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International Conf on Electrical and Electronic engineering (ICEEE)

作者： Nurettin Çerçi Yaprak Yalçin Mechatronics Engineering Department Istanbul Technical University Istanbul Turkey Control and Automation Engineering Department Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

This work focuses on the control of a nonlinear autonomous motorcycle model using Probabilistic Model Predictive control (MPC). The main purpose of this work is to control the speed, yaw angle and roll angle of the motorcycle while keeping its balance during a maneuver. The Probabilistic MPC takes into account the probabilistic disturbances acting on the control inputs or the state variables. The cost function of the optimization of this proposed nonlinear probabilistic MPC is different than the cost of traditional deterministic MPC, such that, it contains terms that represent the mean of the state variable which is calculated with the help of an Extended Kalman Filter (EKF) and also the terms as the functions of covariances of the state variables and control inputs. The optimization algorithm is fed with these mean and covariance values every time instant, then the controller calculates the optimal control sequence to apply it to the system model. The speed of the motorcycle, the yaw angle and, the roll angle of the motorcycle are controlled with good efficiency.

关键词： Costs Motorcycles Optimal control Predictive models Probabilistic logic Cost function Kalman filters Predictive control

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Environmental Consequences of Institutional Facts in Artificial Institutions

Environmental Consequences of Institutional Facts in Artif...

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International Workshop on Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems, COINE 2021, Co-located with the 20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021

作者： Cunha, Rafhael R. Hübner, Jomi F. de Brito, Maiquel Campus Vacaria Vacaria Brazil Automation and Systems Department Federal University of Santa Catarina Florianópolis Brazil Control Automation and Computation Engineering Department Federal University of Santa Catarina Blumenau Brazil

ISBN: (纸本)9783031166167

In multi-agent systems, the agents may have goals that depend on the common interpretation of actions and other agents acting in the system. These goals are thus social goals. Artificial institutions are used to provide such a social interpretation by assigning statuses to the concrete elements that compose the system. These statuses are supposed to enable the assignee element to perform functions that are not exclusively inherent to their design features. However, the consequences in the environment of the enabled functions are not explicit in the existing models of artificial institutions. As a consequence, (i) agents may have difficulties reasoning about the achievement of their social goals and (ii) these institutions are not well instrumented to receive incoming agents in the case of open systems. Considering these problems, this paper proposes the addition of purposes in artificial institution models to express the consequences in the environment of the constitution of status-functions helping the agents to reason about the fulfillment of their social goals. We evaluate the proposal in some scenarios, showing how the agents can use purposes to reason about the satisfaction of their social goals in institutional contexts and how the institution can be flexible enough to support new agents operating in the system. © 2022, Springer Nature Switzerland AG.

关键词： Multi agent systems

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Analysis and Preliminary Results of a Feedback-Feedforward controller for Depth of Anesthesia

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IFAC-PapersOnLine 2024年第7期58卷 216-221页

作者： Erwin Hegedus Marcian D. Mihai Isabela R. Birs Hamed Farbakhsh Erhan Yumuk Dana Copot Eva H. Dulf Robain De Keyser Clara M. Ionescu Cristina I. Muresan Department of Automation Technical University of Cluj-Napoca Memorandumului Street no. 28 400114 Cluj-Napoca Romania Ghent University Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Science Park 125 Zwijnaarde 9052 Belgium Istanbul Technical University Department of Control and Automation Engineering Istanbul Turkey

In a computer-based anaesthesia control system, the depth of hypnosis must be correctly maintained. The regulated variable is the Bispectral Index scale (BIS) controlled via the Propofol drug rate. The anesthesiologist administers Propofol to prevent unwanted fluctuations in the controlled variable during surgical stimulation, which acts as an unmeasurable disturbance on the BIS signal. In this paper, a feedback controller is paired with a feedforward control action. Based on existing clinical protocols, a digitalized disturbance signal that mimics the actual surgical stimulus is employed in the feedforward controller design as a measurable disturbance. To account for the time delay in the BIS measurements, a time delay estimation algorithm is developed and used to estimate the patient time delay. The digitalized disturbance signal is then shifted based on the estimated time delay to ensure a pre-emptive action of the feedforward controller. Two different designs of the feedforward controller are developed. Closed loop simulations considering a nominal patient with and without the feedforward control action are presented and compared. The results show that the surgical stimulus is better tackled using a feedforward control action, even if the actual surgical stimulus is not entirely known.

关键词： feedforward control fractional order control depth of hypnosis time delay estimation closed loop control of anesthesia

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GRU-Net: Gaussian Attention Aided Dense Skip Connection Based MultiResUNet for Breast Histopathology Image Segmentation 28th

GRU-Net: Gaussian Attention Aided Dense Skip Connection Base...

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28th Annual Conference on Medical Image Understanding and Analysis, MIUA 2024

作者： Roy, Ayush Pramanik, Payel Ghosal, Sohom Valenkova, Daria Kaplun, Dmitrii Sarkar, Ram Department of Electrical Engineering Jadavpur University Kolkata700032 India Department of Computer Science and Engineering Jadavpur University Kolkata700032 India Department of Electronics and Communication Engineering International Institute of Information Technology Chhattisgarh India Department of Automation and Control Processes Saint Petersburg Electrotechnical University LETI Saint Petersburg Russia Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China

ISBN: (纸本)9783031669545

Breast cancer is a major global health concern. Pathologists face challenges in analyzing complex features from pathological images, which is a time-consuming and labor-intensive task. Therefore, efficient computer-based diagnostic tools are needed for early detection and treatment planning. This paper presents a modified version of MultiResU-Net for histopathology image segmentation, which is selected as the backbone for its ability to analyze and segment complex features at multiple scales and ensure effective feature flow via skip connections. The modified version also utilizes the Gaussian distribution-based Attention Module (GdAM) to incorporate histopathology-relevant text information in a Gaussian distribution. The sampled features from the Gaussian text feature-guided distribution highlight specific spatial regions based on prior knowledge. Finally, using the controlled Dense Residual Block (CDRB) on skip connections of MultiResU-Net, the information is transferred from the encoder layers to the decoder layers in a controlled manner using a scaling parameter derived from the extracted spatial features. We validate our approach on two diverse breast cancer histopathology image datasets: TNBC and MonuSeg, demonstrating superior segmentation performance compared to state-of-the-art methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Gaussian distribution

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Proton Exchange Membrane Fuel Cell Thermal System Modeling and control

Proton Exchange Membrane Fuel Cell Thermal System Modeling a...

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International Conf on Electrical and Electronic engineering (ICEEE)

作者： Tuna Han Özdemir Claudia Fernanda Yaşar Department of Control and Automation Engineering Yıldız Technical University AVL Research and Engineering İstanbul Turkey Department of Control and Automation Engineering Yıldız Technical University İstanbul Turkey

The urgent issue of global warming and its adverse effects, including wildfires, water scarcity, and the spread of diseases, calls for concerted efforts to mitigate emissions and curb climate change. Among the effective strategies is the reduction of carbon emissions, for which hydrogen-powered proton exchange membrane fuel cell systems are vital. These systems generate electricity through chemical reactions involving hydrogen, with only water and heat as byproducts, hence their environmentally friendly nature. Fuel cell efficiency is higher than conventional systems depending on the type and the operating temperature. Proper thermal control is essential for maintaining high efficiency. This research paper aims to examine standard models of proton exchange membrane fuel cell thermal systems and suggest an efficient control approach. The system dynamics are derived from fundamental models, and an adaptive PID controller is simulated with MATLAB/Simulink. The paper also presents a comparative analysis between traditional PID control and adaptive PID, an advanced control technique.

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Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

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IET control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Closed loop systems

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Prescribed-time stabilization for high-order nonlinear systems with a pre-specified asymmetric output constraint

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Journal of the Franklin Institute 2023年第4期360卷 3545-3574页

作者： Chen, Chih-Chiang Sun, Zong-Yao Xu, Sendren Sheng-Dong Department of Systems and Naval Mechatronic Engineering National Cheng Kung University Tainan70101 Taiwan Institute of Automation Qufu Normal University Shandong Province Qufu273165 China Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taiwan Advanced Manufacturing Research Center National Taiwan University of Science and Technology Taiwan

This article considers the problem of prescribed-time stabilization for a class of uncertain high-order nonlinear systems (i.e., systems in the p-normal form) with a pre-specified asymmetric output constraint. A core ingredient, tangent-type barrier function, is proposed first by skillfully excavating and assimilating the inherent properties of system nonlinearities. Based on the barrier function, as well as a serial of nested signum functions, the celebrated technique of adding a power integrator is renovated finely to establish a new design approach by which a continuous state feedback prescribed-time stabilizer, along with a tangent-type asymmetric barrier Lyapunov function, can be constructed in a systematic fashion, thereby guaranteeing the performance of prescribed-time state convergence and ensuring the fulfillment of pre-specified output constraints surely. Benefiting from the composite characteristics of the presented tangent-type barrier Lyapunov function and the signum functions, the proposed approach further offers a unified nature in design enabling us to organize a prescribed-time stabilizer that is simultaneously valid and executable for the system undergone or free from output constraints, without the need of changing the controller structure. The effectiveness and superiority of the developed approach are illustrated by a numerical example. © 2022 The Franklin Institute

关键词： Lyapunov functions

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Event-triggered learning of Euler-Lagrange systems: A Koopman operator framework 63

Event-triggered learning of Euler-Lagrange systems: A Koopma...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Zheng, Kaikai Shi, Dawei Li, Shilei Shi, Yang Beijing Institute of Technology Miit Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Victoria Faculty of Engineering Department of Mechanical Engineering VictoriaBCV8N 3P6 Canada

ISBN: (纸本)9798350316339

Euler-Lagrange (EL) systems represent a crucial and large class of dynamical systems, and a precise model of the true system would be beneficial in planning and tracking problems. This work aims to learn an unknown EL system using noisy measurement data to achieve improved data utilization efficiency. Specifically, for the considered EL system, a linear representation of the system is constructed using the Koopman operator, which is further characterized by sample data using Willems' fundamental lemma. Moreover, an event-triggered learning mechanism is proposed to improve data utilization efficiency, and it is designed based on the analysis of the learning error bounds. The effectiveness of the proposed event-triggered learning approach is validated through a manipulator example. © 2024 IEEE.

关键词： Lagrange multipliers

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Unmanned Air-Ground Vehicles Path Planning Using Model Predictive control

Unmanned Air-Ground Vehicles Path Planning Using Model Predi...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Gu, Yuanwen Wang, Mi Wu, Huaining Li, Chenlong Li, Gang School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Hangzhou International Innovation Institute Beihang University Hangzhou311115 China Hangzhou Innovation Institute Beihang University Hangzhou310051 China Department of Control Science and Engineering Tongji University Shanghai201800 China

ISBN: (纸本)9789819639649

In this article, the problem of air-ground vehicles path planning is investigated. The objective is to navigate each vehicle from its starting position to the intended destination, while avoiding collisions with obstacles and other vehicles. First, by combining the objective functions of unmanned ground vehicle (UGV) and unmanned aerial vehicles (UAVs) with the constraints of system equations, control constraints and obstacle avoidance constraints, the vehicles’ path planning is formulated as multiple model predictive control (MPC) problems. Second, considering the interdependencies inherent in these optimization problems, we employ an assumed state method to decouple them effectively. Third, the control inputs of the UGV and UAVs are obtained by solving quadratic programming problems and thus the vehicles’ path can be obtained. Finally, a simulation example is shown to illustrate the effectiveness of the proposed path planning method. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Predictive control systems

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Implementation of Neural Networks in Real-Time Swarm Robotics Applications

Implementation of Neural Networks in Real-Time Swarm Robotic...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Emre Yazici Hakan Temeltas Department of Control and Automation Engineering/Software Development Department Istanbul Technical University/NISO Software Technologies Istanbul/Izmir Turkey Department of Control and Automation Engineering Istanbul Technical University Istanbul Turkey

Over the last few decades, significant attention has been devoted to the coordinated motion of swarm systems, which involve multiple autonomous robots. These systems have a range of potential applications, such as creating formations with physical or non-physical bonds, navigating to desired locations while maintaining formation, and preventing collisions. To achieve coordinated motion, recent researches have focused on the potential function method. We previously validated novel potential functions and developed a sliding-mode speed controllers to promote collective behavior. In this study, we implement an accepted neural network with one hidden and one output layer to update potential function weights with decentralized manner in real-time, thereby enhancing swarm behavior for formation creation and maintenance. The effectiveness of this approach is demonstrated through simulation and processor-in-the-loop tests using two different micro-controllers as well as measuring execution time of neural networks' models. By successfully validating neural networks implementation in this context, our study extends the current understanding of swarm behavior and opens up new possibilities for real-time swarm applications.

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