A Control Architecture for Optimal Operation with Inductive Learning

Magdalena, Luis; Velasco, Juan R.; Fernández, Gerardo; Monasterio, F.

doi:10.1016/s1474-6670(17)50888-5

IFAC Proceedings Volumes

1992

DOI: 10.1016/s1474-6670(17)50888-5

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A Control Architecture for Optimal Operation with Inductive Learning

Luis Magdalena¹,

Juan R. Velasco²,

Gerardo Fernández³

et al.

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et al.

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)

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The issues raised in advanced process control applications lead control engineers to be aware of the need of integrating advanced information processing (IP) capabilities, in special artificial intelligence (AI) ones, in the process control loop. This is intrinsically a very complex task due to inherent process complexity and AI software heterogeneity.From our point of view, the control of a complex process can be decomposed in a series of IP tasks that require quite different processing capabilities. These capabilities are provided by a set of heterogeneous software chunks -software technology instantiations-that should be integrated to obtain the required global functionality. The design of the final system must be the result of the process of matching the set of process control tasks with the set of technologies in a tightly constrained environment.In the past years, the Intelligent Control Group at the Universidad Politecnica de Madrid has been developing architectures and applications for complex process control based on artificial intelligence technologies. We present some results obtained and comments about the work under development. The most active issues in these days are the specification of an intelligent control system design methadology based on a task-technology map and the integration of specific technologies to obtain synergistic effects; we are specially studying the application and integration of the technologies addressed in this congress: fuzzy control and validation, neurocontrol, neuromodelling and genetic algorithms for optimization and control adaptation.

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A Control Architecture for Optimal Operation with Inductive Learning

Cited by 4 publications

References 4 publications

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Fuzzy controlled gait synthesis for a biped walking machine

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