Application of DCS for Level Control in Nonlinear System using Optimization and Robust Algorithms

Aparna,

doi:10.14201/adcaij2020912950

ADCAIJ

2020

DOI: 10.14201/adcaij2020912950

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Application of DCS for Level Control in Nonlinear System using Optimization and Robust Algorithms

Aparna Aparna

Abstract: This proposed work deals with the real-time implementation of a PI level controller for a nonlinear interacting multi-input multi-output (MIMO) system using YOKOGAWA CENTUM CS 3000 DCS. Some intricate algorithms were chosen to tune the PI controller, presuming the effect of disturbances in a nonlinear interacting MIMO system. Three algorithms; a classical evolution algorithm, genetic algorithm (GA); a metaheuristic optimization algorithm, particle swarm optimization algorithm (PSO); and a robust algorithm, qua… Show more

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Cited by 2 publications

References 31 publications

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The Use of ZigBee Wireless Communication Technology in Industrial Automation Control

Ding¹,

Jian-li

Yue

2021

Wireless Communications and Mobile Computing

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With the accelerating process of world industrialization, countries pay more attention to industrial modernization. In order to solve the problems of traditional control technology and system with low accuracy, high energy consumption, and high delay in industrial automation control and the difficulty in adapting to the new industrial production process, the new industrial automation control system is discussed and studied. The industrial automation control is studied, and a new monitoring system is designed for automation control by using ZigBee wireless communication technology. The design of the system data communication scheme is completed by the in-depth study and summary of ZigBee wireless communication technology. The hardware structure and software structure of ZigBee wireless communication module are designed, and the wireless monitoring system using ZigBee is established. Taking the production workshop of a pharmaceutical factory as the monitoring object, the working stability and data transmission efficiency of the model are tested. The experiment shows that the ZigBee wireless transmission model has lower temperature and better stability than the wired transmission system in the working process. Compared with the traditional wired control system, the temperature of ZigBee wireless control system is lower when it works. The difference between the highest temperature and the lowest temperature is 0.1°C. In the overall work flow, the system temperature is lower than that of the wired control. ZigBee wireless control has good stability. Subsequently, the method of manually setting obstacles is used to test the effectiveness of data transmission. The experiment found that in the absence of barrier, the maximum effective transmission distance was 40 meters, and the packet loss rate was very low, which could ensure the timeliness of data. Therefore, this system can be applied to industrial automation control. The research results can provide some reference for the design of new control systems in other industrial control fields. The improved system can also be applied to other industries. ZigBee is a short-range technology for wireless sensor networks, and it is a two-way communication technology with low power consumption, low data rate, and low cost. It can be applied to automatic control and remote control. This provides a platform for wireless networking and control of small and cheap devices. ZigBee will not compete with connection technologies such as Wi-Fi. Meanwhile, it will greatly stimulate the progress of the industrial market.

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The Use of ZigBee Wireless Communication Technology in Industrial Automation Control

Ding¹,

Jian-li

Yue

2021

Wireless Communications and Mobile Computing

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Application of nonlinear clustering optimization algorithm in web data mining of cloud computing

Zhang

2023

Nonlinear Engineering

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To improve data mining and data clustering performance to improve the efficiency of the cloud computing platform, the author proposes a bionic optimized clustering data extraction algorithm based on cloud computing platform. According to the Gaussian distribution function graph, the degree of aggregation of the categories and the distribution of data points of the same category can be judged more intuitively. The cloud computing platform has the characteristics of large amount of data and high dimension. In the process of solving the distance between all sample points and the center point, after each center point update, the optimization function needs to be re-executed, the author mainly uses clustering evaluation methods such as PBM-index and DB-index. The simulation data object is the Iris dataset in UCI, and N = 500 samples are selected for simulation. The experiment result shows that when P is not greater than 15, the PBM value changes very little, and when P = 20, the PBM performance of all the four clustering algorithms decreased significantly. When the sample size is increased from 50,000 to 100,000, the DB performance of this algorithm does not change much, and the DB value tends to be stable. In terms of clustering operation time, the K-means algorithm has obvious advantages, the DBSCAN algorithm is the most time-consuming, and the operation time of wolf pack clustering and Mean-shift is in the middle. In the actual application process, the number of samples for each training can be dynamically adjusted according to the actual needs, in order to improve the applicability of the wolf pack clustering algorithm in specific application scenarios. Flattening in cloud computing for data clusters, this algorithm is compared with the common clustering algorithm in PBM. DB also shows better performance.

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Application of DCS for Level Control in Nonlinear System using Optimization and Robust Algorithms

Cited by 2 publications

References 31 publications

The Use of ZigBee Wireless Communication Technology in Industrial Automation Control

The Use of ZigBee Wireless Communication Technology in Industrial Automation Control

Application of nonlinear clustering optimization algorithm in web data mining of cloud computing

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