Genetic and Evolutionary Computation – GECCO 2004

During the last years the use of intelligent strategies for tuning Proportional-Integral-Derivative (PID) controllers has been growing. The evolutionary strategies have won an important place thanks to their flexibility. In this paper, the automatic tuning of systems with stable and unstable dynamics, through a genetic approach is presented. The advantages of the proposed approach ere highlighted through the comparison with the Ziegler-Nichols modified closed loop method, and the Visioli genetic approach. The proposed methodology goal is to expand the intelligent tuning application to a wider range of processes (covering systems with oscillatory or unstable modes).

[1]  Holger H. Hoos,et al.  Stochastic local search - methods, models, applications , 1998, DISKI.

[2]  Thomas Stützle,et al.  Local Search Algorithms for SAT: An Empirical Evaluation , 2000, Journal of Automated Reasoning.

[3]  Alex S. Fukunaga.  Efficient Implementations of SAT Local Search , 2004, SAT.

[4]  Elena Marchiori,et al.  Evolutionary Algorithms for the Satisfiability Problem , 2002, Evolutionary Computation.

[5]  Günter Rudolph,et al.  An Evolutionary Algorithm for Integer Programming , 1994, PPSN.

[6]  R. Cleve,et al.  Quantum algorithms revisited , 1997, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[7]  David J. Montana,et al.  Strongly Typed Genetic Programming , 1995, Evolutionary Computation.

[8]  Mika Hirvensalo.  Quantum Computing , 2001, Natural Computing Series.

[9]  Dale Schuurmans,et al.  Local search characteristics of incomplete SAT procedures , 2000, Artif. Intell..

[10]  Hector J. Levesque,et al.  Hard and Easy Distributions of SAT Problems , 1992, AAAI.

[11]  Bart Selman,et al.  Evidence for Invariants in Local Search , 1997, AAAI/IAAI.

[12]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[13]  Bart Selman,et al.  Noise Strategies for Improving Local Search , 1994, AAAI.

[14]  Peter F. Stadler,et al.  Complex Adaptations and the Structure of Recombination Spaces , 1997 .

[15]  Hans-Paul Schwefel,et al.  Evolution and optimum seeking , 1995, Sixth-generation computer technology series.

[16]  Bart Selman,et al.  Domain-Independent Extensions to GSAT: Solving Large Structured Satisfiability Problems , 1993, IJCAI.

[17]  Ingo Rechenberg,et al.  Evolutionsstrategie '94 , 1994, Werkstatt Bionik und Evolutionstechnik.