Adaptive fuzzy fault tolerant control for a class of nonlinear systems based on a novel K-filters

Hou, Chuanjing; Hu, Li-Sheng

doi:10.1109/cac.2017.8243430

Cited by 1 publication

(1 citation statement)

References 14 publications

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“…A Fuzzy Logic Controller for Force System Stabilizer (FPSS) was made to overhaul the presentation of a Singular Machine Unfathomable Vehicle (SMIB) framework under solid state and dynamic states of the electrical power framework. For improving the presentation of this framework, two data sources FPSS was viewed as which needs to splash the headways under the framework.In [23] Authors built up a versatile issue open-minded controller, under view of a novel K-channels, to address the following manages issue of a class of nonlinear systems. Along the assistance of fuzzy logic systems, a novel K-channels was proposed to gauge the unmeasured system states.…”

Section: Literature Reviewmentioning

confidence: 99%

Distinct Architectures of Feed Forward Neural Network for Implementing A Human Swing Leg System

2023

IJCCCE

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The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Underthat paper, we think the fuzzy controller plan issue for yield following flawed genuine investigation of nonlinear systems. For examination, an essential fuzzy control plot has been bristly developed dependent on a current methodology delegate under the ﬁeld.In this paper, the Feedforward Neural Network has been implemented with integer, fixed point and floating point data representations. Additionally, The Fuzzy Logic Controllers in both analog and digital forms has been implemented in hardware. Both designs use less hardware resources and operate with reasonable speed compared to other existing designs. The digital implementation of Fuzzy Logic Controller has been tested for a simulated first order liquid level process and the performance results have been compared with those of the Matlab version of Fuzzy Logic Controller. Here, Fuzzy Logic Controller is used as the controller and is trained adaptively for the changes in process parameters using recursive k-means clustering algorithm for updating the centers of the hidden layer and Recursive Least Square algorithm for updating the weights of the output layer, the result of the settling time about 20ms and takes 20 iterations, and the squared error reaches zero at approximately 20 µs. Index Terms— Fuzzy Controller, leg interaction force, Prosthetic legs, Human walking, GyroAccelerate,Fuzzy Logic System.

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Section: Literature Reviewmentioning

confidence: 99%

Distinct Architectures of Feed Forward Neural Network for Implementing A Human Swing Leg System

2023

IJCCCE

View full text Add to dashboard Cite

show abstract

Adaptive fuzzy fault tolerant control for a class of nonlinear systems based on a novel K-filters

Cited by 1 publication

References 14 publications

Distinct Architectures of Feed Forward Neural Network for Implementing A Human Swing Leg System

Distinct Architectures of Feed Forward Neural Network for Implementing A Human Swing Leg System

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