Visualization in Java, the performance of control system, based on fuzzy inference system, with a front-end built in Visual Basic

2002 ◽  
Author(s):  
D. Kaur ◽  
K. Shah
Keyword(s):  
Control System ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Visual Basic ◽  
Inference System ◽  
Front End

scholarly journals Design an intelligent hybrid position/force control for above knee prosthesis based on adaptive neuro-fuzzy inference system

2021 ◽  
Vol 23 (2) ◽  
pp. 675
Author(s):  
Mithaq N. Raheema ◽  
Dhirgaam A. Kadhim ◽  
Jabbar S. Hussein
Keyword(s):  
Control System ◽  
Knee Joint ◽  
Force Control ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Knee Prosthesis ◽  
Current Control ◽  
Inference System ◽  
Control Approach ◽  
Neuro Fuzzy

<div>This paper reviews the position/force control approach for governs an efficient knee joint in an active lower limb prosthesis, and the inter facing current control algorithm with human gate parameter is inserted. Two techniques are used to collect gait cycle data of leg: first, the foot ground force is obtained by the force platform device based on its position (x, y), then data of knee joint angles is recorded by using a video-camera device.The collected information is sent and used in the proposed intelligent controller. This intelligent control system used an adaptive neuro-fuzzy inference system (ANFIS) circuit in addition to the proportional integral derivative (PID) controller. This hybrid ANFIS-PID control system simulates and provides the ground force values. The experimental results show anexcellent response and lower root mean square error (RMSE) compared with each of PID and ANFIS controller that implemented for a similar purpose. In summary, the results showed acceptably stable performance of the proposedposition/force controller based on hybrid ANFIS-PID system. It can be concluded that the finest performance of the controlled force, as quantified by the RMSE criteria, is perceived by the proposed hybrid scheme depending on the controller intelligent decision circuit.</div>

An Wavelet Based Handoff Algorithm for Cognitive Wireless Network

2012 ◽  
Vol 433-440 ◽  
pp. 5087-5091
Author(s):  
Meng Jia Li ◽  
Jing Yao Wang ◽  
Mei Song ◽  
Xiao Jun Wang ◽  
Ning Ning Liu
Keyword(s):  
Control System ◽  
Wavelet Analysis ◽  
Fuzzy Control ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Second Use

This paper proposed a novel handoff algorithm for cognitive network based on wavelet analysis and fuzzy control system. It makes the system cognitive and adaptive to the changes of the environment by two steps: first, make wavelet analysis to the received signal to get the basic signal which is without noise. Second, use adaptive neuro-fuzzy inference system (ANFIS) to make diligent handoff decision. The simulation shows that it improves the performance of the whole system when the channel is in low signal-to-noise ratio.

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