437.
  13. Pukrushpan, J., A. Stefanopoulou, Peng, H., 2002. Modeling and control for pem fuel cell stack system. In Proc. of the 2002 American Control Conf., Anchorage, AK, pp. 3117-3122.
  14. Stiller, C., Thorud, B., Bolland, O., Kandepu, R., Imsland, L., 2006. Control strategy for a solid oxide fuel cell and gas turbine hybrid system. J. Power Sources, 158(1), 303-315.
  15. Vahidi, A., Stefanopoulou, A., Peng, H., 2004. Model predictive control for starvation prevention of a hybrid fuel cell system. In Proc. of the 2004 American Control Conf., Boston, MA, 834-839.
  16. Wu, X. J., Zhu, X.J., Cao, G.Y, Tu, H.Y., 2008. Predictive control of SOFC based on a GA-RBF neural network model. J. Power Sources, 179(1) , 232-239.
  17. Yang, J., Mou, H. G., Li, J., 2009. Predictive control of solid oxide fuel cell based on an improved TakagiSugeno fuzzy model. J. Power Sources. 193(2), 699-705.
Download


Paper Citation


in Harvard Style

Pan L., Cao C. and Shen J. (2014). L1 Adaptive Output Feedback Controller with Operating Constraints for Solid Oxide Fuel Cells . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 499-507. DOI: 10.5220/0005043604990507


in Bibtex Style

@conference{icinco14,
author={Lei Pan and Chengyu Cao and Jiong Shen},
title={L1 Adaptive Output Feedback Controller with Operating Constraints for Solid Oxide Fuel Cells},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={499-507},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005043604990507},
isbn={978-989-758-039-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - L1 Adaptive Output Feedback Controller with Operating Constraints for Solid Oxide Fuel Cells
SN - 978-989-758-039-0
AU - Pan L.
AU - Cao C.
AU - Shen J.
PY - 2014
SP - 499
EP - 507
DO - 10.5220/0005043604990507