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Evolutionary Algorithms in Discredibility Detection
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Author(s): Bohumil Sulc (Czech Technical University in Prague, Czech Republic)and David Klimanek (Czech Technical University in Prague, Czech Republic)
Copyright: 2009
Pages: 8
Source title:
Encyclopedia of Artificial Intelligence
Source Author(s)/Editor(s): Juan Ramón Rabuñal Dopico (University of A Coruña, Spain), Julian Dorado (University of A Coruña, Spain)and Alejandro Pazos (University of A Coruña, Spain)
DOI: 10.4018/978-1-59904-849-9.ch087
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Abstract
Evolutionary algorithms are well known optimization techniques suitable for solving various kinds of problems (Ruano, 2005). The new application of evolutionary algorithms represents their use in the detection of biased control loop functions caused by controlled variable sensor discredibility (Klimanek, Sulc, 2005). Sensor discredibility occurs when a sensor transmitting values of the controlled variable provides inexact information, however the information is not absolutely faulty yet. Use of discredible sensors in control circuits may cause the real values of controlled variables to exceed the range of tolerated differences, whereas zero control error is being displayed. However, this is not the only negative consequence. Sometimes, sensor discredibility is accompanied with undesirable and hardly recognizable side effects. Most typical is an increase of harmful emission production in the case of combustion control (Sulc, Klimanek, 2005). We have found that evolutionary algorithms are useful tools for solving the particular problem of finding a software-based way (co-called software redundancy) of sensor discredibility detection. Software redundancy is a more economic way than the usual hardware redundancy, which is otherwise necessary in control loop protection against this small, invisible control error occurrence. Namely, the standard genetic algorithm and the simulated annealing algorithm have been successfully applied and tested to minimize the given cost function; by means of these algorithms newly developed method is able to detect controlled variable sensor discredibility. When applied to combustion processes, production of harmful emissions can be kept within accepted limits. Used application of evolutionary algorithms inclusive terminology transfer reflecting this application area can serve as an explanatory case study helping readers in better understanding the way how the evolutionary algorithms operate.
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