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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Ti, Yaqi Li, Changhe Yang, Shengxiang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350314588

With increasing people who suffer from diet-related diseases, providing suggestions for personal daily nutrient-dense intake is highly expected. However, current dietary nutrition models are less precise, and dietary nutrition optimizers usually fail to give satisfactory solutions. Therefore, we construct a constrained many-objective nutrition model with more precise nutrient assessments and a scalable constrained many-objective benchmark set. This test suite has great flexibility in evaluating algorithms' performance on high dimensional search and objective spaces with some feasible region fragments. We also propose a kd-tree based dynamic constrained many-objective evolutionary algorithm to search for customized food combinations according to personal daily consumption and intake preference. Experiments show that our algorithm has better diversity maintenance ability in high dimension space. © 2023 IEEE.

关键词： Nutrition

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A Decoupled Fractional Order control Strategy to Increase Patient Safety During Anesthesia-Hemodynamic Interactions

A Decoupled Fractional Order Control Strategy to Increase Pa...

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European control Conference (ECC)

作者： Erwin Hegedus Marcian D. Mihai Isabela R. Birs Hamed Farbakhsh Erhan Yumuk Dana Copot Robain De Keyser Clara M. Ionescu Cristina I. Muresan Department of Automation Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Electromechanics Ghent University Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Zwijnaarde Belgium Department of Control and Automation Engineering Istanbul Technical University Istanbul Turkey

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Monitoring and control of general anesthesia, involving cardiac output or mean arterial pressure are critical to ensure patient safety during surgery. Several computer control solutions have been developed for each of the anesthesia components and hemodynamic processes. However, most do not tackle the synergistic and antagonistic effects of the anesthetic and hemodynamic drugs. Hitherto, only a handful of preliminary results and ideas regarding multivariable control have been reported so far, usually considering a simplified decentralized approach. A decoupled control strategy is proposed here to reduce the interaction between the hemodynamic and anesthesia sub-systems, hence increasing the robustness and stability of the overall control loop. Due to their intrinsic robustness to uncertainty and process model variability, fractional order controllers are designed to ensure that more specific performance criteria are addressed, compared to the traditional PIDs. The decoupled control strategy is compared to the decentralized approach to validate the minimization of the interactions. A robustness analysis is performed using a benchmark patient model and data from 24 patients.

关键词： Uncertainty Stability criteria Surgery Process control Anesthesia Robustness Hemodynamics

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Safe Force/Position Tracking control via control Barrier Functions for Floating Base Mobile Manipulator systems

Safe Force/Position Tracking Control via Control Barrier Fun...

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European control Conference (ECC)

作者： Maryam Sharifi Shahab Heshmati-Alamdari ABB Corporate Research Västerås Sweden Department of Electronic Systems Section of Automation & Control Aalborg University Denmark

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper introduces a safe force/position tracking control strategy designed for Free-Floating Mobile Manipulator systems (MMSs) engaging in compliant contact with planar surfaces. The strategy uniquely integrates the control Barrier Function (CBF) to manage operational limitations and safety concerns. It effectively addresses safety-critical aspects in the kinematic as well as dynamic level, such as manipulator joint limits, system velocity constraints, and inherent system dynamic uncertainties. The proposed strategy remains robust to the uncertainties of the MMS dynamic model, external disturbances, or variations in the contact stiffness model. The proposed control method has low computational demand ensures easy implementation on onboard computing systems, endorsing real-time operations. Simulation results verify the strategy's efficacy, reflecting enhanced system performance and safety.

关键词： Uncertainty System dynamics Computational modeling Welding System performance Dynamics Kinematics

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Stability and Bifurcation control of Fractional-Order Coupled Hindmarsh-Rose Neural Networks 42

Stability and Bifurcation Control of Fractional-Order Couple...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Feng Zhou, Feifan Wang, Wei Cai, Gang Wang, Hua O Yang, Xiuqin School of Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Ministry of Education for Intelligent Technology of Earth Exploration China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Boston University Department of Mechanical Engineering BostonMA02215 United States School of Education Minzu University of China Beijing100081 China

ISBN: (纸本)9789887581543

This article investigates a fractional-order coupled Hindmarsh-Rose neural networks model. Firstly, the existence and stability of an equilibrium point in the system are verified. Then, the periodic bifurcation behavior of the system on a two-parameter plane is studied, and numerical simulations show the existence of both non -chaotic and chaotic plus periodic bifurcation behavior on the two-parameter plane. Finally, a feedback controller was designed to stabilize the bifurcation point of the delayed system and increase the stable range of the system. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Neural network models

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Estimation of Bottom-Hole Pressure Based on Bayesian Optimization and Bidirectional Long Short-Term Memory Neural Network 43

Estimation of Bottom-Hole Pressure Based on Bayesian Optimiz...

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43rd Chinese control Conference, CCC 2024

作者： Zhang, Zihan Lu, Chengda Wang, Yawu Zhou, Yang Wu, Min She, Jinhua China University of Geosciences School of Future Technology Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China China University of Geosciences School of Automation Wuhan430074 China Tokyo University of Technology School of Engineering Hachioji192-0982 Japan

ISBN: (纸本)9789887581581

Bottom-hole pressure (BHP) plays a crucial role in a drilling process. The accurate estimation of BHP ensures safe and efficient drilling operations. Artificial neural networks can predict BHP indirectly by analyzing the non-linear relationship with wellhead variables. This paper introduces a BHP estimation model that leverages Bayesian optimization and a bidirectional long short-term memory neural network (BO-BiLSTM). The model employs Bayesian optimization to determine optimal hyperparameters, including the number of hidden layers, initial learning rate, and L2 regularization parameter. The BO-BiLSTM model achieves a mean absolute percentage error of 2.056% and an R-squared score of 0.94596. The results demonstrate that the presented model enhances estimation precision and outperforms other methods examined in this study. This method facilitates indirect measurement of BHP using wellhead data, and contributes to the exploration of deep-sea resources in complex environments. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Bottom hole pressure

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Safe Force/Position Tracking control via control Barrier Functions for Floating Base Mobile Manipulator systems

arXiv

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arXiv 2024年

作者： Sharifi, Maryam Heshmati-Alamdari, Shahab ABB Corporate Research Västerås Sweden The Section of Automation & Control Department of Electronic Systems Aalborg University Denmark

关键词： Real time systems

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Equivalent input disturbance-based load frequency control for smart grid with air conditioning loads

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Science China(Information Sciences) 2022年第2期65卷 106-123页

作者： Li JIN Yong HE Chuan-Ke ZHANG Xing-Chen SHANGGUAN Lin JIANG Min WU School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical Engineering and Electronics University of Liverpool Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Integrating intermittent wind power into power systems results in low or zero inertia, threatening their frequency stability. To accommodate intermittent generations, the demand response(DR) is introduced, and air conditioning loads(ACs) account for an increasing proportion of all loads. The replacement of traditional generators with wind turbines and the ACs user uncertainties produce parameter uncertainties. This paper aims to construct an equivalent input disturbance(EID)-based load frequency control(LFC) strategy for the power system by considering wind power and ACs. First, an open-loop model is constructed for the LFC scheme with parameter uncertainties. Then, the parameter uncertainties and external disturbance are lumped into a fictitious disturbance, which is estimated using an EID *** incorporating the estimation of disturbance into the control input, the disturbance-rejection performance is achieved. Next, the Lyapunov theory is used to derive the two linear-matrix-inequality-based asymptotic stability criteria. A design algorithm is developed for the EID-based LFC scheme by exploiting an overall performance evaluation index. Finally, simulation results for the single-area and two-area LFC schemes show that, compared with the existing approaches, the method presented realizes the better disturbance rejection and higher robustness against parameter uncertainties, wind power fluctuation, and tie-line power ***, its robustness to time delays is verified.

关键词： equivalent input disturbance load frequency control parameter uncertainties wind power air conditioning loads

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Dynamic Analysis and control of Fractional Order Memristor Hopfield Neural Network 42

Dynamic Analysis and Control of Fractional Order Memristor H...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Feng Cai, Gang Zhou, Feifan Wang, Wei Wang, Hua Yang, Xiuqin School of Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Ministry of Education for Intelligent Technology of Earth Exploration China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan4300748 China Boston University Department of Mechanical Engineering BostonMA02215 United States School of Education Minzu University of China Beijing100081 China

ISBN: (纸本)9789887581543

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network (fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Hopfield neural networks

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Predicting microbe-disease associations via attention guided graph convolutional networks 4

Predicting microbe-disease associations via attention guided...

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4th International Conference on Biomedicine and Bioinformatics Engineering, ICBBE 2024

作者： Gong, Shiyun Zhu, Yuan School of Automation China University of Geosciences Lumo Road Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Lumo Road Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Lumo Road Hongshan District Hubei Wuhan430074 China School of Mathematics and Physics China University of Geosciences Lumo Road Wuhan430074 China

ISBN: (纸本)9781510682443

It is important to predict microbe-disease associations, as it helps to understand the cause of diseases episodes, the prevention of diseases, among other roles. Traditionally, the study of microbe-disease association is mainly based on laboratory purified culture for research and observation, which is highly scientific but has some limitations, such as some microbes needing to be cultured in a laboratory environment and costs heavily. This study proposes an attention guided graph convolutional network d approach (AGGCN) to predict possible potential associations between microbes and diseases. In the first place, AGGCN constructs four different similarity networks of microbes and diseases, which are combined with association networks to form a microbe-disease heterogeneous network. Subsequently, it is used as an input to the graph convolutional neural network to obtain each node embedding of this heterogeneous network. In this study, a three-layer network is used, so three different types of node embeddings can be obtained, and these three different types of node embedding representations are integrated via the multichannel graph attention mechanism to obtain the final node embeddings. Finally, the node embeddings obtained above are used for association prediction of microbes-diseases in heterogeneous networks. Experimentally verified, the AUC of AGGCN is 0.8972, and the AUPR is 0.5387. Comparative experimental results indicated that AGGCN shows better than the other five mainstream methods. It provides a new insight to explore network potential feature representation and predict associations between microbe and disease. © 2024 SPIE.

关键词： Graph neural networks

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Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays 42

Stability and Bifurcation control of Fractional BAM Neural N...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Feng Wang, Wei Cai, Gang Zhou, Feifan Wang, Hua O Yang, Xiuqin School of Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Ministry of Education for Intelligent Technology of Earth Exploration China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Boston University Department of Mechanical Engineering BostonMA02215 United States School of Education Minzu University of China Beijing100081 China

ISBN: (纸本)9789887581543

Based on fractional calculus theory and reaction-diffusion equation theory, a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is investigated. By constructing the phase space basis based on the Laplace operator eigenvector, the system equation is linearized to obtain the characteristic equation. Then, the characteristic equation is analyzed, and the local stability of the system at the equilibrium point is discussed. And taking the time delay as the bifurcation parameter, the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay changes. Moreover, a state feedback controller is designed to control the bifurcation of the system. Finally, the theoretical derivation is verified by numerical simulation. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Time delay

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