Control System In Order Research Articles

Modelling And Research on Water Level Control of Great Lakes Based on Neural Network PID Algorithm

The Great Lakes are situated in the border region between the United States and Canada, which has a significant impact on the climate and the lives of those living in the surrounding areas. The objective of this paper is to establish a network of the Great Lakes through Pearson's correlation coefficient analysis and to construct a two-tank water level model based on a PID control system in order to effectively manage the dynamics of the Great Lakes. Firstly, the strength and direction of the linear relationship between two variables is quantified through Pearson's correlation coefficient analysis, which involves the collection of observational data and the calculation of mean values. This analysis serves as a fundamental basis for predictive modelling and hypothesis testing. Secondly, based on the flow balance principle, mathematical expressions are constructed to simulate the water flow, and a PID control system is constructed to achieve optimal water level maintenance. By analysing the Pearson's correlation coefficient, the interrelationships among the variables in the Great Lakes network can be understood, thereby providing guidance for scientific research and decision-making. The results demonstrate that the constructed two-tank water level model combined with the PID control system and SHAP algotithm can effectively manage the water level of the Great Lakes and achieve optimal water level regulation.

On Damping a Control System of Arbitrary Order with Global Aftereffect on a Tree

On Damping a Control System of Arbitrary Order with Global Aftereffect on a Tree

Research on a Real-Time Control System for Discrete Factories Based on Digital Twin Technology

Gear factories are most typical discrete manufacturing factories. Many gear factories are striving to explore how to achieve intelligent manufacturing in order to improve efficiency and reduce costs. Digital twin technology is currently one of the most reliable ways to achieve intelligent manufacturing. This article aims to establish a real-time control system in order to promote intelligent manufacturing for discrete manufacturing factories. Firstly, a model for a digital twin gear factory is put forward based on the characteristics of gear factories, and the composition of a real-time control system for gear factories is clarified. Then, a human–computer interaction architecture for the real-time control system is proposed. The real-time control system consists of three parts as follows: a monitoring module, a virtualizing module, and a controlling module. At work, it appears as a kind of human–machine interaction form with the three following interfaces: a monitoring window, a virtualizing window, and a controlling window. Finally, a gear factory, which is specialized in manufacturing the intermediate shaft dual gear of a new energy vehicle gearbox, develops a set of software for the real-time control system. The prototype software is obtained through some development activities such as 3D MAX and WebGL virtualization modeling and OPC UA and REST communication design.

The use of the Criterion automated assessment system in teaching students of language specialties to write essays in a foreign language: the results of an experimental test

Importance. Modern artificial intelligence (AI) tools are able to take on some of a foreign language teacher’s functions, thereby optimizing the learning process. One of these is the teacher’s function of checking and evaluating students’ written papers (essays). There are works in the scientific literature describing step-by-step methods of teaching students to write essays in a foreign language, including individual extracurricular practice of students with an AI tool during the completion of the essay’s draft version. Based on receiving evaluative feedback from the AI tool, students can refine their essays in linguistic, structural and substantive aspects. The Criterion automated assessment system for written papers is one of the modern AI tools that can be used in teaching. However, checking the effectiveness of this system is not the subject of a separate study. The purpose of the study is to clarify the stages of teaching students of language specialties to write essays in a foreign language using evaluative feedback from the Criterion automated assessment system and to test the effectiveness of this technique during experimental training.Materials and Methods. The study participants are 2nd year students of the specialty 45.05.01 “Translation and Translation Studies” of the Lipetsk State Technical University (control group = 25 and experimental group = 25). The students of the control group studied according to the traditional essay teaching methodology, excluding the use of AI tools, and the experimental group participants studied according to an innovative methodology, including individual extracurricular practice of students with the Criterion system in order to receive evaluative feedback for the completion of the essay. The following aspects of control are: a) the lexical side of written speech; b) the grammatical side of written speech; c) the organizational structure of the work; d) the content of the work.Results and Discussion. It is proved that the innovative method of teaching students to write essays, based on the integration of the Criterion automated essay assessment system into the learning process, is more effective than the traditional method in mastering students a) the organizational structure of the essay (t = 2.82 at p = 0.004) and b) the content side of creative work (t = 3.05 at p = 0.002). However, statistical analysis of the results do not confirm the advantage of the innovative technique in the formation of lexical (t = 1.44 at p = 0.08) and grammatical (t = 1.36 at p = 0.09) speech skills of students of a language university.Conclusion. The novelty of the research consists in developing the stages of teaching students to write an essay based on practice with the Criterion automated control system in order to receive evaluative feedback for the completion of the essay. The results obtained can be used in the methodology of teaching secondary school students and university students in teaching writing.

Research on the Autonomous Control Technology Used in the Slurry Mixing System of Cementing Units

Cementing is a critical link in oil and gas exploitation, in which slurry density control is particularly important. In this study, we examined a slurry mixing control system in order to solve the problem of time delays in the mixing system. The model of a slurry mixing system was built in accordance with the system’s structure. A Smith fuzzy PID (proportion integration differentiation) composite control solution is proposed herein, and the simulation results show that the adjustment time and overshoot are lower than those of the conventional PID control and Smith predictive compensation control. A genetic algorithm is utilized to optimize the quantization factor and scale factor of the Smith fuzzy PID controller. Following optimization, the rise time of the controller was found to be 0.45 s, which represents a decrease of 35.9%, the overshoot was reduced by 0.4%, and the stabilization time was reduced by 36.6%. Afterward, we built a cementing slurry mixing simulation experimental platform, and experiments were used to verify the feasibility and superiority of the Smith fuzzy PID controller optimized by the genetic algorithm in comparison with the conventional controllers. The study results thus provide a scientific basis for the engineering application of the autonomous control technology of the slurry mixing system in cementing units.

Comments on “Global leader-following consensus in finite time for fractional-order multi-agent systems with discontinuous inherent dynamics subject to nonlinear growth”

Despite the proposed results on the non-existing of finite time stable equilibria for fractional order systems (Shen and Lam, 2014), the commented paper (Wang et al., 2020) has shown finite time convergence of fractional order control systems via a couple of theorems. This comment demonstrates that the proofs of the given theorems in Wang et al. (2020) are incorrect.

Application of Fuzzy logic and IoT in a small-scale Smart Greenhouse System

This research aims to address the critical challenges caused by global population increase, climate change, and urbanization on food production by means of a Fuzzy Logic controller in a small-scale greenhouse and improving agricultural efficiency and sustainability.The growing global population has stressed the significance of implementing efficient food production techniques. Furthermore, the impact of climate change and extreme weather events complicates the production process. The goal of this study is to combine an innovative small greenhouse design with a fuzzy logic-based control system in order to develop an IoT-enabled self-regulating environment for autonomous plant growing.Continuous advances in technology have been focusing on automating greenhouses to provide self-regulating microclimates and optimal developmental conditions. Current trends focus on automating greenhouses to provide self-regulating microclimates. Looking ahead, the strategy entails combining automated approaches with precisely planned structures via IoT.This study's key findings include the successful integration of a fuzzy logic control system with greenhouse infrastructure, allowing for real-time monitoring and adjustment of environmental parameters, as well as the development of a pilot IoT ecosystem demonstrating the feasibility of self-regulating microclimates for improved plant growth.

Visualizing the Maximum Energy Zone of Wind Turbines Operating at Time-Varying Wind Speeds

Wind turbines are one of the leading renewable sources of electricity. They are located in areas where the energy potential of the wind is high and more or less permanent. Their efficient operation depends on certain technical characteristics of the entire wind system (wind turbines, generator, automation system, regulation, and control). This paper analyses experimental data from wind turbines, WT, in the Dobrogea area: wind speed, v, velocity, n, and power, PEG, at the electric generator, EG. These are used to identify the local maxima of wind turbine power at different wind speeds. Based on this, a mathematical model for wind turbines and the power losses caused by inefficient control are determined. The mathematical model is used to visualize the maximum energy zones. At the end of this study, an algorithm is given that allows for the visualization of the optimal energy zone. The algorithm resulting from the analyzed case studies can be implemented by the control system in order to maximize the produced electricity with any variation in wind speed.

Model-Based Analysis of the Accuracy of Tracking Control and Energy Efficiency of a Six-Wheeled Skid-Steered Robot

This article concerns the modeling and motion control of a mobile robot with six independently driven and non-steered wheels. The main research issue is analyzing the influence of the structure of the control system and wheel track on the control accuracy and energy efficiency during robot motion on horizontal paved ground. For this purpose, the kinematic relationships for the robot are discussed and a simplified dynamics model for control applications is developed. The robot’s dynamics model takes into account the most important phenomena of the wheel interaction with the paved ground, including slip. In addition, it is supplemented with a model of the robot’s drive units. Two versions of the control system were adopted for analysis, i.e., with the wheels’ controller only and additionally equipped with a pose controller. Simulation studies were carried out for the developed robot dynamics model and the analyzed versions of the control system in order to investigate the influence of the track width of the wheels and the structure of the control system on motion accuracy and energy efficiency. In order to quantitatively compare the results for the analyzed solutions, quality indices were introduced. The results of the simulation research indicate the influence of the track width of the wheels on the accuracy of motion when using the wheels’ controller, as well as its impact on energy efficiency. Moreover, they show that it is possible to significantly improve the accuracy of motion by using an additional pose controller, which allows limiting the impact of the non-optimal geometric parameters of the robot and the slip of the wheels on trajectory tracking errors. However, the addition of the pose controller does not significantly affect the energy efficiency during the robot’s motion, which may be even worse in this case.

Discrete Impulsive Signal Observer for Fractional-Order Control Systems and Its Consumer Electronic Circuit Application

In the process of actual electronic equipment signal transmission, interference is inevitable. How to accurately estimate the device status to ensure valid signal travelling is very meaningful. This paper mainly investigates a new transmission signal estimation strategy for fractional order control systems with unknown inputs. Compared with integer order modeling, fractional order modeling can better describe and report the essential process of system signal transmission. By using the fractional order output derivative-based method and convex optimization technique, an effective discrete-time impulsive observer design algorithm is proposed to stabilize the error dynamic systems. Especially, the resulting criterion reflects well the relationship between the fractional order and the pulse signal, and then is applied on a fractional order electronic circuit. It implies that the given conclusions are of significance in signal estimation.

Assessing The Effect of Creative Accounting on Corporate Performance: a Case of Selected Listed Commercial Banks on the Ghana Stock Exchange

The study examined the effect of creative accounting on the performance of commercial banks listed on the Ghana Stock Exchange. The research design chosen for this study is an ex-post facto research design, which involves examining facts that have already occurred without any interference. The research approach adopted is quantitative, focusing on objective measurements and statistical analysis of data collected through surveys. The study relies on secondary data, specifically financial reports of deposit money banks listed on the Ghana Stock Exchange. The target population includes all the listed commercial banks on the exchange. The sample size consists of 8 out of the 9 commercial banks selected based on their up-to-date financial reports. The data analysis was done with the aid of SPSS software, employing descriptive and inferential statistical techniques such as multiple regression was used to determine the cause and effect relationship among variables. The study found that there was a strong positive link among a bank's size, creative accounting and sales growth and its return on assets and return on equity. Also, SIZE and SG positively affect the profitability (ROA and ROE) of the listed firms on the GSE. However, Creative Accounting negatively affects profitability (ROA and ROE). Therefore, ccommercial banks should be critical regarding on issues or items that they classified under creative accounting. Also, commercial banks should develop strategies to lure many shareholders to invest in the banks in order to improve upon their performance. Moreover, there is urgent need for monitoring companies’ activities in order to raise the quality of financial reporting in Ghana. This can be achieved in determining which accounting manipulation is kept within the limits of legality. Lastly, commercial banks should strengthen their internal control systems in order to deal with issues of creative accounting and misleading financial reports.

Collision Risk in Autonomous Vehicles: Classification, Challenges, and Open Research Areas

When car following is controlled by human drivers (i.e., by their behavior), the traffic system does not meet stability conditions. In order to ensure the safety and reliability of self-driving vehicles, an additional hazard warning system should be incorporated into the adaptive control system in order to prevent any possible unavoidable collisions. The time to contact is a reasonable indicator of potential collisions. This research examines systems and solutions developed in this field to determine collision times and uses various alarms in self-driving cars that prevent collisions with obstacles. In the proposed analysis, we have tried to classify the various techniques and methods, including image processing, machine learning, deep learning, sensors, and so on, based on the solutions we have investigated. Challenges, future research directions, and open problems in this important field are also highlighted in the paper.

An integrative control theory perspective on consciousness.

An integrative account of consciousness should have a number of properties. It should build upon a framework of nonconscious behavior in order to explain how and why consciousness contributes to, and addresses the limitations of, nonconscious processes. It should also encompass the primary (phenomenal), secondary (access), and tertiary (self-awareness) aspects of consciousness. A number of accounts have proposed a role for consciousness in the prediction of sensory input, yet these proposals do not address how organisms deal with multiple, unpredictable, disturbances to maintain control. According to perceptual control theory (PCT), purposiveness is the control of hierarchically organized perceptual variables via changes in output that counteract disturbances which would otherwise increase error between the current value and the reference value (goal state) of each perceptual variable. In PCT, reorganization is the process required for the adaptive modification of control systems in order to reduce the error in intrinsic systems that control essential, largely physiological, variables. The current article proposes that primary consciousness emerges from this system, and is sustained as secondary consciousness through a number of processes including the control of the integration rate of novel information via exploratory behavior, attention, imagination, and altering the mutation rate of reorganization. Tertiary consciousness arises when internally sustained perceptual information is associated with specific symbols that form a parallel, propositional system for the use of language, logic, and other symbolic systems. The hypotheses and initial research designs to test this account are provided. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Toward Effective Aircraft Call Sign Detection Using Fuzzy String-Matching between ASR and ADS-B Data

Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-end Recurrent Neural Network (RNN) toolkits were developed with higher speed and accuracy that can often achieve a Word Error Rate (WER) below 10%. These toolkits can nowadays be deployed, for instance, within aircraft cockpits and Air Traffic Control (ATC) systems in order to identify aircraft and display recognized voice messages related to flight data, especially for airports not equipped with radar. Hence, the performance of air traffic controllers and pilots can ultimately be improved by reducing workload and stress and enforcing safety standards. Our experiment conducted at Tangier’s International Airport ATC aimed to build an ASR model that is able to recognize aircraft call signs in a fast and accurate way. The acoustic and linguistic models were trained on the Ibn Battouta Speech Corpus (IBSC), resulting in an unprecedented speech dataset with approved transcription that includes real weather aerodrome observation data and flight information with a call sign captured by an ADS-B receiver. All of these data were synchronized with voice recordings in a structured format. We calculated the WER to evaluate the model’s accuracy and compared different methods of dataset training for model building and adaptation. Despite the high interference in the VHF radio communication channel and fast-speaking conditions that increased the WER level to 20%, our standalone and low-cost ASR system with a trained RNN model, supported by the Deep Speech toolkit, was able to achieve call sign detection rate scores up to 96% in air traffic controller messages and 90% in pilot messages while displaying related flight information from ADS-B data using the Fuzzy string-matching algorithm.

New results on dynamic output state feedback stabilization of some class of time-varying nonlinear Caputo derivative systems

In modern control theory applications, input–output feedback often arises and plays a crucial role in stabilizing any target control systems. However, in many practical applications, the knowledge of full information on the state of systems may not be available in general due to measurements. In order to control such types of systems, this paper uses a universal concept of real order calculus to stabilize by the method of dynamic output feedback control. Is it possible to design a dynamic output feedback stabilization for time-varying real order control systems? This work develops a new dynamic output feedback control method and proposes linear homogeneous time-varying control law to stabilize incommensurate nonlinear time-varying real order systems under the action of Caputo derivative with an addendum of ultimate random initial-time. We utilize the ideas of the comparison method and establish order-dependent asymptotic results associated with uniform Lipschitz continuous functions that provide stabilization by means of the dynamic output state feedback control method. We provide three examples that include a practical system and show the importance of some theoretical results in the demonstration to stabilize the problems by means of proposed control method.

A Novel Influence Function M-Estimator-Based for Active Noise Control

M-estimators are widely used in active noise control (ANC) systems in order to update the adaptive FIR filter taps. ANC systems reduce the noise level by generating anti-noise signals. Up to now, the evaluation of M-estimators capabilities has shown that there exists a need for further improvements in this area. In this paper, a new improved M-estimator is proposed. The sensitivity of the proposed algorithm to the variations of its constant parameter is checked in feedforward control. The effectiveness of the algorithm in both types is proved by comparing it with previous studies. Simulation results show the steady performance and fast initial convergence of the proposed algorithm.

Distributed deep learning approach for intrusion detection system in industrial control systems based on big data technique and transfer learning

ABSTRACT Industry 4.0 refers to a new generation of connected and intelligent factories that is driven by the emergence of new technologies such as artificial intelligence, Cloud computing, Big Data and industrial control systems (ICS) in order to automate all phases of industrial operations. The presence of connected systems in industrial environments poses a considerable security challenge, moreover with the huge amount of data generated daily, there are complex attacks that occur in seconds and target production lines and their integrity. But, until now, factories do not have all the necessary tools to protect themselves, they mainly use traditional protection. In order to improve industrial control systems in terms of efficiency and response time, the present paper propose a new distributed intrusion detection approach using artificial intelligence methods, Big Data techniques and deployed in a cloud environment. A variety of Machine Learning and Deep Learning algorithms, basically convolutional neural networks (CNN), have been tested to compare performance and choose the most suitable model for the classification. We test the performance of our model by using the industrial dataset SWat.

Prerequisites for developing a technological preparation database of small- and medium-scale machine-building industries

The article deals with the analysis of currently popular databases and their control systems in order to select the most suitable for implementing the goals of the grant project funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No AP14972804). The authors considered the main modules of the automation system for small-scale production. Most of attention was paid to the module of evaluating technological routes; the basic concept of algorithms was described and the requirements for the database architecture were presented. The analysis of various data formats was also made for the convenience of their use in the software product and storage in the database. In the future, based on the analysis carried out, implementation of the system for evaluating technological routes will be carried out, namely, the calculation of the time and the cost, both for each method and for the project as a whole, for further optimization of production.

Motion Strategy of Drilling Anchor Manipulator Based on Intelligent Optimization Algorithm

The drilling and anchoring robot is an important equipment to realize the intellectualization of fully mechanized coal mining. The control effect of its manipulator directly affects the safety and efficiency of the support operation of the drilling and anchoring robot. The control of drilling anchor manipulator usually adopts PID controller, but due to the limitation of integer order PID control algorithm and traditional empirical parameter adjustment, it is difficult to find a group of parameters with the best control effect in a short time, resulting in the failure of timely and accurate positioning of the end of the manipulator. In this paper, the combination of numerical modeling and simulation analysis is used to adjust the parameters of fractional order PIλDμ controller by using search algorithm (GPS) and applied to the motion control of manipulator; Based on the independent joint control theory, the single input single output system model of hydraulic cylinder at the joint of manipulator is established by using Matlab-Simulink software and fractional PIλDμ control technology. The fractional order control system is regulated by input shaping feedforward control technology(IS). The step response effect of the hydraulic system is further analyzed by setting input feedforward controllers with different gain ratios. The numerical simulation results show that the control strategy of “Input Shaping(IS) + Intelligent optimization algorithm (GPS) parameter adjustment + Fractional PIλDμ control technology” can effectively improve the spatial accurate positioning of mining manipulator. The research expand the application of intelligent control technology in the field of mining equipment.

From Incineration to Sterilisation of Solid Hospital Waste in Low-income Contexts: a Gradual Sustainable Transition.

Open burning and incineration are the two most common treatments for hospital solid waste in low-income countries. Due to the absence of limits on emissions and the lack of technical capacity or funding, obsolete incinerators do not guarantee neither a low environmental and economic impact nor people health. The SIRSU Project, co-financed by the Italian Agency for Sustainable Development and Newster Group, aims to substitute the incinerator in Beira Central Hospital (Mozambique) with an electric sterilizer, an environmentally friendly machine that is also safe for workers. However, it is not sufficient to import this new technology and train the staff. First, an assessment of the quantities and types of biomedical waste produced in the different hospitals is necessary, as well as a careful analysis of the waste management system of all hospitals in the city. If the technology is suitable for the context, then, after the training of technicians for maintenance and operation, a period of accompaniment and monitoring is necessary to optimise performances. The transition cannot be immediate, and a period of coexistence of the two plants (steriliser and incinerator) is necessary. To facilitate the gradual transition, the SIRSU project foresees the foundation of a local start-up to manage the steriliser and offer a waste full transport service for smaller hospitals to the Central Hospital where the machine is installed. This experience could be an opportunity to set guidelines comprehensive of the concepts of safety and security during all the steps of the transition. This aspect can be an important element for defining 1) the most appropriate technical solutions, evaluating the implementations on the control and regulation systems in order to minimize the risks associated with the process, 2) management and above all operational methods in order to guarantee not only compliance with the most precautionary technical legislations, but also modern and advanced operating standards.