On Fusion of Soft and Hard Computing: Traditional (“Hard Computing”) Optimal Rescaling Techniques Simplify Fuzzy Control

Hugh F. VanLandingham () and Vladik Kreinovich ()
Additional contact information
Hugh F. VanLandingham: Virginia Polytechnic Institute and State University, The Bradley Department of Electrical Engineering
Vladik Kreinovich: University of Texas at El Paso, Department of Computer Science

Chapter Chapter 4 in Fuzzy Optimization, Decision-making and Operations Research, 2023, pp 73-86 from Springer

Abstract: Abstract One of the main objectives of fuzzy control is to translate expert rules –formulated in imprecise (“fuzzy”) words from natural language– into a precise control strategy. This translation is usually done in two steps. First, we apply a fuzzy control methodology to get a rough approximation of the expert’s control strategy, and then we tune the resulting fuzzy control system. The first step (getting a rough approximation) is well analyzed. Having an expert’s intuitive understanding enables us to use soft computing techniques to perform in this step. At this first step, we only use expert rules. Then, we test the resulting control on a real or simulated system and tune the resulting control based on the results of this testing. This second (tuning) step is much more difficult: we no longer have any expert understanding of which tuning is better, and therefore, soft computing techniques are not that helpful. In this chapter, we present a particular case of the tuning problem as a traditional optimization problem and solve it by using traditional (“hard computing”) techniques. In a practical industrial control example, we show that the resulting fusion of soft computing (for a rough approximation) and hard computing (for tuning) leads to high-quality control.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-35668-1_4

Ordering information: This item can be ordered from
http://www.springer.com/9783031356681

DOI: 10.1007/978-3-031-35668-1_4

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().