A conjugate gradient-based BPTT-like optimal control algorithm

Proceedings of the IEEE International Conference on Control Applications

Volumn , Issue , 2009, Pages 861-866

  Kasać, Josip ^a   Deur, Joško ^a   Novaković, Branko ^a   Kolmanovsky, Ilya V ^b  

^a UNIVERSITY OF ZAGREB   (Croatia)

^b FORD RESEARCH LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL TIME; CONJUGATE GRADIENT; CONJUGATE GRADIENT ALGORITHMS; GRADIENT ALGORITHM; LEARNING RATES; NONLINEAR MULTIVARIABLE SYSTEMS; NUMERICAL ALGORITHMS; OPTIMAL CONTROL ALGORITHM; OPTIMAL CONTROLS; STATE VECTOR; SUBSTANTIAL REDUCTION; VEHICLE DYNAMICS CONTROLS;

CONJUGATE GRADIENT METHOD; MULTIVARIABLE SYSTEMS;

LEARNING ALGORITHMS;

EID: 74049150018     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCA.2009.5281028     Document Type: Conference Paper

References (22)

1. J. T. Betts and W. P. Huffman, "Application of sparse nonlinear programming to trajectory optimization," J. Guidance Control Dynamics, vol. 15, no. 1, pp. 198-206, 1992.
2. I. Y. M. Smets, K. J. E. Versyck and J. F. M. Van Impe, "Optimal control theory - A generic tool for identification and control of (Bio-) Chemical Reactors," Annual Reviews in Control, vol. 26, pp. 57-73, 2002.
3. O. von Stryk and M. Schlemmer, "Optimal control of the industrial robot Manutec," in: Bulirsch, R., Kraft D. (eds.), Computational Optimal Control, International Series of Numerical Mathematics 115, Basel, Birkhauser, pp. 367-382, 1994.
4. I. V. Kolmanovsky, and A. G. Stefanopoulou, "Optimal control techniques for assessing feasibility and defining subsystem level requirements: An automotive case study," IEEE Trans. on Control System Technology, vol. 9, no. 3, pp. 524-534, May 2001.
5. J. Kasać, J. Deur, B. Novaković, M. Hancock, and F. Assadian, "Optimization of global chassis control variables," 17th IFAC World Congress, July 6-11, 2008, Seoul, Korea.
6. J. T. Betts, Practical Methods for Optimal Control using Nonlinear Programming, Society of Industrial and Applied Mathematics, Philadelphia, PA, 2001.
7. O. von Stryk, and R. Bulirsch, "Direct and indirect methods for trajectory optimization," Annals of Operations Research, vol. 37, pp. 357-373, 1992.
8. O. von Stryk, "Numerical solution of optimal control problems by direct collocation," in: Bulirsch R., Miele A., Stoer J., Well K.H. (eds.), Optimal Control-Calculus of Variations, Optimal Control Theory and Numerical Methods, International Series of Numerical Mathematics, vol. 111, Basel, Birkhauser, pp. 129-143, 1993.
9. A. L. Schwartz, "Theory and implementation of numerical methods based on Runge-Kutta integration for solving optimal control problems," PhD Thesis, University Of California At Berkeley, 1996.
10. J. Kasać and B. Novaković, "Neural network application to optimal control of nonlinear systems," Proceedings of 7-th International Conference on Computer Aided Optimum Design of Structures, May 28-30, 2001, Bologna, Italy, pp. 359-368.
11. P. J. Werbos, "Backpropagation through time: What it does how to do it," Proceedings of the IEEE, vol. 78, no. 10, pp. 1550-1560, 1990.
12. A. E. Bryson and Y. Ho, Applied Optimal Control, Hemisphere Publishing Corp, 1975.
13. J. Kasać, "Optimal control of nonlinear systems using neural networks," Master Thesis, University of Zagreb, 1998.
14. J. Kasać, J. Deur, B. Novaković, and I. Kolmanovsky, "A BPTT-like optimal control algorithm with vehicle dynamics control application," Proceedings of the 2008 ASME International Mechanical Engineering Congress & Exposition, October 31-November 6, 2008, Boston, Massachusetts, USA.
15. M. Hancock, "Vehicle handling control using active differentials," Ph.D. Thesis, University of Loughborough, UK, 2006.
16. E. Hairer, S. P. Norsett, and G. Wanner, Solving Ordinary Differential Equations I - Nonstiff Problems, 2nd ed., Springer, Berlin, 1993.
17. J. Nocedal and S. J. Wright, Numerical Optimization, Springer, New York, 2006.
18. J. A. Snyman, Practical Mathematical Optimization, Springer, New York, 2005.
19. C. A. Floudas and P. M. Pardalos, (edit.), Encyclopedia of Optimization, Springer, New York, 2008.
20. C. G. H. Jondarr, "Back propagation family album," Technical Report C/TR96-05, Macquarie University, August 1996.
21. T. Tollenaere, "Supersab: Fast adaptive backpropagation with good scaling properties," Neural Networks, no. 3, vol. 5, 1990.
22. M. Riedmiller, "Advanced supervised learning in multi-layer perceptrons - From backpropagation to adaptive learning algorithms," Int. J. Comput. Standards Interfaces, vol. 16, pp. 265, 1994.