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Adaptive Performance Seeking Control Using Fuzzy Model Reference Learning Control and Positive Gradient ControlPerformance Seeking Control attempts to find the operating condition that will generate optimal performance and control the plant at that operating condition. In this paper a nonlinear multivariable Adaptive Performance Seeking Control (APSC) methodology will be developed and it will be demonstrated on a nonlinear system. The APSC is comprised of the Positive Gradient Control (PGC) and the Fuzzy Model Reference Learning Control (FMRLC). The PGC computes the positive gradients of the desired performance function with respect to the control inputs in order to drive the plant set points to the operating point that will produce optimal performance. The PGC approach will be derived in this paper. The feedback control of the plant is performed by the FMRLC. For the FMRLC, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for the effective tuning of the FMRLC controller.
Document ID
19970025512
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Kopasakis, George (NASA Lewis Research Center Cleveland, OH United States)
Date Acquired
September 6, 2013
Publication Date
May 1, 1997
Subject Category
Aircraft Propulsion And Power
Report/Patent Number
E-10740
NASA-TM-107455
NAS 1.15:107455
AIAA Paper 97-3191
Meeting Information
Meeting: Joint Propulsion
Location: Seattle, WA
Country: United States
Start Date: July 6, 1997
End Date: July 9, 1997
Sponsors: American Inst. of Aeronautics and Astronautics, American Society for Electrical Engineers, Society of Automotive Engineers, Inc., American Society of Mechanical Engineers
Accession Number
97N25009
Funding Number(s)
PROJECT: RTOP 538-06-AR
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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