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Process-Model-Free Design of MPC via a Reference-Model-Based PI controller for the Gas Turbine 9

Process-Model-Free Design of MPC via a Reference-Model-Based...

引用

9th International Conference on Electrical engineering, control and Robotics, EECR 2023

作者： Shi, Gengjin Dai, Chengbo Ma, Miaomiao Li, Donghai Ding, Yanjun Tsinghua University State Key Lab of Power Systems Dept. of Energy & Power Engineering Beijing China North China Electric Power University School of Control & Computer Engineering Beijing China

ISBN: (纸本)9781665491204

Model predictive control (MPC) is a modern advanced control strategy which has great reputation because of its excellent reference tracking performance and the ability to deal with process constraints, time delay and multivariable problems. However, the gas turbine is difficult to model accurately and unmeasurable disturbances are unavoidable, which limits the application of MPC to the gas turbine. To solve these problems, a process-model-free design method for MPC via a reference-model (RM)-based proportional-integral (PI) controller-desired dynamic equational (DDE)-PI controller (MPC-DDE) is proposed in this paper. The DDE-PI provides the design model for the MPC and handle with unmeasurable disturbances while MPC provides a rolling optimized set point for DDE-PI. Simulation results illustrate the superiorities of the proposed hierarchical control strategy in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of practical application of MPC-DDE to the gas turbine. © 2023 IEEE.

关键词： Model predictive control

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Intelligent Operational Decision Support System for Sugar Factory Resource Efficiency 5

Intelligent Operational Decision Support System for Sugar Fa...

引用

5th IEEE International Conference on Modern Electrical and Energy System, MEES 2023

作者： Lutska, Nataliia Zaiets, Nataliia Vlasenko, Lidiia Junge, Stefan National University of Food Technologies Dept. of Automation and Computer Technologies of Control Systems Kyiv Ukraine National University of Life and Environmental Sciences of Ukraine Dept. of Automation and Robotic Systems Kyiv Ukraine State University of Trade and Economics Dept. of Software Engineering and Cyber Security Kyiv Ukraine Berlin University of Applied Sciences Dept. of Packaging Technology Berlin Germany

ISBN: (纸本)9798350359787

With the economic crisis that is looming over the world due to changes in the energy sector and a reduction in the supply of certain types of products, energy and resource efficiency issues are becoming more relevant for the food industry. Also important is the preservation of the environment and the implementation of Cleaner Production trends. Most enterprises follow the concept of Industry 4.0 and increase efficiency through the implementation of intelligent methods, in particular machine learning. The paper proposes a neural network model of sugar production. The model makes it possible to predict the main estimates of resource efficiency used to correct the technological modes of production by the operator-technologist. The structure of the operational decision support system has been developed and is used by personnel to model and predict changes in resource efficiency estimates and KPIs calculated on their basis. Its feature is the integration of methods for achieving resource efficiency, improving environmental performance and ensuring KPIs. To do this, at the initial stage, an analysis of the main flows that affect resource efficiency and an assessment of their importance was carried out. Ensuring Production Performance is confirmed by the simulation and the adequacy of the created neural network accuracy of more than 95%. © 2023 IEEE.

关键词： Decision support systems

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Maneuvering control of Autonomous Underwater Vehicle (AUV) by Simulated Annealing and Moth Flame Optimization Tuned controllers

Maneuvering Control of Autonomous Underwater Vehicle (AUV) b...

引用

2022 International Conference on Electronic systems and Intelligent Computing, ICESIC 2022

作者： Valluru, Sudarshan K. Thareia, Hitesh Center for Control of Dynamical Systems and Computation Dept. of Electrical Engineering Delhi Technological University Delhi110042 India

ISBN: (纸本)9781665483858

This paper emphasizes maneuvering control of Autonomous Underwater Vehicle (AUV) with the help of Linear-Proportional Integral Derivative (L-PID) and Fractional Order PID (FOPID) controllers. The values of the gain parameters of L-PID (Kp, Ki, Kd) and FOPID (Kp, Ki, Kd,λ, μ) are tuned by Simulated Annealing (SA) and Moth Flame optimization (MFO) techniques. The performance of both the controllers is compared and the better algorithm to tune the parameters of the controllers is determined. A step function is applied to the system's input to test the AUV, and the corresponding response to the input function is examined. The transient parameters of the AUV, such as rise time, settling time, overshoot, and performance index IT AE were calculated and compared. The investigatory results show that both the algorithms used to tune the FO PID controller accurately steer the AUV. Also, the MFO tuned FOPID controller is more efficient than the SA tuned FOPID controller. © 2022 IEEE.

关键词： Simulated annealing

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Multi-Aspect Optimal Sliding Mode controller for a Mecanum Wheeled Robot 11

Multi-Aspect Optimal Sliding Mode Controller for a Mecanum W...

引用

11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Allahyari, Sohrab Rahmanei, Hamid Moosavian, S. Ali A. K. N. Toosi University of Technology Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems Laboratory Dept. of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

Four-wheel drive Mecanum robots have gained attention due to their ability to move in all directions, which allows them to work in tight and complex environments. For this reason, ensuring precise control of these robots along predefined trajectories is crucial. This work presents a comparative study on the effects of parametric uncertainties, external disturbances, measurement noises, and initial deviations on the trajectory-Tracking performance of a 4-wheel drive Mecanum robot. First, the kinematic and kinetic models of the Mecanum robot are introduced. Then, the integral sliding mode control is designed, and proof of stability is provided. In addition, we explore other control strategies, including PID, feedback linearization, sliding mode, and adaptive sliding mode control, that are designed for this robot. Furthermore, the particle swarm optimization algorithm is hired for the controllers with a cost function as the total sum of average error, maximum error, and final error. Optimization has been done on all controllers to compare the results fairly. To appraise the effectiveness of the proposed control optimization methods, simulations are carried out in MATLAB/Simulink. The results reveal that the proposed ISMC method performs best in both defined scenarios compared to other controllers. However, it must be noted that the ISMC controller exhibits limitations when facing significant uncertainties in the dynamic model. This study underscores the effectiveness of our proposed control method and provides valuable insights into the practical implementation controller for the Mecanum robot in real-world applications. © 2023 IEEE.

关键词： Three term control systems

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Local Polynomial Models for Real-Time Tracking of Humidity Sensor Signals 3

Local Polynomial Models for Real-Time Tracking of Humidity S...

引用

3rd International Conference on Communications, Information, Electronic and Energy systems, CIEES 2022

作者： Nikovski, Plamen Titova, Tanya Mihov, Vasil University of Food Technologies Dept. of Electronics And Electrical Engineering Plovdiv Bulgaria University of Food Technologies Dept. of Automation Information And Control Systems Plovdiv Bulgaria

ISBN: (数字)9781665491495

ISBN: (纸本)9781665491495

Sensor signal tracking has great practical importance for solving a number of problems such as data fusion and sensor integration in multi-sensor systems (MSS), robotics, fault detection (FD), and diagnosis, etc. The Kalman filter is a widely used algorithm that can be applied in these cases if an appropriate model of the signal is available. The present study shows that under a step change in humidity, the filter can estimate the signal from a humidity sensor by means of a second-order local polynomial model. This gives a reason to expect similar behavior not only for sudden but also for all other changes. The proposed online signal tracking solution is simple to implement and can be used not only for humidity sensors, but also for sensors that measure quantities such as temperature, pressure, level, etc. © 2022 IEEE.

关键词： Polynomials

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Proposal for a Job Management Tool for Deep Learning in a Mixed Environment of Heterogeneous GPUs

Proposal for a Job Management Tool for Deep Learning in a Mi...

引用

Consumer Technology (ICCT-Pacific), International Conference on

作者： Nobuyuki Ishii Aoi Kondo Hiroaki Koga Dept. Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

In recent years, the use of GPUs for computation has become commonplace in deep learning. It is not uncommon for deep learning labs to procure GPU servers for computation without standardising specifications such as GPU architecture and VRAM capacity, resulting in a heterogeneous GPU server environment. Container technology is also widely used as a method of isolating software execution environments. Among them, Docker is the de facto standard for container platforms. In this paper, we have developed a management system that can allocate deep learning training jobs to GPU servers (workers) using container technology to absorb differences in execution environments in heterogeneous GPU server environments. In experiments, we confirmed that the proposed system can estimate the completion time of training for each worker and can detect Out-Of-Memory (OOM) of GPUs in advance. We were able to confirm in advance the “inference time” and the “possibility of OOM”, which are difficult to predict when performing deep learning. We have succeeded in obtaining the “predicted value of learning time” and “possibility of OOM” that engineers need to know in advance, and have shown that the proposed system is effective in deep learning tests.

关键词： Deep learning Training Graphics processing units Containers Software Servers Resource management Proposals Standards Testing

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Verification of the Effect of Label Modification on Neural Network Learning

Verification of the Effect of Label Modification on Neural N...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Tsubasa Oka Hiroaki Koga Dept. Control and Information Systems Engineering National Institute of Technology Kurume College Fukuoka Japan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

This study focuses on the problem of subjective labeling that arises in the application of machine learning with neural networks to the medical field. The first problem is that of subjectivity, which arises because the labeling of medical data relies on expert knowledge and the process can be subjective. The second problem is the reduced information content of labels caused by discrete and quantitative labeling. If the intermediate values between the discrete values also have evaluative meaning, the detailed information is lost due to the discrete numerical labeling. We focus on such instability in labels and propose an approach to label modification using values inferred during neural network training. Specifically, we consider labels that are discrete, quantitative numbers as continuous numbers, compare the inferred value with the label value at each step in the learning phase, and compare the label value with the inferred value at each step in the learning phase. The update method is to give the label a sign-responsive variation. The goal is to modify each label using the value inferred by the inference made during learning in this way. As an experiment, we conducted an experiment on label modification under pseudo-conditions to verify its effectiveness. The results showed that when the amount of label modification was controlled by a constant, the generalization performance and the nature of label modification differed depending on the constant. In particular, generalization performance was improved when the constant of the label modification amount was determined so that the label value was separated from the inferred value at each step.

关键词： Training Neural networks Machine learning Labeling

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NIS Test for Selecting the Order of Local Polynomial Model 3

NIS Test for Selecting the Order of Local Polynomial Model

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3rd International Conference on Communications, Information, Electronic and Energy systems, CIEES 2022

ISBN: (数字)9781665491495

ISBN: (纸本)9781665491495

This work presents an approach that uses normalized innovations squared (NIS) test to determine the order of a local polynomial trend model of a humidity sensor signal. Compared to the classical Akaike information criterion which balances model fit and model complexity NIS test allows to determine the lowest order of the model at which a consistent Bayesian estimation is possible. This approach is useful when signal processing algorithms, such as those for data fusion in multi-sensor systems, contain a Kalman filter, because a successful NIS test is a prerequisite for normal filter operation. The results of the study show that the response of the SHT31-DIS sensor under a step change in humidity is adequately described by a second-order local polynomial model, and this implies a consistent estimation for other input variations. © 2022 IEEE.

关键词： Polynomials

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Augmented Reality Used in Technical Diagnostics and Maintenance

Augmented Reality Used in Technical Diagnostics and Maintena...

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ELEKTRO

作者： Aleš Janota Peter Holečko Dept. of Control and Information Systems Faculty of Electrical Engineering and IT UNIZA Žilina Slovak Republic

ISBN: (数字)9798350372359

ISBN: (纸本)9798350372366

Integrating digital data and human sensory input in real-world settings offers new possibilities in device diagnostics and maintenance. In this study, we utilized the EcoStruxure Augmented Operator Advisor to develop an augmented reality application for a family house heating system. Our application was designed without access to the real heating system; instead, we simulated its operation with a programmable logic controller. Our final application includes three primary scenes: the heat pump, its indoor unit, and the engine room. Drawing on our practical experience, we discuss the benefits of our approach and the software tools used and summarize our subjective opinions.

关键词： Heating systems Three-dimensional displays Image recognition Heat pumps Two-dimensional displays Time measurement Maintenance

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Detection of Consumer Electrical Load Profile Anomalies

Detection of Consumer Electrical Load Profile Anomalies

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Eurocon

作者： Michael Farrugia Kenneth Scerri Andrew Sammut Dept. of Systems and Control Engineering University of Malta Msida Malta Dept. of Electronic Systems Engineering University of Malta Msida Malta

Faulty meters, billing inaccuracies and fraudulent activity all contribute to the non-technical losses experienced by power utilities. Apart from the intended advantage of billing efficiency, the advent of smart meters for consumption and load profile logging, has made possible the analysis of subscriber data for load balancing and consumer classification, amongst other uses. This study analyses data from smart meters in Malta and develops a method for anomaly detection aiming to identify costumers contributing to non-technical losses. Consumers are grouped into clusters with similar weekly consumption patterns using hierarchical clustering. For each consumer, two novel coefficients are then computed: the Anomaly Coefficient, which measures the divergence in consumption patterns for a consumer from all other member of the same cluster, and the Cluster Change Coefficient, which quantifies the likelihood of a customer to exhibit patterns associated with other clusters. Together these two measures are joined in a single Anomaly Score, thus identifying consumers with highly irregular consumption patterns.

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