Anti‐windup controller design for singularly perturbed systems subject to actuator saturation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166157/1/cth2bf00153.pd

Impact of the Aerobic Mesophilic Microorganisms on Black Sigatoka of Bananas According to the Cropping Systems in the Region of Kisangani (Case of the old secondary forest)

The microorganisms play crucial roles in the cycle of matter and damage the organic substances, sources of electrons, source of carbon, and source of energy for their biosynthesis. In this work, we studied the impact of the aerobic mesophiles microorganisms on the black sigatokaof banana in the old secondary forest. The objective was to count and to identify the microbial diversity of the forest ecosystems, as well as to study their impact on the development of the black sigatoka of banana. The assessment of the microbial populations has been done in an experimental field according to a device in blocks of Fischer by the method of successive dilutions of coloration of Gram and by the discharge of ascospores. The results showed that the rain season was lower in total microbial biomass (700, 7 colonies) than subdry season (840,3 colonies). The Bacillus genera have been more represented more than the Coccusgenera. The impact of black sigatoka of banana was raised at the cultivar LibangaLikale (40%) and low at Yangambi 5 Km (14%). The distribution of microorganisms in depth in the sub-dry season to the level of surface with vegetation was considerable either 3819, 3. 103 UFC( UNIT FORMAT COLONY) by gram of soil between 0 and 5 cm against 2754,5.103 UFC by gram of soil between 15 and 20 cm. This suggests that the raised number of microorganisms could have positive impact on soil fertility by decreasing the illnesses in this ecosystem

Stability bound analysis of singularly perturbed systems with time-delay

This paper considers the stability bound problem of singularly perturbed systems with time-delay. Some stability criteria are derived by constructing appropriate Lyapunov-Krasovskii functionals. The proposed criteria are less conservative than the existing ones. Two numerical examples are given to illustrate the advantages and effectiveness of the proposed methods

Numerical investigation of the scale effects of pump-jet propulsor with a pre-swirl stator

In this study, the performance of a pump-jet propulsor (PJP) with pre-swirl stator in open water is numerically investigated. Both full-scale and model-scale configurations are considered. The Reynolds-averaged Navier–Stokes equations and shear stress transport\ua0\u1d458−\u1d714 turbulence model are used in the numerical calculation. The computational domain is discretized using structured grids, and a rotating grid is affixed to the rotor to deal with the relative motion between the rotor and stationary components. The mesh quality is determined based on a grid uncertainty analysis. The numerical method is validated using model-scale experimental data. The simulation results reveal the influences of the scale size on the hydrodynamic performance and the distributions of the velocity, pressure and vorticity under three advance coefficients. With the increase in the advance coefficients, the scale influences on the efficiency become more obvious, and the efficiency of the full-scale PJP is always higher than that of the model-scale PJP. The full-scale configuration is found with a more significant instability in the gap vortex development, because it presents larger interaction between tip leakage vortex (TLV) and the inner wall of the duct. As the main velocity increases, the TLV shedding is delayed. Finally, the development process of gap vortices is analyzed for the difference operation conditions

Improving Robust Fairness via Balance Adversarial Training

Adversarial training (AT) methods are effective against adversarial attacks, yet they introduce severe disparity of accuracy and robustness between different classes, known as the robust fairness problem. Previously proposed Fair Robust Learning (FRL) adaptively reweights different classes to improve fairness. However, the performance of the better-performed classes decreases, leading to a strong performance drop. In this paper, we observed two unfair phenomena during adversarial training: different difficulties in generating adversarial examples from each class (source-class fairness) and disparate target class tendencies when generating adversarial examples (target-class fairness). From the observations, we propose Balance Adversarial Training (BAT) to address the robust fairness problem. Regarding source-class fairness, we adjust the attack strength and difficulties of each class to generate samples near the decision boundary for easier and fairer model learning; considering target-class fairness, by introducing a uniform distribution constraint, we encourage the adversarial example generation process for each class with a fair tendency. Extensive experiments conducted on multiple datasets (CIFAR-10, CIFAR-100, and ImageNette) demonstrate that our method can significantly outperform other baselines in mitigating the robust fairness problem (+5-10\% on the worst class accuracy

Feature extraction of vibration signal using OMP-NWE method

Feature extraction is one of the core problems in condition monitoring and fault diagnosis of mechanical equipment. In this study, an OMP-NWE method of feature extraction is proposed, aiming at the problem of low accuracy of existing feature extraction method. The OMP-NWE method integrates the strengths of orthogonal matching pursuit (OMP) algorithm with the benefits of nonparametric waveform estimation (NWE). Signal feature extraction model is constructed by design of filter bank and adaptive template signal. Then the vibration signal is linearly decomposed into a set of best matching waveform, which solves the problem that the basis function must be chosen in advance in OMP algorithm. The OMP-NWE method is applied to the feature extraction of the simulation and experimental vibration signal of rolling bearing, compared with the traditional OMP algorithm. Results show that the SNR of the extracted feature signal using OMP-NWE method increased by 19.22 % compared with that using the OMP method, which illustrates that OMP-NWE method has a higher accuracy in the feature extraction of unknown complex vibration signals. This work provides a new idea and a successful example for the feature extraction of vibration signal in the condition monitoring and fault diagnosis of mechanical equipment