Parameter Adaptation for Wavelet Regularization in Parallel MRI

Author(s):  
Joseph Suresh Paul ◽  
Raji Susan Mathew
2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Jianyong Yao ◽  
Guichao Yang ◽  
Dawei Ma

The integration of internal leakage fault detection and tolerant control for single-rod hydraulic actuators is present in this paper. Fault detection is a potential technique to provide efficient condition monitoring and/or preventive maintenance, and fault tolerant control is a critical method to improve the safety and reliability of hydraulic servo systems. Based on quadratic Lyapunov functions, a performance-oriented fault detection method is proposed, which has a simple structure and is prone to implement in practice. The main feature is that, when a prescribed performance index is satisfied (even a slight fault has occurred), there is no fault alarmed; otherwise (i.e., a severe fault has occurred), the fault is detected and then a fault tolerant controller is activated. The proposed tolerant controller, which is based on the parameter adaptive methodology, is also prone to realize, and the learning mechanism is simple since only the internal leakage is considered in parameter adaptation and thus the persistent exciting (PE) condition is easily satisfied. After the activation of the fault tolerant controller, the control performance is gradually recovered. Simulation results on a hydraulic servo system with both abrupt and incipient internal leakage fault demonstrate the effectiveness of the proposed fault detection and tolerant control method.


2020 ◽  
Vol 102 (12) ◽  
Author(s):  
Mikhail V. Altaisky ◽  
Robin Raj

2021 ◽  
Vol 69 ◽  
pp. 101987
Author(s):  
Xinlin Zhang ◽  
Hengfa Lu ◽  
Di Guo ◽  
Lijun Bao ◽  
Feng Huang ◽  
...  

2021 ◽  
Vol 5 (2) ◽  
pp. 33
Author(s):  
Marylu L. Lagunes ◽  
Oscar Castillo ◽  
Fevrier Valdez ◽  
Jose Soria ◽  
Patricia Melin

Stochastic fractal search (SFS) is a novel method inspired by the process of stochastic growth in nature and the use of the fractal mathematical concept. Considering the chaotic stochastic diffusion property, an improved dynamic stochastic fractal search (DSFS) optimization algorithm is presented. The DSFS algorithm was tested with benchmark functions, such as the multimodal, hybrid, and composite functions, to evaluate the performance of the algorithm with dynamic parameter adaptation with type-1 and type-2 fuzzy inference models. The main contribution of the article is the utilization of fuzzy logic in the adaptation of the diffusion parameter in a dynamic fashion. This parameter is in charge of creating new fractal particles, and the diversity and iteration are the input information used in the fuzzy system to control the values of diffusion.


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