Knowledge-based supervisory process control: applying fuzzy sets to blackboard control architecture

Information granules and ensuing Granular Computing offer interesting opportunities to endow processing with an important facet of human-centricity. This facet implies that the underlying processing supports non-numeric data inherently associated with the variable perception of humans. Systems that commonly become distributed and hierarchical, managing granular information in hierarchical and distributed architectures, is of growing interest, especially when invoking mechanisms of knowledge generation and knowledge sharing. The outstanding feature of human centricity of Granular Computing along with essential fuzzy set-based constructs constitutes the crux of this study. The author elaborates on some new directions of knowledge elicitation and quantification realized in the setting of fuzzy sets. With this regard, the paper concentrates on knowledge-based clustering. It is also emphasized that collaboration and reconciliation of locally available knowledge give rise to the concept of higher type information granules. Other interesting directions enhancing human centricity of computing with fuzzy sets deals with non-numeric semi-qualitative characterization of information granules, as well as inherent evolving capabilities of associated human-centric systems. The author discusses a suite of algorithms facilitating a qualitative assessment of fuzzy sets, formulates a series of associated optimization tasks guided by well-formulated performance indexes, and discusses the underlying essence of resulting solutions.

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Approximate reasoning in knowledge-based fuzzy sets

2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622) ◽

10.1109/nafips.2002.1018100 ◽

2003 ◽

Cited By ~ 1

Author(s):

R. Intan ◽

M. Mukaidono

Keyword(s):

Fuzzy Sets ◽

Approximate Reasoning ◽

Knowledge Based

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Supervisory Control of Drilling

Journal of Engineering for Industry ◽

10.1115/1.2803630 ◽

1996 ◽

Vol 118 (1) ◽

pp. 10-19 ◽

Cited By ~ 12

Author(s):

R. J. Furness ◽

A. Galip Ulsoy ◽

C. L. Wu

Keyword(s):

Process Control ◽

Torque Control ◽

Feed Speed ◽

Machining Time ◽

Control Approach ◽

Drilling Operation ◽

Control Functions ◽

Control Concept ◽

Supervisory Process ◽

And Control

A supervisory process control approach to machining is presented in this paper, and demonstrated by application to a drilling operation. The supervisory process control concept incorporates optimization and control functions in a hierarchical structure. This approach utilizes feedback measurements to parameterize the constraints of a process optimization problem whose solution determines both strategies and references for process control. For this particular drilling operation, a three-phase strategy (utilizing a combination of feed, speed, and torque control) evolved due to inherent variation in constraint activity as a function of hole depth. A controller comparison study was conducted which demonstrates the advantages of this approach compared to (1) uncontrolled “conventional” drilling, (2) feed and speed controlled drilling, and (3) torque and speed controlled drilling. Benefits of reduced machining time, improved hole quality, and the elimination of tool breakage are demonstrated, and the potential economic impact is highlighted for an example production application.

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Knowledge-Based Intelligent Process Control

New Approaches in Intelligent Control - Intelligent Systems Reference Library ◽

10.1007/978-3-319-32168-4_7 ◽

2016 ◽

pp. 207-240

Author(s):

Mihaela Oprea ◽

Sanda Florentina Mihalache ◽

Mădălina Cărbureanu

Keyword(s):

Process Control ◽

Knowledge Based ◽

Intelligent Process ◽

Intelligent Process Control

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