A Hybrid Intelligent Optimal Control System Design for Wastewater Treatment Process

Qiao, Junfei; Han, Guoqiang; Han, Honggui; Yang, Cuili

doi:10.5755/j01.itc.46.3.16061

Cited by 3 publications

(5 citation statements)

References 27 publications

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“…Performance comparisons DNN-GSO (Pandey et al 2021) Improved precision, accuracy, and F1-score ANN-PSO (Moayedi et al 2019) Improved R2 and lower RMSE PID-DDAOC (Qiao et al 2017) Energy consumption decreased by 13.6% DMSC-FBL (Mahmoodabadi et al 2018) Improved robustness and effectiveness CSA-PID (Alkrwy et al 2021) Improved the steady-state error, step response stability, overshoot, rising time, and settling time HDLNNC (El-Nagar et al 2022) Fast learning, stable controller, reduced system uncertainties Fuzzy-PID (Carvalho et al 2021) Reduced overshoots and undershoots PSO-LMS-PI (Tamer et al 2021) Higher efficiency, improved power factor It differs in a certain way from the aforementioned studies by using simultaneous weight vector updates to assign new PID gains. The performance metrics of the proposed method are found superior to the origin algorithms.…”

Section: Hybridized Methodsmentioning

confidence: 99%

“…The integration of more than one algorithm has also demonstrated promising results in many adaptive Black Sea Journal of Engineering and Science control problems, and further research is required in this direction. Different types and combinations of hybrid algorithms have been developed in many papers (Qiao et al, 2017;Mahmoodabadi et al, 2018;Moayedi et al, 2019;Pandey et al, 2021;Carvalho et al, 2021;Tamer et al, 2021;Alkrwy et al, 2021, El-Nagar et al, 2022 to find gains of different controller types to enhance the system transient response as well as to ensure the robustness and stability of the system. Text detection and character recognition are successfully achieved by weighted naïve Bayes classifier and deep neural network (DNN)-based adaptive galactic swarm optimization (GSO) (Pandey et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…A hybrid neuro particle-based optimization (PSO) of the artificial neural network (ANN) is investigated for slope stability calculation (Moayedi et al, 2019). A control optimization system based on hybrid intelligent technology is proposed to obtain the minimum energy consumption in the wastewater treatment process (Qiao et al, 2017). Compared to the traditional PID and data-driven adaptive optimal controller (DDAOC) methods, the simulation results of the proposed method show better performance.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Algorithm for Adaptive Neuro-controllers

Demirtaş

2023

Black Sea Journal of Engineering and Science

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In this study, a novel hybrid algorithm consisting of the least mean square and backpropagation neural network is proposed to auto-adjust adaptive proportional integral derivative (PID) controller gains for improving the transient response of linear systems. The hybrid approach comprises the scheme of the two algorithms running in parallel and updates PID gains simultaneously. All algorithms are implemented on the same linear system and present a general framework for different scenarios such as initial PID gains, learning rates, and target functions. The results show that the presented hybrid algorithm has better accuracy, precision, F1-score, adaptability, and robustness than origin algorithms, and significantly improves the controllability in most of the system scenarios. It also exhibits better performance in periodic incremental and decremental targets compared to origin algorithms. Different hybridization levels are also simulated and are highlighted as significant features of their performance. This work can be expanded to the combination of the other well-known algorithms, paving the way to significant improvements in control system applications.

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Section: Hybridized Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Hybrid Algorithm for Adaptive Neuro-controllers

Demirtaş

2023

Black Sea Journal of Engineering and Science

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“…Besides the theoretical achievements, some works have been performed to design the feedback control solutions based on PID [44,117,4] or PI [107] controllers to demonstrate that this strategy can guarantee the stability of the flows whereas the manual choking occurred insufficiently. The production (subsea) choke is used to control the offshore flow and stabilize the flow line pressure.…”

Section: Flow Controlmentioning

confidence: 99%

Computer methods for non-invasive measurement and control of two-phase flows: a review study

Wajman

2019

ITC

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Nowadays, the application of advanced technologies in modern production systems is the main trend of development and technological progress in many industrial sectors. It is due to the still growing trends of energy-saving and production quality enhancement. Wherever in the production process the phase mixture is transported and it is not optimal or not economic, there is a need to develop a system which would be able to prevent any construction disaster, unexpected production line stopping or situation where for reasons of bad flow parameters, the final product is defective. This paper studies various sensors, measurement techniques and computer methods for signal processing and analysis to diagnose and control two-phase flows. Due to the possibility that the invasive measurement disturbs the process and changes it parameters and behavior especially in the location just after the measurement point and simultaneously does not provide any information about these changes it is unreliable for the diagnosis or control. Therefore, the non-invasive techniques commonly used for measurement of flows parameters are described. Depending on the industrial demands many of applications examples for non-invasive two-phase flows measurement and monitoring are given. This description for identifying the flow parameters is divided into features categories of this phenomena as void fraction distribution, velocity profile and flow regime. However, from these methods the high accuracy and short processing time is expected. The continued observation and monitoring of the process abnormalities can provide valuable information about its dynamic state and allow for real-time and automatic monitoring and control. Therefore, the development of advanced process control is one of the most important challenges to keep the flow regime on the given level and for instant and long-term energy saving, quality improvement.

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“…As a result, translation is also one of human wisdom activities that have existed since ancient times and is an indispensable means of information exchange in the modern society. High-quality translation services are undoubtedly of great significance for China's social development, especially economic development [3].…”

Section: Introductionmentioning

confidence: 99%

Networked Artificial Intelligence English Translation System Based on an Intelligent Knowledge Base and Translation Method Thereof

Ren

2021

Mobile Information Systems

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Language translation is often conducted in work and study. Traditional language translation is based on lexical structure analysis. However, natural language is not so standardized, which causes this translation method to have fundamental defects, no matter how much the algorithm is improved. The translation results and human translation will be very different. This paper mainly studies the networked artificial intelligence. The English translation system and translation methods are based on a smart knowledge base. Bringing an example of English-Chinese translation to suggest translations according to the intelligent knowledge base explains in detail the principle of intelligent knowledge-based translation and the advantage of this translation method compared with the traditional translation method based on lexical structure analysis. In the experiment of this paper, when the variance is 2/N, 30/N, 100/N, and 2N, it is the experimental data for an in-depth study. When the variance is 2/N, 30/N, and 100/N, the result is the same as that when the variance is 0.5; the result when the variance is 2N also conforms to the trend in the tables, which is close to the effect of the smoothing algorithm, which verifies the effectiveness of the system in this paper.

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A Hybrid Intelligent Optimal Control System Design for Wastewater Treatment Process

Cited by 3 publications

References 27 publications

A Hybrid Algorithm for Adaptive Neuro-controllers

A Hybrid Algorithm for Adaptive Neuro-controllers

Computer methods for non-invasive measurement and control of two-phase flows: a review study

Networked Artificial Intelligence English Translation System Based on an Intelligent Knowledge Base and Translation Method Thereof

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