238 research outputs found
Multi-objective Optimization of Multi-loop Control Systems
Cascade Control systems are composed of inner and outer control loops. Compared to the traditional single feedback controls, the structure of cascade controls is more complex. As a result, the implementation of these control methods is costly because extra sensors are needed to measure the inner process states. On the other side, cascade control algorithms can significantly improve the controlled system performance if they are designed properly. For instance, cascade control strategies can act faster than single feedback methods to prevent undesired disturbances, which can drive the controlled system’s output away from its target value, from spreading through the process. As a result, cascade control techniques have received much attention recently. In this thesis, we present a multi-objective optimal design of linear cascade control systems using a multi-objective algorithm called the non-dominated sorting genetic algorithm (NSGA-II), which is one of the widely used algorithms in solving multi-objective optimization problems (MOPs). Two case studies have been considered. In the first case, a multi-objective optimal design of a cascade control system for an underactuated mechanical system consisting of a rotary servo motor, and a ball and beam is introduced. The setup parameters of the inner and outer control loops are tuned by the NSGA-II to achieve four objectives: 1) the closed-loop system should be robust against inevitable internal and outer disturbances, 2) the controlled system is insensitive to inescapable measurement noise affecting the feedback sensors, 3) the control signal driving the mechanical system is optimum, and 4) the dynamics of the inner closed-loop system has to be faster than that of the outer feedback system. By using the NSGAII algorithm, four design parameters and four conflicting objective functions are obtained. The second case study investigates a multi-objective optimal design of an aeroelastic cascade controller applied to an aircraft wing with a leading and trailing control surface. The dynamics of the actuators driving the control surfaces are considered in the design. Similarly, the NSGA-II is used to optimally adjust the parameters of the control algorithm. Ten design parameters and three conflicting objectives are considered in the design: the controlled system’s tracking error to an external gust load should be minimal, the actuators should be driven by minimum energy, and the dynamics of the closed-loop comprising the actuators and inner control algorithm should be faster than that of the aeroelastic structure and the outer control loop. Computer simulations show that the presented case studies may become the basis for multi-objective optimal design of multi-loop control systems
Nighttime Smartphone Reflective Flare Removal Using Optical Center Symmetry Prior
Reflective flare is a phenomenon that occurs when light reflects inside
lenses, causing bright spots or a "ghosting effect" in photos, which can impact
their quality. Eliminating reflective flare is highly desirable but
challenging. Many existing methods rely on manually designed features to detect
these bright spots, but they often fail to identify reflective flares created
by various types of light and may even mistakenly remove the light sources in
scenarios with multiple light sources. To address these challenges, we propose
an optical center symmetry prior, which suggests that the reflective flare and
light source are always symmetrical around the lens's optical center. This
prior helps to locate the reflective flare's proposal region more accurately
and can be applied to most smartphone cameras. Building on this prior, we
create the first reflective flare removal dataset called BracketFlare, which
contains diverse and realistic reflective flare patterns. We use continuous
bracketing to capture the reflective flare pattern in the underexposed image
and combine it with a normally exposed image to synthesize a pair of
flare-corrupted and flare-free images. With the dataset, neural networks can be
trained to remove the reflective flares effectively. Extensive experiments
demonstrate the effectiveness of our method on both synthetic and real-world
datasets.Comment: CVPR2023 (Highlight
Quantitative Determination of the Critical Points of Mott Metal-Insulator Transition in Strongly Correlated Systems
The Mottness is at the heart of the essential physics in a strongly
correlated system as many novel quantum phenomena occur at the metallic phase
near the Mott metal-insulator transition. We investigate the Mott
metal-insulator transition in a strongly-correlated electron system based on
the Hubbard model. The on-site moment evaluated by the dynamical mean-field
theory is employed to depict the Mott metal-insulator transition. Conveniently,
the on-site moment is a more proper order parameter to quantitatively determine
the Mott critical point, in comparison with the corresponding quasiparticle
coherent weight. Moreover, this order parameter also gives a consistent
description of two distinct forms of the critical points of the Mott
metal-insulator transition.Comment: 6 pages, 4 figure
Occlusion facial expression recognition based on feature fusion residual attention network
Recognizing occluded facial expressions in the wild poses a significant challenge. However, most previous approaches rely solely on either global or local feature-based methods, leading to the loss of relevant expression features. To address these issues, a feature fusion residual attention network (FFRA-Net) is proposed. FFRA-Net consists of a multi-scale module, a local attention module, and a feature fusion module. The multi-scale module divides the intermediate feature map into several sub-feature maps in an equal manner along the channel dimension. Then, a convolution operation is applied to each of these feature maps to obtain diverse global features. The local attention module divides the intermediate feature map into several sub-feature maps along the spatial dimension. Subsequently, a convolution operation is applied to each of these feature maps, resulting in the extraction of local key features through the attention mechanism. The feature fusion module plays a crucial role in integrating global and local expression features while also establishing residual links between inputs and outputs to compensate for the loss of fine-grained features. Last, two occlusion expression datasets (FM_RAF-DB and SG_RAF-DB) were constructed based on the RAF-DB dataset. Extensive experiments demonstrate that the proposed FFRA-Net achieves excellent results on four datasets: FM_RAF-DB, SG_RAF-DB, RAF-DB, and FERPLUS, with accuracies of 77.87%, 79.50%, 88.66%, and 88.97%, respectively. Thus, the approach presented in this paper demonstrates strong applicability in the context of occluded facial expression recognition (FER)
MIPI 2023 Challenge on RGBW Remosaic: Methods and Results
Developing and integrating advanced image sensors with novel algorithms in
camera systems are prevalent with the increasing demand for computational
photography and imaging on mobile platforms. However, the lack of high-quality
data for research and the rare opportunity for an in-depth exchange of views
from industry and academia constrain the development of mobile intelligent
photography and imaging (MIPI). With the success of the 1st MIPI Workshop@ECCV
2022, we introduce the second MIPI challenge, including four tracks focusing on
novel image sensors and imaging algorithms. This paper summarizes and reviews
the RGBW Joint Remosaic and Denoise track on MIPI 2023. In total, 81
participants were successfully registered, and 4 teams submitted results in the
final testing phase. The final results are evaluated using objective metrics,
including PSNR, SSIM, LPIPS, and KLD. A detailed description of the top three
models developed in this challenge is provided in this paper. More details of
this challenge and the link to the dataset can be found at
https://mipi-challenge.org/MIPI2023/.Comment: CVPR 2023 Mobile Intelligent Photography and Imaging (MIPI)
Workshop--RGBW Sensor Remosaic Challenge Report. Website:
https://mipi-challenge.org/MIPI2023/. arXiv admin note: substantial text
overlap with arXiv:2209.08471, arXiv:2209.07060, arXiv:2209.07530,
arXiv:2304.1008
The cosmic ray test of MRPCs for the BESIII ETOF upgrade
In order to improve the particle identification capability of the Beijing
Spectrometer III (BESIII),t is proposed to upgrade the current endcap
time-of-flight (ETOF) detector with multi-gap resistive plate chamber (MRPC)
technology. Aiming at extending ETOF overall time resolution better than 100ps,
the whole system including MRPC detectors, new-designed Front End Electronics
(FEE), CLOCK module, fast control boards and time to digital modules (TDIG),
was built up and operated online 3 months under the cosmic ray. The main
purposes of cosmic ray test are checking the detectors' construction quality,
testing the joint operation of all instruments and guaranteeing the performance
of the system. The results imply MRPC time resolution better than 100,
efficiency is about 98 and the noise rate of strip is lower than
1() at normal threshold range, the details are discussed and
analyzed specifically in this paper. The test indicates that the whole ETOF
system would work well and satisfy the requirements of upgrade
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