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Evolutionary Algorithms in Supervision of Error-Free Control

Evolutionary Algorithms in Supervision of Error-Free Control

Bohumil Sulc, David Klimanek
Copyright: © 2010 |Pages: 10
ISBN13: 9781605668147|ISBN10: 1605668141|ISBN13 Softcover: 9781616923068|EISBN13: 9781605668154
DOI: 10.4018/978-1-60566-814-7.ch003
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MLA

Sulc, Bohumil, and David Klimanek. "Evolutionary Algorithms in Supervision of Error-Free Control." Soft Computing Applications for Database Technologies: Techniques and Issues, edited by K. Anbumani and R. Nedunchezhian, IGI Global, 2010, pp. 39-48. https://doi.org/10.4018/978-1-60566-814-7.ch003

APA

Sulc, B. & Klimanek, D. (2010). Evolutionary Algorithms in Supervision of Error-Free Control. In K. Anbumani & R. Nedunchezhian (Eds.), Soft Computing Applications for Database Technologies: Techniques and Issues (pp. 39-48). IGI Global. https://doi.org/10.4018/978-1-60566-814-7.ch003

Chicago

Sulc, Bohumil, and David Klimanek. "Evolutionary Algorithms in Supervision of Error-Free Control." In Soft Computing Applications for Database Technologies: Techniques and Issues, edited by K. Anbumani and R. Nedunchezhian, 39-48. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-814-7.ch003

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Abstract

Evolutionary algorithms are well known as 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. The 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 (so called software redundancy) of sensor discredibility detection. Software redundancy is a more economical way than the usual hardware redundancy, which is otherwise necessary in control loop protection against this small, invisible control error occurrence. New results from a long-term tracking residuum trends show that credibility loss can be forecasted. Operators can be warned in advance that the sensor measuring the controlled variable needs to be exchanged. This need can be effectively reflected in maintenance plans. 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, a 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. The application of the used evolutionary algorithms inclusive terminology transfer in this application area can serve as an explanatory case study to help readers gain a better understanding of the how the evolutionary algorithms operate.

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