Genetic evolution of controllers for challenging control problems

Journal of Computational Methods in Sciences and Engineering

Volumn 11, Issue 4, 2011, Pages 227-242

  Dracopoulos, Dimitris C ^a  

^a UNIVERSITY OF WESTMINSTER   (United Kingdom)

Author keywords

aircraft control; autolanding; bioreactor control; evolutionary control; Genetic programming

Indexed keywords

AUTO-LANDING; AUTOMATIC CONSTRUCTION; AUTOMATIC CONTROLLERS; BIOREACTOR CONTROL; COMPUTER PROGRAM; CONTROL LAWS; CONTROL PROBLEMS; GENETIC EVOLUTION; HIGH LEVEL DESCRIPTION; OBJECTIVE FUNCTIONS; SPECIFIC PROBLEMS;

AIRCRAFT CONTROL; BENCHMARKING; BIOLOGY; BIOREACTORS; CONTROL THEORY; DYNAMICAL SYSTEMS; GENETIC ALGORITHMS; GENETIC PROGRAMMING; INTELLIGENT SYSTEMS;

CONTROLLERS;

EID: 80052825610     PISSN: 14727978     EISSN: None     Source Type: Journal    
DOI: 10.3233/JCM-2011-0388     Document Type: Article

References (19)

1. C.W. Anderson and W.T. Miller, III. Challenging control problems, in: S. Miller and Werbos, editors, Neural Networks for Control. MIT Press, 1990.
2. K.J. Astrom and B. Wittenmark, Adaptive Control, Addison-Wesley, first edition, 1989.
3. D.C.Dracopoulos, Autolanding of commercial aircrafts by genetic programming, inProceedings of the 2007 International Conference of Computational Intelligence and Intelligent Systems. World Congress on Engineering 2007, IAENG, July 2007.
4. D.C. Dracopoulos and R. Piccoli, Bioreactor control by genetic programming, in: Parallel Problem Solving from Nature (PPSN) XI, R. Schaefer et al., editor, volume II of LNCS 6239, Springer-Verlag Berlin Heidelberg, 2010, pp. 181-188.
5. F.A. Administration, Automatic Landing Systems, 1971. AC 20-57A.
6. John H. Holland. Adaptation in Natural and Artificial Systems, The University of Michigan Press, 1975.
7. C.C. Jorgensen and C. Schley, A neural network baseline problem for control of aircraft flare and touchdown. In Sutton Miller and Werbos, editors, Neural Networks for Control. MIT Press, 1990.
8. J.-G. Juang, H.-H. Chang and K.-C. Cheng, Intelligent landing control using linearlized inverse aircraft model. In Proceedings of the American Control Conference, pages 3269-3274, 2002.
9. J.-G. Juang andK.-C.Cheng, Wind disturbances encountered during controlled landings using neural network approaches. In Proceedings of the 2001 IEEE International Conference on Control Applications, pages 825-840, 2001.
10. J.R. Koza, Genetic Programming, MIT Press, 1992.
11. J.R. Koza, Genetic Programming II, MIT Press, 1994.
12. Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs. Springer Verlag, 1996.
13. K.S. Narendra and A.M. Annaswamy, Stable Adaptive Systems, Prentice Hall, 1989.
14. E.H.J. Pallett and S. Coyle, Automatic Flight Control, Blackwell Science, fourth edition, 1993.
15. R. Poli,W.B. Langdon and N.F.McPhee, A field guide to genetic programming, Published via http://lulu.com and freely available at http://www.gp-field-guide.org.uk, 2008. (With contributions by J. R. Koza).
16. L.H. Ungar, A bioreactor benchmark for adaptive network-based process control. In Sutton Miller and Werbos, editors, Neural Networks for Control. MIT Press, 1990.
17. P. Werbos, ADP: Goals, Opportunities and Principles, in: Handbook of Learning and Approximate Dynamic Programming, J. Si, A.G. Barto, W.B. Powell and D. Wunch II, editors, Wiley, 2004, pp. 3-44.
18. P.A. Whigham and G. Dick, Implicitly controlling bloat in genetic programming, Evolutionary Computation, IEEE Transactions on 14(2) (April 2010), 173-190
19. D.A. White and D.A. Sofge, editors, Handbook of Intelligent Control, Van Nostrand Reinhold, 1992.