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Methods for Developing Effective Models of Biomedical Processes in MATLAB 17

Methods for Developing Effective Models of Biomedical Proces...

17th IEEE international conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2024

作者： Kolisnyk, Kostyantyn Kolisnyk, Viktoriia Wik, Torsten National Technical University 'Kharkiv Polytechnic Institute' Dept. Industrial and Biomedical Electronics Kharkov Ukraine Kharkiv National University of Radio Electronics Dept. Media Engineering and Information Radioelectronic Systems Kharkiv Ukraine Institutionen for elektroteknik Chalmers tekniska hogskola Dept. Systems and Control Technology Electrical Technology Gothenburg Sweden

ISBN: (纸本)9798331520564

Mathematical modeling in the study of dynamic processes in biomedicine is currently widely used. The use of mathematical statistics and formal logic methods in the analysis of complex biomedical processes is especially important for increasing the efficiency of biomedical research. Taking into account the established growth of the technical base of research, the development of new technologies and technical means for obtaining and processing statistical biomedical information, the use of mathematical modeling methods is a fairly promising direction in scientific and practical work. In this paper the authors studies the possibility of improving the quality of biomedical process modeling using the MATLAB software environment. The research was carried out on real statistical material obtained by the authors during a full-scale experiment to study the impact of a complex of external factors on patients. The results obtained in this work can be used in the implementation of scientific and applied research of biomedical processes. © 2024 IEEE.

关键词： MATLAB

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Optimal PD-PD and State Feedback control of Underactuated Ball and Beam System with Uncertainty and Disturbances 12th

Optimal PD-PD and State Feedback Control of Underactuated Ba...

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12th international conference on Mathematical modeling in Physical Sciences (IC-MSQUARE)

作者： Sahu, Yaman Gupta, Bibek Wael, Mahmoud Shalaby, Raafat Nile Univ Sch Engn & Appl Sci MECT Program Giza Egypt Erasmus Mundus Joint Master Mech Engn EU4M Oviedo Spain Nile Univ Smart Engn Syst Res Ctr SESC Giza Egypt Menoufia Univ Fac Elect Engn Menoufia Egypt

ISBN: (纸本)9783031529672;9783031529658;9783031529641

This research paper investigates the optimal control of the ball and beam system, a challenging fourth-degree system that is commonly used in control studies. Four different control techniques, namely cascaded PD-P, cascaded PD-PD, optimized cascaded PD-PD control using a genetic algorithm, and state feedback control, are compared in terms of their performance. The study aims to achieve specific design criteria, including low rise time, less than three percent overshoot, and less than two seconds of settling time. In addition, the impact of disturbances, uncertainty, control action, and beam angle on the robustness of the system is also examined. MATLAB software is employed to implement and evaluate the performance of the different control methods. The findings contribute to the understanding of how to achieve optimal control of complex systems like the ball and beam system.

关键词： Optimal control State feedback Genetic algorithm Ball and beam Robust control

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Intelligent Support systems for NPP Operators: Dynamic modeling and Operational Diagnostics

Intelligent Support Systems for NPP Operators: Dynamic Model...

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2023 international conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Jharko, Elena Chernyshov, Kirill V.A. Trapeznikov Institute of Control Sciences The Russian Academy of Sciences Laboratory of Distributed Information and Control Systems Moscow Russia V.A. Trapeznikov Institute of Control Sciences The Russian Academy of Sciences Laboratory of Identification of Control Systems Moscow Russia

ISBN: (纸本)9781665475952

The efficiency of human-machine interaction is highly dependent on the quality of information support that the power unit (PU) operators receive from the control system in different operating modes of NPP PU. The paper shows the importance of intelligent support systems (ISS) for NPP operators to ensure the reliable operation of the NPP power unit. The most significant elements of the ISS for operators in terms of the diagnostic system are the block of dynamic modeling, which anticipates the course of technological processes, and the expert system. The paper analyzes the state of the problem of creating dynamic modeling systems, singles out a "three-step"approach to creating the predictive models of a technological process, and shows its shortcomings. Relationships between dynamic modeling and operational diagnostics (OD) are presented. A group of standard diagnostic systems and classes of problems of the solvable problems of ODs are considered. The implementation of the solution to the problem of diagnosing in the intelligent support system of the NPP operator, as well as functional diagrams of operational diagnostics, is presented. The proposed implementation of the tasks of operational diagnostics is used to create intelligent support systems for NPP operators. © 2023 IEEE.

关键词： Expert systems

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Model-predictive optimal control of ferrofluidic microrobots in three-dimensional space

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international JOURNAL OF ROBOTICS RESEARCH 2025年第5期44卷 826-839页

作者： Skowronek, E. Olga Baker, Luke S. Ahmed, Reza Marvi, Hamid Arizona State Univ Sch Engn Matter Transport & Energy 501 E Tyler Mall Tempe AZ 85287 USA Univ Texas Rio Grande Valley Coll Engn & Comp Sci Edinburg TX USA Los Alamos Natl Lab Ctr Nonlinear Studies Theoret Div Los Alamos NM USA

Ferrofluid microrobots have emerged as promising tools for minimally invasive medical procedures. Their unique properties to navigate complex fluids and reach otherwise inaccessible regions of the human body have enabled new applications in targeted drug delivery, tissue engineering, and diagnostics. This paper proposes a model-predictive controller for the external magnetic manipulation of ferrofluid microrobots in three dimensions (3D). The internal optimization routine of the controller determines appropriate changes in the applied electromagnetic field to minimize the deviation between the actual and desired trajectories of the microrobot. A linear system governing locomotion is derived and used as the equality constraints of the optimization problems associated with the feedback index. In addition to ferrofluid droplets, the controller presented in this work may be applied to other magnetically-pulled microrobots. Several experiments are performed to validate the controller and showcase its ability to adapt to changes in system parameters such as the desired tracking trajectory and the size, orientation, deformation, and velocity of the microrobot. The accuracy of the controller is analyzed for each experiment, and the average error is found to be within 0.25 mm for small velocities. An additional experiment is performed to demonstrate significant improvement over a PID controller that is optimally tuned using Bayesian optimization. The results presented in this paper suggest that the proposed control algorithm could enable new microrobotic capabilities in minimally invasive medical procedures, lab-on-a-chip applications, and microfluidics.

关键词： modeling control learning for soft robots micro/nano robots medical robots and systems

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modeling and Optimization of controlled Conveyor systems Using Intelligent controllers 15th

Modeling and Optimization of Controlled Conveyor Systems U...

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15th international conference on Optimization and Applications, OPTIMA 2024

作者： Petrov, Alexey Druzhinina, Olga Masina, Olga Bunin Yelets State University Yelets Russia Federal Research Center "Computer Science and Control" of Russian Academy of Sciences Moscow Russia V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783031791185

The construction of generalized mathematical models is proposed that describe the dynamics of a controlled belt conveyor with a variable angle between the horizontal plane and the plane of the belt. The models under consideration are defined using nonlinear nonstationary systems of four differential equations with switching. Switching modes are characterized by a change in the loading and unloading sequence. Statements of optimal control problems are presented under restrictions on the magnitude of control and on the speed of control. Synthesis of neural network controllers for stabilization of the angular position of the conveyor is carried out. controllers are synthesized using such direct propagation neural networks for which reinforcement learning is implemented based on the optimization algorithm of differential evolution. A comparative analysis of the effectiveness of synthesized controllers is carried out. Algorithmic support for modeling controlled conveyor systems is developed using intelligent analysis and global parametric optimization methods. The results of computational experiments are presented. The obtained results can find application in solving problems of optimal stabilization of dynamic systems with switching. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Belt conveyors

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Establishing of Dynamic control Functions for a Hybrid Robot Based on Analytical Mechanics Principles 33rd

Establishing of Dynamic Control Functions for a Hybrid Robot...

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33rd international conference on Robotics in Alpe-Adria-Danube Region (RAAD)

作者： Schonstein, Claudiu Tech Univ Cluj Napoca Cluj Napoca Romania

ISBN: (纸本)9783031592591;9783031592577;9783031592560

The use of complex mechanical systems in different tasks assumes the controlling of each motor from the kinematic joints known as dynamic control equations. The moving differential equations for any mechanical system can be expressed very efficiently based on principles from Analytical Mechanics, among which the method developed by Lagrange-Euler provides explicit equations of motion. The Lagrange-Euler second kind formalism is an analytical approach extremely useful in modelling of multibody systems which uses an important notion in dynamics-kinetic energy. These equations can be used to analyze and devise advanced control strategies by mathematical modeling based on mathematical algorithms. In this paper, for two robot structures (serial and mobile), considering that are working independently, will be established the dynamic control functions, using a generalized algorithm, consisting in geometrical, kinematical and dynamical modeling.

关键词： Robots Dynamic control functions Kinetic energy Algorithm

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Research on Two-Switch Bridge Buck-Boost Converter Based on Active Disturbance Rejection control 6

Research on Two-Switch Bridge Buck-Boost Converter Based on ...

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6th international conference on Energy, Power and Grid, ICEPG 2024

作者： Wu, Wenying Pan, Sanbo Shanghai Dianji University The School of Electrical Engineering Shanghai China

ISBN: (纸本)9798350377798

Power electronic converters, especially buck-boost circuits, play a vital role in energy management, electric vehicles, renewable energy systems and other fields. Due to the traditional PID control, there are some problems such as complex parameter setting, accurate mathematical model, sensitivity to external interference and limited response speed. In this paper, the second-order active disturbance rejection control is used as the basic control structure of the main circuit, which solves the problems of slow dynamic response speed, complex parameter setting and high accuracy of model requirements of PID control. At the same time, the selection of the main circuit structure also has the function of realizing wide input, which can be applied to many occasions. Finally, by analyzing and comparing the output voltage waveforms under the active disturbance rejection control strategy and the double closed-loop proportional integral control applied in different working conditions, the robustness and effectiveness of the active disturbance rejection control strategy applied in this paper are verified. © 2024 IEEE.

关键词： Buck-Boost converter

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Intelligent Manufacturing Flexibility Scheduling Optimization Based on Hybrid NSGA-II Algorithm 7

Intelligent Manufacturing Flexibility Scheduling Optimizatio...

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7th international conference on Mechatronics, Robotics and Automation

作者： Hu, Zhuoya Liu, Jun Xu, Ji Ye, Chaoqian Wuhan Inst Engn Sch Comp Sci & Engn Wuhan 430205 Peoples R China Key Lab Biomarkers & In Vitro Diag Translat Zheji Hangzhou 310063 Peoples R China Hubei Cent China Technol Dev Elect Power Co Ltd Hubei Engn Res Ctr Intelligent Digital Technol Ne Wuhan 430074 Peoples R China

ISBN: (纸本)9798350352481;9798350352474

The flexible job-shop problem is one of the classical problems that have attracted much attention in the field of industrial automation and control. For the Multi-Objective Flexible Job-shop Scheduling Problem (MOFJSP), this paper proposes a hybrid particle swarm Non-dominated Sorting Genetic Algorithm II (NSGA-II) to solve the problem. The high-quality solution of the problem is obtained through particle swarm optimization as part of the initial population of NSGA-II, and an elite strategy is used to prevent the loss of outstanding individuals by mixing all the individuals of the parent and the offspring in a non-dominated sorting method. This approach not only facilitates automation in manufacturing and production but also enhances the control and optimization of complex systems. Furthermore, integrating intelligent transportation systems and the Internet of Things (IoT) into the scheduling process ensures real-time fault diagnosis and fault-tolerant control, thereby improving the overall efficiency and reliability of the production system. The experimental results show that the hybrid optimization approach combining PSO and NSGA-II exhibits superior performance in solving MOFJSP. This research contributes to the advancement of cyber-physical systems and the automation of complex industrial processes.

关键词： flexible job shop scheduling NSGA-II PSO industrial automation control and optimization

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A Soft Robotic System Automatically Learns Precise Agile Motions Without Model Information

A Soft Robotic System Automatically Learns Precise Agile Mot...

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2024 international conference on Intelligent Robots and systems

作者： Bachhuber, Simon Pawluchin, Alexander Pal, Arka Boblan, Ivo Seel, Thomas FAU Erlangen Nurnberg Dept Artificial Intelligence Biomed Engn D-91052 Erlangen Germany Univ Appl Sci & Technol CoRoLab Berlin D-13353 Berlin Germany Indian Inst Technol Bhubaneswar Sch Mech Sci Bhubaneswar 752050 Odisha India Leibniz Univ Hannover Inst Mechatron Syst D-30167 Hannover Germany

ISBN: (纸本)9798350377712;9798350377705

Many application domains, e.g., in medicine and manufacturing, can greatly benefit from pneumatic Soft Robots (SRs). However, the accurate control of SRs has remained a significant challenge to date, mainly due to their nonlinear dynamics and viscoelastic material properties. Conventional control design methods often rely on either complex system modeling or time-intensive manual tuning, both of which require significant amounts of human expertise and thus limit their practicality. In recent works, the data-driven method, Automatic Neural ODE control (ANODEC) has been successfully used to - fully automatically and utilizing only input-output data - design controllers for various nonlinear systems in silico, and without requiring prior model knowledge or extensive manual tuning. In this work, we successfully apply ANODEC to automatically learn to perform agile, non-repetitive reference tracking motion tasks in a real-world SR and within a finite time horizon. To the best of the authors' knowledge, ANODEC achieves, for the first time, performant control of a SR with hysteresis effects from only 30 s of input-output data and without any prior model knowledge. We show that for multiple, qualitatively different and even out-of-training-distribution reference signals, a single feedback controller designed by ANODEC outperforms a manually tuned PID baseline consistently. Overall, this contribution not only further strengthens the validity of ANODEC, but it marks an important step towards more practical, easy-to-use SRs that can automatically learn to perform agile motions from minimal experimental interaction time.

关键词： Feedback control

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control of the Technological Process for Obtaining Propylene Glycol, Functioning in Fuzzy Information Conditions 16th

Control of the Technological Process for Obtaining Propylene...

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16th international conference on Application of Fuzzy systems, Soft Computing and Artificial Intelligence Tools, ICAFS 2023

作者： Melikov, E.A. Magerramova, T.M. Safarova, A.A. Azerbaijan State Oil and Industry University Baku Azerbaijan

ISBN: (纸本)9783031725050

Modern complex chemical-technological systems as automation objects are distinguished by the presence of a large number of controlled and uncontrolled parameters, high productivity, technological modes intensity and ongoing technological operations continuity. The proposed article focuses on the actual problems of analysis, modeling, development of a mathematical formulation and solving the control problem, which is important in the chemical industry, the technological process for producing propylene glycol, which is widely used in various industries, in particular, as a working fluid in hydraulic systems, raw materials in production antifreeze, varnish and paint, tobacco humidifier in the food industry, in the pharmaceutical and cosmetic industries, etc. Here, due to the complexity and impossibility of taking into account factors that are difficult to formalize, changes in technological parameters and process characteristics over a wide range, and the difficulty of monitoring the states of the process under consideration, the apparatus of fuzzy set theory is used. Mathematical models of the process under study are constructed on the basis of the estimating the maximum probability method, in the form of fuzzy regression dependencies connecting the perturbing, control and state parameters of the object under consideration. On the basis of the obtained fuzzy models, a physically based mathematical formulation of the problem of optimal control of the object under study is formulated and a self-adjusting automatic control system with a fuzzy controller is built, which ensures the optimal functioning of the object under conditions of incomplete information. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Chemical industry

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