scholarly journals Robust Estimation of the Unbalance of Rotor Systems Based on Sparsity Control of the Residual Model

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Tingpeng Zang ◽  
Guangrui Wen ◽  
Zhifen Zhang
Keyword(s):  
Optimization Problem ◽  
Signal Reconstruction ◽  
External Disturbance ◽  
Reconstruction Algorithm ◽  
Working Environment ◽  
External Disturbances ◽  
Convex Optimization Problem ◽  
Rotor Systems ◽  
Vibration Data ◽  
The Impact

The vibration signals of rotating machinery are frequently disturbed by background noise and external disturbances because of the equipment’s particular working environment. Thus, robustness has become one of the most important problems in identifying the unbalance of rotor systems. Based on the observation that external disturbance of the unbalance response often displays sparsity compared with measured vibration data, we present a new robust method for identifying the unbalance of rotor systems based on model residual sparsity control. The residual model is composed of two parts: one part takes regular measurements of noise, while the other part evaluates the impact of external disturbances. With the help of the sparsity of external disturbances, the unbalance identification is converted into a convex optimization problem and solved by a sparse signal reconstruction algorithm. Experiment results have shown that the proposed method is robust and effective in identifying the unbalance of rotor systems in a complex environment, improving the precision of unbalance estimation and simplifying the balancing process.

scholarly journals Control of an IPMC Soft Actuator Using Adaptive Full-Order Recursive Terminal Sliding Mode

Actuators ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 33
Author(s):  
Romina Zarrabi Ekbatani ◽  
Ke Shao ◽  
Jasim Khawwaf ◽  
Hai Wang ◽  
Jinchuan Zheng ◽  
...  
Keyword(s):  
Sliding Mode ◽  
External Disturbance ◽  
Tracking Error ◽  
Working Environment ◽  
Parametric Uncertainties ◽  
Metal Composite ◽  
External Disturbances ◽  
Terminal Sliding Mode ◽  
Positioning Accuracy ◽  
Soft Actuator

The ionic polymer metal composite (IPMC) actuator is a kind of soft actuator that can work for underwater applications. However, IPMC actuator control suffers from high nonlinearity due to the existence of inherent creep and hysteresis phenomena. Furthermore, for underwater applications, they are highly exposed to parametric uncertainties and external disturbances due to the inherent characteristics and working environment. Those factors significantly affect the positioning accuracy and reliability of IPMC actuators. Hence, feedback control techniques are vital in the control of IPMC actuators for suppressing the system uncertainty and external disturbance. In this paper, for the first time an adaptive full-order recursive terminal sliding-mode (AFORTSM) controller is proposed for the IPMC actuator to enhance the positioning accuracy and robustness against parametric uncertainties and external disturbances. The proposed controller incorporates an adaptive algorithm with terminal sliding mode method to release the need for any prerequisite bound of the disturbance. In addition, stability analysis proves that it can guarantee the tracking error to converge to zero in finite time in the presence of uncertainty and disturbance. Experiments are carried out on the IPMC actuator to verify the practical effectiveness of the AFORTSM controller in comparison with a conventional nonsingular terminal sliding mode (NTSM) controller in terms of smaller tracking error and faster disturbance rejection.

scholarly journals When Probabilistic Shaping Realizes Improper Signaling for Hardware Distortion Mitigation

2020 ◽  
Author(s):  
Sidrah Javed ◽  
Ahmed Elzanaty ◽  
Osama Amin ◽  
Basem Shihada ◽  
Mohamed-Slim Alouini
Keyword(s):  
Monte Carlo ◽  
Communication Systems ◽  
Error Probability ◽  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Rate Performance ◽  
Convex Optimization Problem ◽  
Maximum A Posterior ◽  
The Impact ◽  
Successive Convex Programming

<pre><pre>Hardware distortions (HWD) render drastic effects on the performance of communication systems. They are recently proven to bear asymmetric signatures; and hence can be efficiently mitigated using improper Gaussian signaling (IGS), thanks to its additional design degrees of freedom. Discrete asymmetric signaling (AS) can practically realize the IGS by shaping the signals' geometry or probability. In this paper, we adopt the probabilistic shaping (PS) instead of uniform symbols to mitigate the impact of HWD and derive the optimal maximum a posterior detector. Then, we design the symbols' probabilities to minimize the error rate performance while accommodating the improper nature of HWD. Although the design problem is a non-convex optimization problem, we simplified it using successive convex programming and propose an iterative algorithm. We further present a hybrid shaping (HS) design to gain the combined benefits of both PS and geometric shaping (GS). Finally, extensive numerical results and Monte-Carlo simulations highlight the superiority of the proposed PS over conventional uniform constellation and GS. Both PS and HS achieve substantial improvements over the traditional uniform constellation and GS with up to one order magnitude in error probability and throughput. </pre></pre>

scholarly journals When Probabilistic Shaping Realizes Improper Signaling for Hardware Distortion Mitigation

2020 ◽  
Author(s):  
Sidrah Javed ◽  
Ahmed Elzanaty ◽  
Osama Amin ◽  
Basem Shihada ◽  
Mohamed-Slim Alouini
Keyword(s):  
Monte Carlo ◽  
Communication Systems ◽  
Error Probability ◽  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Rate Performance ◽  
Convex Optimization Problem ◽  
Maximum A Posterior ◽  
The Impact ◽  
Successive Convex Programming

<pre><pre>Hardware distortions (HWD) render drastic effects on the performance of communication systems. They are recently proven to bear asymmetric signatures; and hence can be efficiently mitigated using improper Gaussian signaling (IGS), thanks to its additional design degrees of freedom. Discrete asymmetric signaling (AS) can practically realize the IGS by shaping the signals' geometry or probability. In this paper, we adopt the probabilistic shaping (PS) instead of uniform symbols to mitigate the impact of HWD and derive the optimal maximum a posterior detector. Then, we design the symbols' probabilities to minimize the error rate performance while accommodating the improper nature of HWD. Although the design problem is a non-convex optimization problem, we simplified it using successive convex programming and propose an iterative algorithm. We further present a hybrid shaping (HS) design to gain the combined benefits of both PS and geometric shaping (GS). Finally, extensive numerical results and Monte-Carlo simulations highlight the superiority of the proposed PS over conventional uniform constellation and GS. Both PS and HS achieve substantial improvements over the traditional uniform constellation and GS with up to one order magnitude in error probability and throughput. </pre></pre>

scholarly journals Noise suppression in stochastic genetic circuits using PID controllers

2021 ◽  
Vol 17 (7) ◽  
pp. e1009249
Author(s):  
Saurabh Modi ◽  
Supravat Dey ◽  
Abhyudai Singh
Keyword(s):  
Noise Suppression ◽  
External Disturbance ◽  
Open Loop ◽  
Loop System ◽  
Pid Controllers ◽  
Noise Sources ◽  
External Disturbances ◽  
Stochastic Expression ◽  
Integral Feedback ◽  
The Impact

Inside individual cells, protein population counts are subject to molecular noise due to low copy numbers and the inherent probabilistic nature of biochemical processes. We investigate the effectiveness of proportional, integral and derivative (PID) based feedback controllers to suppress protein count fluctuations originating from two noise sources: bursty expression of the protein, and external disturbance in protein synthesis. Designs of biochemical reactions that function as PID controllers are discussed, with particular focus on individual controllers separately, and the corresponding closed-loop system is analyzed for stochastic controller realizations. Our results show that proportional controllers are effective in buffering protein copy number fluctuations from both noise sources, but this noise suppression comes at the cost of reduced static sensitivity of the output to the input signal. In contrast, integral feedback has no effect on the protein noise level from stochastic expression, but significantly minimizes the impact of external disturbances, particularly when the disturbance comes at low frequencies. Counter-intuitively, integral feedback is found to amplify external disturbances at intermediate frequencies. Next, we discuss the design of a coupled feedforward-feedback biochemical circuit that approximately functions as a derivate controller. Analysis using both analytical methods and Monte Carlo simulations reveals that this derivative controller effectively buffers output fluctuations from bursty stochastic expression, while maintaining the static input-output sensitivity of the open-loop system. In summary, this study provides a systematic stochastic analysis of biochemical controllers, and paves the way for their synthetic design and implementation to minimize deleterious fluctuations in gene product levels.

scholarly journals Sparse Signal Reconstruction Based on Multiparameter Approximation Function with Smoothedl0Norm

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xiao-Feng Fang ◽  
Jiang-She Zhang ◽  
Ying-Qi Li
Keyword(s):  
Optimization Problem ◽  
Null Space ◽  
Signal Reconstruction ◽  
Iteration Process ◽  
Reconstruction Algorithm ◽  
Measurement Matrix ◽  
Hyperbolic Tangent ◽  
Reconstruction Quality ◽  
And Performance ◽  
Quasi Newton

The smoothedl0norm algorithm is a reconstruction algorithm in compressive sensing based on approximate smoothedl0norm. It introduces a sequence of smoothed functions to approximate thel0norm and approaches the solution using the specific iteration process with the steepest method. In order to choose an appropriate sequence of smoothed function and solve the optimization problem effectively, we employ approximate hyperbolic tangent multiparameter function as the approximation to the big “steep nature” inl0norm. Simultaneously, we propose an algorithm based on minimizing a reweighted approximatel0norm in the null space of the measurement matrix. The unconstrained optimization involved is performed by using a modified quasi-Newton algorithm. The numerical simulation results show that the proposed algorithms yield improved signal reconstruction quality and performance.

Antecedents And Outcomes Of Qwl Among Employees In Banks

2019 ◽  
Vol 118 (7) ◽  
pp. 1-19
Author(s):  
Geethanjali N ◽  
Parveen Roja M ◽  
Lavanya D
Keyword(s):  
Organizational Climate ◽  
Job Stress ◽  
Work Life ◽  
Working Environment ◽  
Quality Of Work Life ◽  
Quality Of Work ◽  
Significant Difference ◽  
Service Productivity ◽  
The Impact

Quality of work life is the major factor to be considered in working environment of any organization. The performance of employees and the organization lies on the ability of the employees based on working environment. The QWL leads to better working environment which improves the performance of organization. The present study has made an attempt to find the level of factors causing QWL and the impact of outcome of QWL in banks. Since the profile of the banks may be associated with the level of outcomes of QWL, the present study has made an attempt to examine it with the help of one way analysis of variance and t-test. The included outcomes of QWL are job satisfaction, job stress, organizational climate, organizational commitment, employees retention behaviour, service quality employees and service productivity of employees. The highly associated determinants of QWL and the significant difference among the PUSBs and PRSBs have been noticed. The significantly associating important profiles of the banks regarding the existence of outcome of QWL are identified.

Assessment of the impact of factors of the working environment on the health of workers in oil refining based on the analysis of morbidity

2020 ◽  
pp. 600-600 ◽  
Author(s):  
I. V. Ginko ◽  
T. M. Sushinskaya ◽  
A. L. Rybina
Keyword(s):  
Comparison Group ◽  
Main Group ◽  
Working Environment ◽  
Oil Refinery ◽  
Oil Refining ◽  
Production Environment ◽  
The Impact

Studies have been conducted to assess the impact of factors of the production environment on employees of the oil refinery ofJSC «Naftan». Significant differences with the comparison group on the indicators of SVT were revealed. Priority nosological forms of employees of the main group are identified.

New areas of research in occupational medicine

2020 ◽  
pp. 811-811
Author(s):  
E. E. Shigan
Keyword(s):  
Occupational Medicine ◽  
Working Environment ◽  
Medium Businesses ◽  
The Impact

The study of the preservation of worker's health in recent years is gaining more and more new areas of research, among which like to point out the problems of harmonization of age and work, the impact of unemployment on health and aspects of the impact of the working environment of small and medium businesses on health.

Image Reconstruction with the Fourier Coefficients for Magnetic Induction Tomography

2020 ◽  
Vol 16 (2) ◽  
pp. 156-163
Author(s):  
Jingwen Wang ◽  
Xu Wang ◽  
Dan Yang ◽  
Kaiyang Wang
Keyword(s):  
Inverse Problem ◽  
Image Reconstruction ◽  
Magnetic Induction ◽  
Fourier Coefficients ◽  
Signal Reconstruction ◽  
Reconstruction Algorithm ◽  
Reconstruction Method ◽  
Measurement Equation ◽  
Image Reconstruction Method ◽  
Magnetic Induction Tomography

Background: Image reconstruction of magnetic induction tomography (MIT) is a typical ill-posed inverse problem, which means that the measurements are always far from enough. Thus, MIT image reconstruction results using conventional algorithms such as linear back projection and Landweber often suffer from limitations such as low resolution and blurred edges. Methods: In this paper, based on the recent finite rate of innovation (FRI) framework, a novel image reconstruction method with MIT system is presented. Results: This is achieved through modeling and sampling the MIT signals in FRI framework, resulting in a few new measurements, namely, fourier coefficients. Because each new measurement contains all the pixel position and conductivity information of the dense phase medium, the illposed inverse problem can be improved, by rebuilding the MIT measurement equation with the measurement voltage and the new measurements. Finally, a sparsity-based signal reconstruction algorithm is presented to reconstruct the original MIT image signal, by solving this new measurement equation. Conclusion: Experiments show that the proposed method has better indicators such as image error and correlation coefficient. Therefore, it is a kind of MIT image reconstruction method with high accuracy.

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