CMAC-based radar target recognition

Teng, Yueyang; Luoh, Leh; Lin, Pei Pei

doi:10.1109/icsse.2011.5961989

Cited by 2 publications

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Cerebellar Model Articulation Controller (CMAC), proposed by Albus 1 in 1975, is widely used in data fusion, 2,3 intelligent control [4][5][6][7] and many other fields [8][9][10][11] for its simple architecture, quick learning convergence and inexistence of local minimum. [12][13][14] For simulating the human cerebellum, however, one drawback of CMAC is its binary input activating function.…”

Section: Introductionmentioning

confidence: 99%

A loading control strategy for electric load simulator based on new mapping approach and fuzzy inference in Cerebellar Model Articulation Controller

Yang

Liu

Zhang

2019

Measurement and Control

View full text Add to dashboard Cite

To improve surplus torque suppression and loading performance of electric load simulators, this paper presents a loading control strategy based on the new mapping approach and fuzzy inference scheme in the fuzzy Cerebellar Model Articulation Controller. The proposed mapping approach and fuzzy inference scheme in the fuzzy Cerebellar Model Articulation Controller, designed free from the mathematical model of system, comprises a mapping fuzzy Cerebellar Model Articulation Controller and a fuzzy inference controller, in which the former is the main controller. By introducing the new mapping approach in mapping fuzzy Cerebellar Model Articulation Controller, the proposed control strategy is actually a global network with local weight updating and its continuity has been enhanced. The fuzzy inference controller is used as a fuzzy compensator. As a torque controlled system, electric load simulator takes the loading error as the performance index. The results of dynamic simulation and experiments indicate that the proposed loading control strategy can achieve favorable control performance.

show abstract