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检索条件"任意字段=International Conference on Complex Systems: Control and Modeling Problems"

共 12182 条记录，以下是251-260 订阅

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Topological derivative method for control of wave equation on networks 27

Topological derivative method for control of wave equation o...

引用

27th international conference on Methods and Models in Automation and Robotics (MMAR)

作者： Gugat, Martin Qian, Meizhi Sokolowski, Jan Friedrich Alexander Univ Erlangen Nurnberg Dept Data Sci Lehrstuhl Dynam Control & Numer Alexander von Hum Erlangen Germany Polish Acad Sci Syst Res Inst Warsaw Poland East China Normal Univ Shanghai Peoples R China Univ Lorraine Inst Elie Cartan Lorraine CNRS Nancy France

ISBN: (纸本)9798350311075

The dynamical, boundary optimal control problems on networks are considered. The domain of definition for the distributed parameter system is given by a graph G. The optimal cost function for control problem is further optimized with respect to the shape and topology of the graph O. The small cycle is introduced and the topological derivative of the cost with respect to the size of the cycle is determined. In this way, the singular perturbations of the graph can be analyzed in order to change the topology O. The topological derivative method in shape and topology optimization is a new tool which can be used to minimize the shape functionals under the Partial Differential Equations (PDEs) constraints. The topological derivative is used as well for solution of optimum design problems for graphs. In optimal control problems the topological derivative is used for optimum design of the domain of integration of the state equation. As an example, optimal control problems are considered on a cross with a small cycle. The state equation is the wave equation on the graph. The boundary control problem by Neumann conditions at a boundary vertex is solved for a tracking cost function. The shape functional is given by the optimal value of the control cost. The topological derivative of the shape functional is determined for the steady state model with the size of a cycle epsilon -> 0. Numerical results for a model problem are presented.

关键词： Distributed parameter system optimal control shape optimization topological derivative network modeling optimality system

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AN IMPROVED TOTAL INTERPRETIVE STRUCTURAL modeling METHOD FOR CONSTRUCTING INDICATOR systems IN MULTI-CRITERIA DECISION-MAKING problems: THE CASE OF SHIP DESIGN EVALUATION AND SELECTION 42

AN IMPROVED TOTAL INTERPRETIVE STRUCTURAL MODELING METHOD FO...

引用

ASME 42nd international conference on Ocean, Offshore and Arctic Engineering (OMAE)

作者： Chen, Cheng Zhang, Xiangrui Zhang, Pei Feng, Feng Sun, Cong Zhang, Xiuyuan Harbin Engn Univ Coll Shipbldg Engn Harbin Peoples R China Marine Design & Res Inst China Shanghai Peoples R China

ISBN: (纸本)9780791886878

The inherent complexity of large ships makes it challenging to construct appropriate indicator systems for evaluating and selecting optimal ship designs. Knowledge-based expert systems can be reasonable solutions. However, this problem needs more rationality and better operability, especially in complicated multi-criteria decision-making (MCDM) problems with numerous indicators and complex structures. This paper aims to present a universal methodological approach for constructing indicator systems in MCDM problems using an improved total interpretive structural modeling (TISM) method. The classical TISM method is extended under group decision-making settings and interval type-2 fuzzy sets (IT2FS) environment to deal with the uncertainties and variances in expert knowledge. To ensure the rationality and operability of indicator system construction, two novel cardinal and ordinal indices are proposed to quantify the degree of group consensus, and an interactive group consensus improvement algorithm is further developed to assist experts in reviewing their opinions to achieve acceptable group consensus. Finally, a case study of constructing a ship-equipment environmental suitability indicator system is examined to illustrate the feasibility and effectiveness of the proposed method, with the results indicating that the improved TISM method can deal with the uncertainties and variances in expert knowledge, promote rationality and operability in indicator system construction, and can be applied to numerous group decision-making problems.

关键词： Multi-criteria decision-making (MCDM) Indicator systems Total interpretive structural modeling (TISM) Interval type-2 fuzzy sets (IT2FS) Group consensus Ship design evaluation and selection

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Adaptive Optimization Tracking control for an Unmanned Aerial Vehicle with Disturbance Suppression

Adaptive Optimization Tracking Control for an Unmanned Aeria...

引用

2024 IEEE international conference on systems, Man, and Cybernetics, SMC 2024

作者： Yang, Meiying Zhu, Hai Xia, Xingyu Liu, Zhe Yao, Wen Ai Institute Shanghai Jiao Tong University MoE Key Lab of Artificial Intelligence Shanghai China Defense Innovation Institute Chinese Academy of Military Science Beijing China Intelligent Game and Decision Laboratory Beijing China College of Aerospace Science and Engineering National University of Defense Technology Changsha China

ISBN: (纸本)9781665410205

Aiming at the tracking control for an unmanned aerial vehicle (UAV) with uncertainty and external disturbances, an adaptive optimization control method is proposed based on the backstepping method. The model uncertainty in the UAV is estimated using neural networks. Moreover, a disturbance observer is designed to estimate and counteract the disturbance in real-time. In addition, reinforcement learning (RL) is used to solve optimal problems and overcome the difficult issues of the Hamilton-Jacobi-Bellman (HJB) equation. In the controller design, dynamic surfaces are employed to avoid complex derivation issues in the virtual controller and improve operating efficiency. Furthermore, the stability of the UAV system is proved by the Lyapunov theory. Finally, the effectiveness and superiority of the proposed method are verified through numerical simulations and real-world experiments. © 2024 IEEE.

关键词： Disturbance rejection

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NeuroPhysNet: A Novel Hybrid Neural Network Model for Enhanced Prediction and control of Cyber-Physical systems 19th

NeuroPhysNet: A Novel Hybrid Neural Network Model for Enhanc...

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19th international conference on Mathematical modeling and Simulation of systems, MODS 2024

作者： Dolhopolov, Serhii Honcharenko, Tetyana Chernyshev, Denys Kyiv National University of Construction and Architecture 31 Air Force Avenue Kyiv03037 Ukraine

ISBN: (纸本)9783031907340

This paper introduces NeuroPhysNet, a novel hybrid neural network architecture designed for enhanced prediction and control of cyber-physical systems (CPS). The increasing complexity and dynamic nature of CPS present significant challenges in modeling and control, often stretching the limits of traditional approaches. NeuroPhysNet addresses these challenges by seamlessly integrating deep learning techniques with physics-based modeling, offering a robust framework that leverages both data-driven insights and domain-specific knowledge. The architecture comprises three main components: a Deep Neural Network (DNN) module for capturing complex non-linear relationships, a Physical Model Integration (PMI) module for incorporating domain-specific equations, and an Adaptive Fusion (AF) module for dynamically combining outputs based on current system states. We evaluate NeuroPhysNet across multiple CPS domains, including smart grid energy management, autonomous vehicle control, and industrial process control. Results demonstrate significant improvements in prediction accuracy, physical consistency, and generalization capabilities compared to state-of-the-art baseline models. NeuroPhysNet achieves up to 15% improvement in mean squared error and a 20% increase in physical consistency scores across tested domains. This research contributes to the growing field of physics-informed machine learning, offering a versatile approach for enhancing the performance and reliability of complex cyber-physical systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Physical addresses

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Ungar - A C++ Framework for Real-Time Optimal control Using Template Metaprogramming

Ungar - A C++ Framework for Real-Time Optimal Control Using ...

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2023 IEEE/RSJ international conference on Intelligent Robots and systems, IROS 2023

作者： De Vincenti, Flavio Coros, Stelian Computational Robotics Lab ETH Zurich Switzerland

ISBN: (纸本)9781665491907

We present Ungar, an open-source library to aid the implementation of high-dimensional optimal control problems (OCPs). We adopt modern template metaprogramming techniques to enable the compile-time modeling of complex systems while retaining maximum runtime efficiency. Our framework provides syntactic sugar to allow for expressive formulations of a rich set of structured dynamical systems. While the core modules depend only on the header-only Eigen and *** libraries, we bundle our codebase with optional packages and custom wrappers for automatic differentiation, code generation, and nonlinear programming. Finally, we demonstrate the versatility of Ungar in various model predictive control applications, namely, four-legged locomotion and collaborative loco-manipulation with multiple one-armed quadruped robots. Ungar is available under the Apache License 2.0 at https://***/fdevinc/ungar. © 2023 IEEE.

关键词： Model predictive control

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Communications-Aware Robotics: Challenges and Opportunities

Communications-Aware Robotics: Challenges and Opportunities

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international conference on Unmanned Aircraft systems (ICUAS)

作者： Licea, Daniel Bonilla Silano, Giuseppe Ghogho, Mounir Saska, Martin Czech Tech Univ Fac Elect Engn Prague Czech Republic Int Univ Rabat Rabat Morocco

ISBN: (纸本)9798350310375

The use of Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs) has seen significant growth in the research community, industry, and society. Many of these agents are equipped with communication systems that are essential for completing certain tasks successfully. This has led to the emergence of a new interdisciplinary field at the intersection of robotics and communications, which has been further driven by the integration of UAVs into 5G and 6G communication networks. However, one of the main challenges in this research area is how many researchers tend to oversimplify either the robotics or the communications aspects, hindering the full potential of this new interdisciplinary field. In this paper, we present some of the necessary modeling tools for addressing these problems from both a robotics and communications perspective, using the UAV communications relay as an example.

关键词： Communications control Design Motion Planning Multi-Rotor UAVs Communications relay

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Research on Real-Time Tuning of PID Parameters Based on Fuzzy control 2

Research on Real-Time Tuning of PID Parameters Based on Fuzz...

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2nd IEEE international conference on Image Processing and Computer Applications, ICIPCA 2024

作者： Sun, Weixu Tianjin University of Commerce Tianjin China

ISBN: (纸本)9798350360240

A strategy for correcting PID parameters in real time for fuzzy control is proposed for the problem of the difficulty of correcting traditional PID control parameters. Exploring the effect of three PID control parameters on the control's quality was the initial step. Next, this paper imports the fuzzy control strategy and creates the fuzzy controller. PID parameters are adjusted in real time by fuzzy inference, fuzzy inference, knowledge base, non-fuzzy. Finally, an experimental comparison between traditional and fuzzy PID was made using Matlab simulation experiments. Test results showed that the fuzzy PID algorithm significantly reduces overclock response time compared to traditional PID algorithms, with a 20% response time reduction and a 10% overclock reduction. Fuzzy PID is a more ideal and efficient control method thanks to its excellent performance and adaptability to the control problems of complex systems. © 2024 IEEE.

关键词： Fuzzy control

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Neural MPC-based Decision-making Framework for Autonomous Driving in Multi-lane Roundabout 26

Neural MPC-based Decision-making Framework for Autonomous Dr...

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IEEE 26th international conference on Intelligent Transportation systems (ITSC)

作者： Mu, Yao Lan, Zhiqian Chen, Chen Liu, Chang Luo, Ping Li, Shengbo Eben Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Tsinghua Univ Sch Vehicle & Mobil Beijing Peoples R China Peking Univ Dept Adv Mfg & Robot Coll Engn Beijing Peoples R China

ISBN: (纸本)9798350399462

The multi-lane roundabout poses significant challenges for autonomous driving due to its complex road structure and traffic conditions. To address these challenges, this paper proposes a novel Neural Model Predictive control (NMPC)-based decision-making framework that integrates prediction, planning, and control for autonomous vehicles to navigate multi-lane roundabouts. The proposed NMPC framework learns a dynamical model, incorporating interaction data, to accurately predict the behavior of surrounding traffic participants. Multiple candidate static paths are then generated based on the road structure, and the decision-making problem is formulated as a series of parallel static path tracking control problems subject to safety constraints. The static path with minimal tracking cost is selected as the target reference path, and the tracking control is generated simultaneously. To enhance computational efficiency, NMPC utilizes a critic network and an actor network to approximate the tracking cost and the control policy, respectively. Experimental evaluation on a multi-lane roundabout simulator, based on a real roundabout in Beijing, demonstrates that the proposed method performs better in terms of driving safety and efficiency compared to several baseline algorithms across various traffic densities.

关键词： Model predictive control

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Energy Management and Vehicle Following Strategy of Hybrid Electric Vehicle Based on Deep Reinforcement Learning and Sliding Mode control

Energy Management and Vehicle Following Strategy of Hybrid E...

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2024 international Annual conference on complex systems and Intelligent Science, CSIS-IAC 2024

作者： Zhao, Bingxi Wang, Hui Li, Xiaofeng Mu, Chaoxu Anhui University Anhui Provincial Key Laboratory of Security Artificial Intelligence Hefei China

ISBN: (纸本)9798331504755

Recently, the hybrid electric vehicle is more and more popular due to its advantage on the energy solution. Hence, the research of further optimizing the energy management of hybrid electric vehicle is crucial. Besides, the AI -assisted driving technologies are widely applied on such vehicles, which yields an important problem, that is how to manage the energy consumption when applying such technologies? As a typical AI-assisted driving situation, vehicle following needs more inves-tigation. Therefore, this paper proposes a method combining Multi-agent Deep Deterministic Policy Gradient (MADDPG) and sliding mode control (SMC) to deal with hybrid electric vehicle energy management and vehicle following problems. This method optimizes sliding mode control parameters through the exploration of MADDPG and takes into account the stability of SMC. The experimental results show that this method signifi-cantly achieves lower speed following error, more stable relative safety distance control and higher safety compared to traditional MADDPG algorithm, which implies less speed changes, higher passenger comfort under the constraints like safety and energy management. Meanwhile, less speed changes further contribute to less energy consumption. © 2024 IEEE.

关键词： Deep reinforcement learning

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Digitization of Emergency Monitoring Processes and Data Mining 5

Digitization of Emergency Monitoring Processes and Data Mini...

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5th international conference on control systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Goryunova, V.V. Goryunova, T.I. State Fire Academy of Emercom of Russia Moscow Russia V. A. Trapeznikov Institute of Control Sciences of the Russian Moscow Russia

ISBN: (纸本)9798350309126

The introduction of digitalization contributes to solving the priority task of the Russian Ministry of Emergency Situations - the transition from a system of responding to emergencies to their prevention. The purpose of the research presented in the article concerns the design of intelligent information systems to solve problems of organizational management of emergency monitoring processes in situation centers at the municipal level. In the course of the work, data mining methods were studied from the point of view of the possibility of using each to analyze data from the emergency monitoring process. Based on the results, the precedent method was chosen. The authors proposed a model of an ontological resource that includes concepts related to all properties of the presentation of information about emergencies. © 2023 IEEE.

关键词： Data mining

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