OPTIMUM FUZZY MODEL FOR SINGLE INPUT SINGLE OUTPUT DATA SYSTEM

2011 ◽  
Vol 39 (1) ◽  
Author(s):  
Amjad AlSakarneh
Keyword(s):  
Fuzzy Model ◽  
Data System ◽  
Output Data ◽  
Single Input Single Output ◽  
Single Output ◽  
Single Input

THE INTEGRATION OF EXTENSION THEORY TO DESIGN A NEW FUZZY INFERENCE MODEL

2000 ◽  
Vol 09 (04) ◽  
pp. 473-492 ◽  
Author(s):  
YO-PING HUANG ◽  
HUNG-JIN CHEN ◽  
CHI-PENG OUYANG
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Model ◽  
Extension Theory ◽  
Turning Process ◽  
Inference Model ◽  
Single Input Single Output ◽  
Identification Process ◽  
Single Output ◽  
System Requirement ◽  
Single Input

A novel extension-based fuzzy model is proposed in this paper. The newly established extension theory is integrated into the conventional fuzzy system to enhance the reasoning capability. In parameter identification process, adjusting a membership function to satisfy one pattern may deteriorate the others performance and result in a lengthy turning process. This incompatible issue is alleviated by the extension theory. We will investigate how to define the extended relational functions and how to refine the roughly designed model to meet the system requirement. During the refining process, both the fired and the neighborhood of the fired membership functions are adjusted simultaneously. Simulation results from single-input-single-output and double-input-single-output models verified that better results than the conventional methods have been obtained.

An Identification Method With Direct Acquisition of Reduced Order Model From a Steplike Response

2004 ◽  
Vol 126 (4) ◽  
pp. 746-752 ◽  
Author(s):  
Manabu Kosaka ◽  
Hiroshi Uda ◽  
Hiroshi Shibata
Keyword(s):  
Order Model ◽  
Output Data ◽  
Mass System ◽  
Single Input Single Output ◽  
Reduced Order ◽  
Identification Method ◽  
Single Output ◽  
Rational Transfer ◽  
Line Identification ◽  
Single Input

In this paper, we propose a deterministic off-line identification method performed by using input and output data with a constant steady-state output response. The method can directly acquire any order of reduced model without knowing the real order of a plant, in such a way that the intermediate parameters are uniquely determined so as to be orthogonal with respect to 0-N-tuple integral values of output error and irrelevant to the unmodeled dynamics. From the intermediate parameters, the co-efficients of a rational transfer function are calculated. In consequence, the method can be executed for any linear single-input single-output plant without knowing or estimating its order at the beginning. The effectiveness of the method is illustrated by numerical simulations and also by applying it to a two-mass system.

Comparative analysis of SISO and wavelength diversity-based FSO systems at different transmitter power levels

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Varun Srivastava ◽  
Abhilash Mandloi ◽  
Dhiraj Kumar Patel
Keyword(s):  
Optical Signal ◽  
Free Space Optical ◽  
Optical Source ◽  
Transmit Power ◽  
Single Input Single Output ◽  
Transmitter Power ◽  
Single Output ◽  
Communication Links ◽  
Single Input ◽  
Matching Performance

AbstractFree space optical (FSO) communication refers to a line of sight technology, which comprises optical source and detector to create a link without the use of physical connections. Similar to other wireless communication links, these are severely affected by losses that emerged due to atmospheric turbulence and lead to deteriorated intensity of the optical signal at the receiver. This impairment can be compensated easily by enhancing the transmitter power. However, increasing the transmitter power has some limitations as per radiation regulations. The requirement of high transmit power can be reduced by employing diversity methods. This paper presents, a wavelength-based diversity method with equal gain combining receiver, an effective technique to provide matching performance to single input single output at a comparatively low transmit power.

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