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Optimal synchronization control formulti-agent systems with input saturation:a nonzero-sum game

Frontiers of Information Technology & Electronic Engineering 2022年第7期23卷 1010-1019页

作者： Hongyang LI Qinglai WEI School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

This paper presents a novel optimal synchronization control method for multi-agent systems with input *** multi-agent game theory is introduced to transform the optimal synchronization control problem into a multi-agent nonzero-sum ***,the Nash equilibrium can be achieved by solving the coupled Hamilton–Jacobi–Bellman(HJB)equations with nonquadratic input energy terms.A novel off-policy reinforcement learning method is presented to obtain the Nash equilibrium solution without the system models,and the critic neural networks(NNs)and actor NNs are introduced to implement the presented *** analysis is provided,which shows that the iterative control laws converge to the Nash *** results show the good performance of the presented method.

关键词： Optimal synchronization control Multi-agent systems Nonzero-sum game Adaptive dynamic programming Input saturation Off-policy reinforcement learning Policy iteration

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Fuzzy PID controller Optimized by Improved Gravitational Search Algorithm for Load Frequency control in Multi-area Power System

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2022年第1期49卷 125-139页

作者： Chen, Gonggui Qin, Feng Long, Hongyu Zeng, Xianjun Kang, Peng Zhang, Jinming Professor of Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Graduate student of Chongqing University of Posts and Telecommunications Chongqing400065 China Professor level senior engineer of Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Senior engineer of State Grid Chongqing Electric Power Company Chongqing400015 China Senior engineer of Economic and Technology Research Institute State Grid Chongqing Electric Power Company Chongqing401120 China

In this paper, an objective function considering performance index and an improved gravitational search algorithm (IGSA) are proposed to optimize the parameters of fuzzy PID (FPID) controller. IGSA is obtained by combining elite strategies and the mining capability of PSO algorithm. The IGSA FPID method which integrates IGSA and FPID controller is tested in a typical two-area non-reheat system, and system responses reflect the advantages of proposed objective function and IGSA. Additionally, the proposed IGSA FPID method still has excellent effects even on the two-area multi-source system with thermal power, hydropower and gas turbines. Meanwhile, the effect of high voltage direct current (HVDC) links in suppressing fluctuations is verified. Due to the popularity of wind power, a novel three-area interconnected power system with nonlinearity connected wind turbine (WT) is designed. Under the control of IGSA FPID, the good stability and dynamic performance of mentioned three-area system are verified. Therefore, FPID controller optimized by IGSA has excellent control effects, stability and universal applicability on the different power systems with multiple area and sources. © 2022. All Rights Reserved.

关键词： Wind turbines

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A 3D Virtual Try-On Method with Global-Local Alignment and Diffusion Model

A 3D Virtual Try-On Method with Global-Local Alignment and D...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shougan Pan Zhengwentai Sun Chenxing Wang Junkai Zhang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China The Hong Kong Polytechnic University Institute of Automation Chinese Academy of Sciences

3D virtual try-on has recently received more attention due to its great practical and commercial value. However, there remains the problems that the garment cannot accurately correspond to a human body by geometric transformation and abnormal textures may be produced in the synthesis result. To address these issues, a 3D virtual try-on method with global-local alignment and diffusion model is proposed. The global-local alignment module is designed for more accurate garment warping, combined with the guidance of an "after-try-on" semantic map alignment. Then, a diffusion model is introduced to design a try-on synthesizer that can not only avoid producing abnormal textures but also enhance the quality of textures produced in edge regions. Experiments on existing datasets show that our method outperforms the state-of-the-art methods. Code is available at https://***/Breaveh/VTON-GD.

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Frequency comb in a parametrically modulated micro-resonator

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Acta Mechanica Sinica 2022年第11期38卷 79-88页

作者： Xuefeng Wang Qiqi Yang Zhan Shi Ronghua Huan Weiqiu Zhu Xingjian Jing Zichen Deng Xueyong Wei Department of Engineering Mechanics MIIT Key Laboratory of Dynamics and Control of Complex SystemsNorthwestern Polytechnical UniversityXi’an710072China Department of Mechanics Key Laboratory of Soft Machines and Smart Devices of Zhejiang ProvinceZhejiang UniversityHangzhou310027China State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an710049China Department of Mechanical Engineering City University of Hong KongHong Kong999077China

In this paper,we report the frequency comb response experimentally and analytically in a rhombic micro-resonator with parametrical *** the electrostatically actuated rhombic micro-resonator is modulated axially by a low-frequency periodic excitation,a comb-like vibration response with few equidistant positioned fingers in the frequency domain is *** finger spacing of frequency comb response is exactly consistent with modulation frequency and the number and amplitude of the fingers can be tuned by modulation strength.A mixed frequency comb with extra comb fingers is further generated when the resonator is modulated simultaneously by two different low-frequency excitation *** adjusting the relation of the two modulation frequencies,unequal spacing frequency combs are achieved for the first time,which leads to a more flexible tunability of the comb spacing for different *** analysis based on the dynamic model well explains the corresponding observations.

关键词： Micro-resonator Nonlinear dynamics Vibration Parametrical modulation Frequency comb

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Identification and Prediction of Microvascular Invasion in Hepatocellular Carcinoma Based on Multiple Sequence Fusion Images

Identification and Prediction of Microvascular Invasion in H...

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Chinese control Conference (CCC)

作者： Mingguang Lu Yuan Zhu School of Automation China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Hepatocellular carcinoma (HCC) is one of the most difficult diseases to be treated fundamentally in the medical field in today’s world, and the recurrence rate of HCC has been increasing year by year in recent years. The study on the identification and prediction of microvascular invasion phenomenon (MVI) in hepatocellular carcinoma is beneficial to the postoperative prevention of hepatocellular carcinoma patients, which can greatly improve the survival probability of patients after surgery. In this study, a new MVI prediction method (MSF-GWO-GPR) was proposed, which combines the multi-sequence image features of imaging histology, sifts out the unimportant features through the T-test method and the dimensionality reduction of Lasso regression, and establishes the multi-sequence Gaussian process regression (GPR) prediction model for data fusion, and combined with the Gray Wolf optimization (GWO) algorithm to design a suitable optimization objective function to optimize the hyper-parameters in the GPR, in order to get better prediction results. Compared with the existing methods, the data from different sequences of MRI images are selected for fusion in this study, which makes the feature data richer and more complete, and the model applicability is better; moreover, by optimizing the hyperparameters in the model through the GWO, the model can be made more accurate, reduce the risk of misidentified prediction, and improve the accuracy rate. The experimental results show that MSF-GWO-GPR outperforms widely used machine learning methods in terms of accuracy, F1 score, precision, recall and AUC metrics. This may provide a new idea for the identification and prediction of MVI in hepatocellular carcinoma.

关键词： Liver cancer Accuracy Magnetic resonance imaging Prevention and mitigation Surgery Predictive models Feature extraction

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An Efficient Learning control Framework with Sim-to-Real for String-Type Artificial Muscle-Driven Robotic systems

arXiv

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arXiv 2024年

作者： Tao, Jiyue Zhang, Yunsong Rajendran, Sunil Kumar Zhang, Feitian The Robotics and Control Laboratory Department of Advanced Manufacturing and Robotics College of Engineering the State Key Laboratory of Turbulence and Complex Systems Peking University Beijing100871 China The BSS Technologies Inc. Takoma ParkMD20912 United States

Robotic systems driven by artificial muscles present unique challenges due to the nonlinear dynamics of actuators and the complex designs of mechanical structures. Traditional model-based controllers often struggle to achieve desired control performance in such systems. Deep reinforcement learning (DRL), a trending machine learning technique widely adopted in robot control, offers a promising alternative. However, integrating DRL into these robotic systems faces significant challenges, including the requirement for large amounts of training data and the inevitable sim-to-real gap when deployed to real-world robots. This paper proposes an efficient reinforcement learning control framework with sim-to-real transfer to address these challenges. Bootstrap and augmentation enhancements are designed to improve the data efficiency of baseline DRL algorithms, while a sim-to-real transfer technique, namely randomization of muscle dynamics, is adopted to bridge the gap between simulation and real-world deployment. Extensive experiments and ablation studies are conducted utilizing two string-type artificial muscle-driven robotic systems including a two degree-of-freedom robotic eye and a parallel robotic wrist, the results of which demonstrate the effectiveness of the proposed learning control strategy. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Task-Centered Heterogeneous Multi-Robot Cooperative Task Allocation and Planning: An Welding Case Study

SSRN

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SSRN 2024年

作者： Liu, Wenbo Kuang, Zhian Zhang, Yongcong Zhou, Bo Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Shanghai Friendess Electronic Technology Shanghai201100 China

In this article, the complicated task assignment, scheduling and planning of heterogeneous multi-robot welding process are studied. Firstly, for large-scaled tasks that involve heterogeneous multi-robot task allocation under different internal and external constraints, the traditional multi-robot task allocation (MRTA) framework is extended to a novel and unified heterogeneous multi-robot task allocation (H MRTA)***,robotsofdifferentconfigurations (including manipulators, positioners, gantries) are treated as unified robots. Secondly, taking into account constraints such as reachability, collision avoidance, kinematic and dynamic process constraints, the optimization model based on H-MRTA framework is established. The optimization objectives are formulated by combining the total execution time and load balance between robots. Then, a hierarchical optimization algorithm(TCO-HMRTA) is proposed to solve the H-MRTA problem with decoupled two-layer optimization sub-problems : task space segmentation subproblem and multi-robot path planning subproblem. For the task space segmentation subproblem, a task-centered optimization model is established, which aims to balance the workload among robots, considering the competition and cooperation between robots. For the multi-robot path planning problem, multiple process constraints are considered and the total working time is minimized as the objective function. Finally, The effectiveness of the optimization algorithm is verified by a case study on the welding task of a large plate element in a ship hull. Compared to two other state-of-the-art algorithms, TCO-HMRTA can save more than 50% of the waiting time and 10%-20% of the execution time, which demonstrates the effectiveness and feasibility of the hierarchical optimization-based task allocation algorithm for complicated heterogeneous multi-robots. © 2024, The Authors. All rights reserved.

关键词： Industrial robots

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Zonotope-based Symbolic controller Synthesis for Linear Temporal Logic Specifications

arXiv

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arXiv 2024年

作者： Ren, Wei Jungers, Raphaël M. Dimarogonas, Dimos V. Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China ICTEAM institute UCLouvain Louvain-la-Neuve1348 Belgium Division of Decision and Control Systems EECS KTH Royal Institute of Technology StockholmSE-10044 Sweden

This paper studies the controller synthesis problem for nonlinear control systems under linear temporal logic (LTL) specifications using zonotope techniques. A local-to-global control strategy is proposed for the desired specification expressed as an LTL formula. First, a novel approach is developed to divide the state space into finite zonotopes and constrained zonotopes, which are called cells and allowed to intersect with the neighbor cells. Second, from the intersection relation, a graph among all cells is generated to verify the realization of the accepting path for the LTL formula. The realization verification determines if there is a need for the control design, and also results in finite local LTL formulas. Third, once the accepting path is realized, a novel abstraction-based method is derived for the controller design. In particular, we only focus on the cells from the realization verification and approximate each cell thanks to properties of zonotopes. Based on local symbolic models and local LTL formulas, an iterative synthesis algorithm is proposed to design all local abstract controllers, whose existence and combination establish the global controller for the LTL formula. Finally, the proposed framework is illustrated via a path planning problem of mobile robots. Copyright © 2024, The Authors. All rights reserved.

关键词： Cells

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An Ensemble Rule Extraction Algorithm Based on Interpretable Greedy Trees for Detecting Malicious Traffic*

An Ensemble Rule Extraction Algorithm Based on Interpretable...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Qian Ku Wu Tiejun Zhang Ya School of Automation Southeast University Nanjing Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing China School of Cyber Science and Engineering Southeast University Nanjing China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper studies the detection and identification problem of malicious network traffic and proposes a rule extraction algorithm based on interpretable models. The algorithm utilizes interpretable greedy trees as the foundational model and extends its applicability to handle multi-classification problems, thereby enhancing interpretability and detection accuracy. This methodology furnishes a more dependable and secure framework for discerning attack categories within the domain of network security. The experiment results show that the proposed algorithm achieves better balance between interpretability and identification precision.

关键词： Accuracy Automation Telecommunication traffic Artificial neural networks Network security Classification algorithms complexity theory Computer security Robots

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An Error Correcting Output Code Algorithm Based on Hierarchical Clustering for Lithology Identification

An Error Correcting Output Code Algorithm Based on Hierarchi...

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Chinese control Conference (CCC)

作者： Ao Li Xi Chen School of Rail Transit Hunan University of Technology Zhuzhou China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Lithology identification serves as a crucial foundation for the precise exploration and safe exploitation of geological resources. However, challenges arise from the inherent imbalance and overlap present in logging data, making the accurate identification of lithology a complex task. Addressing these challenges effectively, this paper introduces a novel algorithm, the Error Correcting Output Code algorithm based on Hierarchical Clustering(HC-ECOC). The proposed algorithm initially formulates a coding matrix using distance and overlap measures between class clusters. Subsequently, it extends the length of the coding matrix by considering both the accuracy of the integrated classifier and the diversity among base classifiers. To evaluate the efficacy of the proposed method, comparisons were conducted with alternative algorithms using UCI datasets and an authentic lithology dataset. The results unequivocally demonstrate the superior performance of our algorithm.

关键词： Codes Accuracy Geology Clustering algorithms Binary trees Encoding Classification algorithms

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