Evolving PID-like Neurocontrollers for Nonlinear Control Problems

S. Doncieux and J.-A. Meyer


  1. [1] A. Isidori, Nonlinear control systems, 2nd ed. (Berlin: Springer-Verlag, 1989).
  2. [2] J.-J. Slotine & W. Li, Applied nonlinear control (Prentice Hall, 1990).
  3. [3] S. Miller & Werbos (Ed.), Neural networks for control (Cambridge, MA: MIT Press, 1990).
  4. [4] A.M.S. Zalzala, Neural networks for robotic control: Theoryand applications (Ellis Horwood, 1996).
  5. [5] J.-A. Meyer, Evolutionary approaches to neural control inmobile robots, Proc. IEEE Int. Conf. on Systems, Man andCybernetics, San Diego, 1998. doi:10.1109/ICSMC.1998.725019
  6. [6] S. Landau, S. Doncieux, A. Drogoul, & J.-A. Meyer, Sferes:Un framework pour la conception de Syst`emes multi-agentsadaptatifs, Technique et Science Informatique, 21(4), 2002.
  7. [7] S. Doncieux & J.-A. Meyer, Evolving neural networks for thecontrol of a lenticular blimp, in G.R. Raidl et al. (Ed.), Applications of evolutionary computing, EvoWorkshops2003: EvoBIO, EvoCOP, EvoIASP, EvoMUSART, EvoROB, EvoSTIM (Berlin: Springer Verlag, 2003).
  8. [8] S. Doncieux, Évolution de controleurs neuronaux pour animats volants: Méthodologie et applications, doctoral diss.,LIP6/AnimatLab, Université Pierre et Marie Curie, Paris,France, 2003.
  9. [9] S. Doncieux & J.-A. Meyer, Evolving modular neural networksto solve challenging control problems, Proc. 4th Int. ICSCSymp. on Engineering of Intelligent Systems (EIS 2004), 2004(forthcoming).
  10. [10] W.R. Ashby, Design for a brain: The origin of adaptivebehavior (Chapman & Hall, 1952).
  11. [11] J.-A. Meyer & A. Guillot, Simulation of adaptive behavior inanimats: Review and prospect, in Meyer and Wilson (Eds),Proc. 1st Int. Conf. on Simulation of Adaptive Behavior(Cambridge, MA: MIT Press, 1991).
  12. [12] T. Bäck & H.P. Schwefel, Evolution strategies 1: Variants andtheir computational implementation, in Genetic Algorithms inEngineering and Computer Science, Proc. First Short CourseEUROGEN-95, 1995.
  13. [13] H.P. Schwefel & T. Bäck, Evolution strategies 2: Theoreticalaspects, in Genetic Algorithms in Engineering and ComputerScience, Proc. First Short Course EUROGEN-95, 1995.
  14. [14] D.E. Goldberg, Genetic algorithms in search, optimization andmachine learning (Addison-Wesley, 1989).
  15. [15] A.C. Schultz & J.J. Grefenstette, Continuous and embedded learning in autonomous vehicles: Adapting to sensor failures, SPIE Int. Symp. on Aerospace/Defence Snesing, Simulation and Controls (AeroSense 2000), 2000.

Important Links:

Go Back