Design of intelligent control systems with use of soft computing: conceptions and methods

The general issues of designing the hybrid intelligent control systems based on rational combination of different knowledge processing technologies is discussed. The principles of structural construction of such systems are considered. A general approach to design of hierarchical intelligent control systems, based on the expert estimation of complexity of control object, its environment, control objective and subsequent determination of specifications to different control levels of the systems, is proposed. The example of design of hybrid intelligent system for control of autonomous mobile vehicle in the conditions of uncertainty is presented.

[1]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[2]  Maysam F. Abbod,et al.  Multi-objective genetic optimisation for self-organising fuzzy logic control , 1998 .

[3]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[4]  Frank Klawonn,et al.  Modifications of genetic algorithms for designing and optimizing fuzzy controllers , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

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

[6]  Lotfi A. Zadeh The roles of soft computing and fuzzy logic in the conception, design and deployment of intelligent systems , 1997, Proceedings of 6th International Fuzzy Systems Conference.

[7]  Martin Brown,et al.  Advances in neurofuzzy algorithms for real-time modelling and control , 1996 .

[8]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[9]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[10]  Piero P. Bonissone,et al.  Soft computing: the convergence of emerging reasoning technologies , 1997, Soft Comput..

[11]  Madan M. Gupta Fuzzy-Neural Computing Systems: Recent Developments and Future Directions , 1997, Fuzzy Days.

[12]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[13]  K. S. Narendra,et al.  Neural networks for control theory and practice , 1996, Proc. IEEE.