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11.
Ting Cui Ling Xu Feng Ding Ahmed Alsaedi Tasawar Hayat 《International Journal of Adaptive Control and Signal Processing》2020,34(11):1658-1676
Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms. 相似文献
12.
Hot-dip galvanizing is a standard technology to produce coated steel strips. The primary objective of the galvanizing process is to establish a homogeneous zinc layer with a defined thickness. One condition to achieve this objective is a uniform transverse distance between the strip and the gas wiping dies, which blow off excessive liquid zinc. Therefore, a flat strip profile at the gas wiping dies is required. However, strips processed in such plants often exhibit residual curvatures which entail unknown flatness defects of the strip. Such flatness defects cause non-uniform air gaps and hence an inhomogeneous zinc coating thickness. Modern hot-dip galvanizing lines often use electromagnets to control the transverse strip profile near the gas wiping dies. Typically, the control algorithms ensure a flat strip profile at the electromagnets because the sensors for the transverse strip displacement are also located at this position and it is unfeasible to mount displacement sensors directly at the gas wiping dies. This brings along that in general a flatness defect remains at the gas wiping dies, which in turn entails a suboptimal coating.In this paper, a model-based method for a feedforward control of the strip profile at the position of the gas wiping dies is developed. This method is based on a plate model of the axially moving strip that takes into account the flatness defects in the strip. First, an estimator of the flatness defects is developed and validated for various test strips and settings of the plant. Using the validated mathematical model, a simulation study is performed to compare the state-of-the-art control approach (flat strip profile at the electromagnets) with the optimization-based feedforward controller (flat strip profile at the gas wiping dies) proposed in this paper. Moreover, the influence of the distance between the gas wiping dies and the electromagnets is investigated in detail. 相似文献
13.
Mahmoud Elsisi 《国际智能系统杂志》2020,35(11):1857-1878
The controller design for the robotic manipulator faces different challenges such as the system's nonlinearities and the uncertainties of the parameters. Furthermore, the tracking of different linear and nonlinear trajectories represents a vital role by the manipulator. This paper suggests an optimal design for the nonlinear model predictive control (NLMPC) based on a new improved intelligent technique and it is named modified multitracker optimization algorithm (MMTOA). The proposed modification of the MTOA is carried out based on opposition-based learning (OBL) and quasi OBL approaches. This modification improves the exploration behavior of the MTOA to prevent it from becoming trapped in a local optimum. The proposed method is applied on the robotic manipulator to track different linear and nonlinear trajectories. The NLMPC parameters are tuned by the MMTOA rather than the trial and error method of the designer. The proposed NLMPC based on MMTOA is compared with the original MTOA, genetic algorithm, and cuckoo search algorithm in literature. The superiority and effectiveness of the proposed controller are confirmed to track different linear and nonlinear trajectories. Furthermore, the robustness of the proposed method is emphasized against the uncertainties of the parameters. 相似文献
14.
Olatunde Adebayo Adeoti Sunday Olawale Koleoso 《Quality and Reliability Engineering International》2020,36(6):2170-2186
Several modifications and enhancements to control charts in increasing the performance of small and moderate process shifts have been introduced in the quality control charting techniques. In this paper, a new hybrid control chart for monitoring process location is proposed by combining two homogeneously weighted moving average (HWMA) control charts. The hybrid homogeneously weighted moving average (HHWMA) statistic is derived using two smoothing constants λ1 and λ2 . The average run length (ARL) and the standard deviation of the run length (SDRL) values of the HHWMA control chart are obtained and compared with some existing control charts for monitoring small and moderate shifts in the process location. The results of study show that the HHWMA control chart outperforms the existing control charts in many situations. The application of the HHWMA chart is demonstrated using a simulated data. 相似文献
15.
在干扰条件下,卫星导航抗干扰波束形成算法往往需要卫星信号波达方向(Direction-of-Arrival,DOA)的先验信息。但当存在低信噪比信号或主动干扰源时,常规的DOA估计算法性能急剧下降甚至失效。针对此问题,提出了一种被干扰信号压制的低信噪比“北斗”信号的DOA估计算法。该算法首先通过对接收信号进行子空间投影抑制干扰信号,然后对抑制干扰后的信号进行解扩重构处理,最后通过多重信号分类算法完成对“北斗”信号的DOA估计。仿真结果表明,在干扰信号干信比80 dB条件下,“北斗”信号DOA估计误差在5°以内,为下一步进行波束形成计算提供了高精度的入射角信息。 相似文献
16.
The recent trend of integration among new network services such as the long-term evolution (LTE) based on internet protocol (IP) needs reputable analyses and prediction information on the internet traffic. The IP along with increased internet traffics due to expanding new service platforms such as smartphones will reflect policies such as network QoS according to new services. The establishment of monitoring methods and analysis plans is thus required for the development of internet traffics that will analyze their status and predict their future. The paper with the speed of Internet traffic model is developed for monitoring the state of the experiment and verified. The problem is that the proposed service Internet service provider (ISP) to resolve the conflict between the occurrences can be considerably Internet traffic and that the state of data may be helpful in understanding. The paper advancement policy to reflect the network traffic volume of Internet services and users irradiation with increased traffic due to the development and management of the analysis was carried out experimental measurements. 相似文献
17.
18.
Susan Sabra Khalid Mahmood Malik Muhammad Afzal Vian Sabeeh Ahmad Charaf Eddine 《Expert Systems》2020,37(1):e12388
Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE. 相似文献
19.
Aishwarya
Srivastava Siddhant Aggarwal Amy Apon Edward Duffy Ken Kennedy Andre Luckow Brandon Posey Marcin Ziolkowski 《Software》2020,50(6):868-898
We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system. 相似文献
20.
Aditi Chatterjee Jayabrata Biswas Kiranmoy Das 《International Journal of Communication Systems》2020,33(9)
In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature. 相似文献