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Context-Aware control for Quality Improvement in Liquid Steel Manufacturing

Context-Aware Control for Quality Improvement in Liquid Stee...

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control Technology and Applications (CCTA),

作者： Isabela R. Birs Cristina I. Muresan Mircea Susca Vlad Mihai Mihaly Mihaela Ghita Maria Ghita Robin De Keyser Clara Ionescu Research Group of Dynamical Systems and Control Faculty of Engineering and Architecture Ghent University EEDT Decision & Control Flanders Make Consortium Ghent Belgium Department of Automation Technical University of Cluj Napoca Cluj-Napoca Romania

This paper presents an original theoretical and implementation framework of fractional order event-based control with the purpose of quality improvement at the end production line of a continuous casting process. A real-life steel manufacturing plant is taken into consideration in the study. A prior fractional order model is considered to tune a fractional order Proportional Integral controller that ensures an ideal flow velocity of liquid steel. A novel event-based fractional order methodology is proposed that uses internal and external process events in order to improve quality . The implementation strategy takes into consideration available software and hardware components at the plant site, offering a realistic and implementable solution, highly suitable for the current steel industry setting. Numeric simulations successfully validate the proposed methodology.

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Development and modeling of some elements of the twowheeled mobile robot system 8

Development and modeling of some elements of the twowheeled ...

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8th International Young Scientists Conference on Information Technologies, Telecommunications and control systems, ITTCS 2021

作者： Karpov, Alexander O Karpov, Alexey O Vasilyeva, M Yu Belashova, E.S. Process Dynamics and Control Department Kazan National Research Technical University named after A.N. Tupolev - KAI Kazan Russia Federal University Kazan Russia Department of Automation and Process Control Systems Kazan National Research Technological University Kazan Russia Department of Computer Systems Kazan National Research Technical University named after A.N. Tupolev - KAI Kazan Russia

The article deals with the navigation system elements development process. The movement and positioning of a two-wheeled mobile robot with a high level of accuracy are realized through this system. Also, the algorithms mechanisms based on the construction of the optimal path for the autonomous device movement and based on a map building in an unknown area and avoiding obstacles are described. Using mathematical models, computer modeling of the device executive system is carried out using the engineering program MatLab. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Navigation systems

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Fuzzy PID control for suppressing stick-slip vibration of drill-string system

Fuzzy PID control for suppressing stick-slip vibration of dr...

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2022 Chinese automation Congress, CAC 2022

作者： Hu, Shuaikang Lu, Chengda Wu, Min He, Zhaoqing Song, Haitao Li, Wangnian School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Xi’an Research Institute Co. Ltd. China Coal Technology and Engineering Group Xi’an710077 China

ISBN: (纸本)9781665465335

In this paper, a fuzzy PID (Proportional Integral Derivative) controller is introduced to suppress the stick-slip vibration present in the drilling process. First, the dynamical model of stick-slip vibration is composed of the multi-DOF (Degree-Of-Freedom) drill-string model and the Karnopp model describing the interaction of the drill bit with the rock. Then, stability analysis is made for the initial PID parameters of our controller. To suppress the stick-slip vibration and at the same time mitigate the effects of the stratigraphic environment variation on the control performance, the fuzzy adaptive algorithm is chosen as the method of optimization controller parameters. From the experimental results, it is clear that our controller has good control performance in the complex and changing stratigraphic environment. © 2022 IEEE.

关键词： controllers

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Model predictive control of hemodynamics during intravenous general anesthesia

Model predictive control of hemodynamics during intravenous ...

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International Conference on System Theory, control, and Computing (ICSTCC)

作者： Hamed Farbakhsh Erhan Yumuk Ghada Ben Othman Robin De Keyser Dana Copot Isabela Birs Clara M. Ionescu Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Science Park 125 Ghent University Zwijnaarde Belgium Department of Control and Automation Engineering Istanbul Technical University Istanbul Turkey Department of Automation Technical University of Cluj-Napoca Memorandumului no. 28 Cluj-Napoca Romania

In the operating rooms and the intensive care unit, it is crucial to manage the patient’s hemodynamic status, which includes factors like cardiac output and mean arterial pressure. Anesthesiologists confront a difficult task while monitoring high-risk patients. Cardiac output optimization has been found to enhance the result of high-risk patients in terms of hospital stay, mortality rate, post-operative problems, etc. The application of standard control approaches is restricted because the mean arterial pressure response of a patient using vasoactive medicines is modeled by a first-order dynamical system with time-varying parameters and a time-varying delay in the control input. In order to circumvent implementation challenges, this work develops an approximation technique that describes the system using a higher-order model. Predictive control is therefore used to comprehend the practical application of higher-order hemodynamic systems. The effectiveness of this strategy is demonstrated by the simulations and outcomes that are given.

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Risk Monitoring and Mitigation for Automated Vehicles: A Model Predictive control Perspective

Risk Monitoring and Mitigation for Automated Vehicles: A Mod...

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Automated Vehicle Validation Conference (IAVVC), IEEE International

作者： Kailin Tong Fengwei Guo Selim Solmaz Martin Steinberger Martin Horn (Dept.-E) Virtual Vehicle Research GmbH Graz Control Systems Group Austria Vehicle Safety Institute Graz University of Technology Graz Austria Institute of Automation and Control Graz University of Technology Graz Austria

Despite recent advances in algorithms and technology, self-driving vehicles are still susceptible to errors that can have severe consequences. As a result, effective risk monitoring and mitigation measures for autonomous driving systems are in high demand. To overcome this issue, several specifications and standards have been developed. However, a theoretical framework for dealing with autonomous vehicle hazards has rarely been presented. This study suggests a risk modeling method inspired by ideas from control theory and introduces a Model Predictive control (MPC) Framework to deal with risks in general. Two application examples are presented. The first example shows how MPC parameters may affect the aggressiveness of the response. In the second example, our proposed risk monitoring and mitigation module is integrated into a vision-based Adaptive Cruise control (ACC) system. Simulation results indicate a significant improvement in collision avoidance rate (from 0% to 47% in edge scenarios) during the Euro NCAP ACC Car-to-Car tests with a stationary target, which demonstrates the utility of our approach for addressing various types of hazards faced by autonomous vehicles.

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A Compartmental Modelling Framework for Drug Distribution in Lean and Obese Patients in Long-Term General Anesthesia*

A Compartmental Modelling Framework for Drug Distribution in...

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European control Conference (ECC)

作者： Amani R. Ynineb Erhan Yumuk Hamed Farbakhsh Ghada Ben Othman Dana Copot Isabela R. Birs Cristina I. Muresan Robin De Keyser Samir Ladaci Clara M. Ionescu Martine Neckebroek Department of Electromechanics Ghent University Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Science Park 125 Zwijnaarde Belgium Department of Control and Automation Engineering Technical University of Istanbul Maslak Istanbul Turkey Department of Automation Technical University of Cluj Napoca Romania Cluj Romania Department of Automatics and Control Engineering National Polytechnic School Algiers Algeria Department of Anesthesia Ghent University Hospital Ghent Belgium

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In personalized medicine applications such as general anesthesia, an individualised pharmacokinetic (PK) model requires to move away from the classical assumption of homogeneous drug mixing in various tissue compartments in the body. By default, these model coefficients are pre-surgery initialized from population based models as a function of age, gender, weight, height, lean body mass and do not include at this moment specific drug diffusion patterns in the fat compartment, whereas various types of fat will induce various time constants in non-lean patients. In this work, the pharmacokinetic compartmental model structure is revisited to account for non-uniform distribution of uptake/clearance time constants in patients as a nonlinear function of body mass index. Simulations are confirming expected patterns of drug distribution in the body and can account for post-anesthesia side effects up to 72 hours. The model is a novel advance in providing the control community with yet increasingly realistic patient models for closed loop control of anesthesia.

关键词： Drugs Precision medicine Sociology Surgery Europe Tail Anesthesia

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Disturbance Observer-Based control of Weight on Bit in Drilling process with Formation Variation

Disturbance Observer-Based Control of Weight on Bit in Drill...

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Asian control Conference

作者： Shipeng Chen Wangnian Li Chengda Lu Yang Zhou Weihua Cao Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China CCTEG Xi'an Research Institute (Group) Co. Ltd. Xi'an China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In deep geological drilling, encountering various formations is inevitable. Formation changes can lead to fluc-tuations in the weight on bit due to the bit-rock interaction. This paper proposes a disturbance observer-based weight on bit control system to mitigate the adverse effects of formation changes on system performance. First, an axis-torsion coupled dynamic model is established, and the relationship between the two dimensions is analyzed. The validity of the model is confirmed through comparison with field data collected from a geothermal well drilling operation. Then, a disturbance observer is designed to estimate and compensate for the disturbance at the control input, thereby reducing weight on bit fluctuations caused by formation variations. Simulation results considering formation variation during drilling verify the effectiveness of the proposed method.

关键词： Drilling Simulation System performance Geology process control control systems Disturbance observers

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Enhancing Pain Level Assessment in Post-Surgery Patients Using Artificial Intelligence Algorithms

Enhancing Pain Level Assessment in Post-Surgery Patients Usi...

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European control Conference (ECC)

作者： G. Ben Othman E. Yumuk D. Copot A. R. Ynineb H. Farbakhsh I. R. Birs C. I. Muresan R. De Keyser I. Chihi C. M. Ionescu M. Neckebroek Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Ghent University Gent Belgium Department of Control and Automation Engineering Istanbul Technical University Maslak Istanbul Turkey Department of Automation Technical University of Cluj-Napoca Cluj-Napoca Romania Department Of Engineering Faculty of Science Technology and Medicine University of Luxembourg Kirchberg Luxembourg Department of Anesthesia Ghent University Hospital Ghent Belgium

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

control performance decreases significantly in the presence of uncertainty in variable availability, measurement noise, or instrumentation failure. In cluttered environments such as the Post Anesthesia Care Unit (PACU), clinical measures are often influenced by noise and artifacts. An important component in post-operative treatment is the assessment and management of pain levels. However, reliable information is critical for clinically relevant results and improved patient outcomes. From a control engineering point of view, variables are often estimated and interpolated to allow a suitable flow of feedback information to control loops for the optimization of drug dosages. In this context, Artificial Intelligence (AI) stands as a promising tool to augment pain level assessment. This study introduces and compares two AI-based approaches for predicting continuous Numerical Rating Scales (NRS) based on heart rate (HR) data. The first approach uses polynomial regression, lasso regression, and ridge regression, while the second employs an LSTM model. Notably, the AI prediction model, independent of traditional interpolation techniques, outperforms the approach relying on interpolation. The proposed AI-based method holds promise for continuous estimation and can serve as an estimator for model-based control. This proof of concept study underscores the potential of AI tools to enhance pain level assessment.

关键词： Heart rate Interpolation Uncertainty Pain Noise Numerical models Noise measurement

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Design of Supervisory Model Predictive control for Building HVAC System Subject to Time-Varying Operating Points

Design of Supervisory Model Predictive Control for Building ...

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International Conference on control, automation and systems ( ICCAS)

作者： Sitthiphat Promchaiwattana David Banjerdpongchai Department of Electrical Engineering Faculty of Engineering Intelligent Control Automation of Process Systems Research Unit Chulalongkorn University 254 Phayathai Road Pathumwan Bangkok Thailand

This paper presents the design of supervisory model predictive control for HVAC systems with consideration of peak demand shaving and thermal comfort. In this work, we analyze the operating points with the thermal comfort requirement. Afterwards, we linearize the nonlinear dynamic model to a linear time-varying model. In particular, we specify that the operating point of the open-loop HVAC system satisfies the thermal comfort condition. This makes the predicted mean vote (PMV) equal to zero or nearly to zero. Subsequently, we calculate the zone temperature, the zone humidity ratio, and the volumetric flow rate. When considering the time-varying disturbance profiles, it appears that the operating points are time-varying. We observe that the coefficient of performance (COP) and the operating points are time-varying which lead to time-varying model. Moreover, we design supervisory control (SC) and model predictive control (MPC) for linear time-varying model. In the SC design, we aim to find the optimal reference zone temperature which is used as the reference signal for MPC. In the MPC design, the objectives are twofold. First, the zone temperature tracks the reference signal. Second, both electrical energy cost and deviation of desired thermal comfort are minimized. The computer simulation shows that MPC of time-varying HVAC system yields the best reference tracking. In addition, it reduces total electrical energy cost the most. We conclude that the optimal temperature reference can be effectively applied to the building HVAC systems while the occupants feel comfortable and the total electrical energy cost is the lowest.

关键词： HVAC Costs Input variables Buildings Predictive models Supervisory control Thermal analysis

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Robustness analysis of a fractional order control system for the hemodynamic variables in anesthetized patients

Robustness analysis of a fractional order control system for...

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European control Conference (ECC)

作者： Erwin Hegedus Mihaela Ghita Isabela R. Birs Dana Copot Cristina I. Muresan Department of Automation Technical University of Cluj-Napoca Memorandumului Street no. 28 Cluj-Napoca Romania DySC research group on Dynamical Systems and Control Ghent University Technologiepark 125 Ghent Belgium

Computer-based control of anesthesia is a puzzle requiring multiple other states to be suitably monitored and controlled. Among these, hemodynamic stabilization is a must. Very few studies have been reported regarding the automatic control of the combined anesthesia-hemodynamic systems. Hemodynamic states are strongly affected by hypnotic drugs. At the same time, drugs used for hemodynamic control influence the depth of hypnosis. In this paper, a solution to maintain anesthetic and hemodynamic variables within safe operating ranges is presented and consists in a multivariable fractional order controller. The robustness of the proposed solution is analysed by considering a benchmark patient model and data from 24 patients.

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