The role of fuzzy logic in modeling, identification and control
In the nearly four decades which have passed since the launching of the Sputnik, great progress has been achieved in our understanding of how to model, identify and control complex systems. However, to be able to design systems having high MIQ (Machine Intelligence Quotient), a profound change in th...
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| Format: | Article |
| Language: | English |
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Norwegian Society of Automatic Control
1994-07-01
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| Series: | Modeling, Identification and Control |
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| Online Access: | http://www.mic-journal.no/PDF/1994/MIC-1994-3-9.pdf |
| Summary: | In the nearly four decades which have passed since the launching of the Sputnik, great progress has been achieved in our understanding of how to model, identify and control complex systems. However, to be able to design systems having high MIQ (Machine Intelligence Quotient), a profound change in the orientation of control theory may be required. More specifically, what may be needed is the employment of soft computing - rather than hard computing - in systems analysis and design. Soft computing - unlike hard computing - is tolerant of imprecision, uncertainty and partial truth. |
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| ISSN: | 0332-7353 1890-1328 |