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Distributed Optimization and Scaling Design for Solving Sylvester Equations

Journal of Systems Science & Complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

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A Recursive System Identification With Non-Uniform Temporal Feedback Under Coprime Collaborative Sensing

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ASME Letters in Dynamic Systems and control 2023年第2期3卷 021010页

作者： Ouyang, Jinhua Chen, Xu Mechatronics Automation and Control Systems Laboratory Department of Mechanical Engineering University of Washington SeattleWA98195 United States Mechatronics Automation and Control Systems Laboratory Department of Mechanical Engineering University of Washington SeattleWA98195 United States

We present a system identification method based on recursive least-squares (RLS) and coprime collaborative sensing, which can recover system dynamics from non-uniform temporal data. Focusing on systems with fast input sampling and slow output sampling, we use a polynomial transformation to reparameterize the system model and create an auxiliary model that can be identified from the non-uniform data. We show the identifiability of the auxiliary model using a Diophantine equation approach. Numerical examples demonstrate successful system reconstruction and the ability to capture fast system response with limited temporal feedback. Copyright © 2023 by ASME.

关键词： Feedback

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Data-driven cooperative optimal output regulation for linear discrete-time multi-agent systems by online distributed adaptive internal model approach

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Science China(Information Sciences) 2023年第7期66卷 30-45页

作者： Kedi XIE Yi JIANG Xiao YU Weiyao LAN Department of Automation Xiamen University Department of Electrical Engineering City University of Hong Kong Key Laboratory of Control and Navigation(Xiamen University) Fujian Province University

In this study, a data-driven learning algorithm was developed to estimate the optimal distributed cooperative control policy, which solves the cooperative optimal output regulation problem for linear discretetime multi-agent systems. Notably, the dynamics of all the agent systems and exo-system is completely unknown. By combining adaptive dynamic programming with an internal model, a model-free off-policy learning method is proposed to estimate the optimal control gain and the distributed adaptive internal model by only accessing the measurable data of multi-agent systems. Moreover, different from the traditional cooperative adaptive controller design method, a distributed internal model is approximated online. Convergence and stability analyses show that the estimate controller generated by the proposed data-driven learning algorithm converges to the optimal distributed controller. Finally, simulation results verify the effectiveness of the proposed method.

关键词： adaptive dynamic programming cooperative control distributed adaptive internal model multi-agent systems optimal output regulation

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Self-Tuning Neural Network controller Based on Fuzzy Logic for Multiple Positions Tracking of a Pneumatic Driven Soft Endoscope Actuator 10

Self-Tuning Neural Network Controller Based on Fuzzy Logic f...

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10th International Conference on automation, Robotics, and Applications, ICARA 2024

作者： Acosta, Renzo Tafur, Julio Canahuire, Ruth Pontificia Universidad Catolica del Peru Control and Automation Engineering Master Degree Program Enginnering Department Lima Peru Universidad de Ingenieria y Tecnologia - UTEC Department of Electrical and Mechatronics Engineering Lima Peru

ISBN: (纸本)9798350394245

This paper presents the dynamic modelling and end effector position control of a soft endoscope. Soft endoscope system under study consists mainly of a pneumatic driven soft actuator (PDSA) with four independently chambers. Recurrent neural network (RNN) and dynamic back propagation (DBP) training algorithm are used to obtain PDSA dynamic model. PDSA position controller is based on a feedforward neural network (FNN) and it is trained using PDSA closed loop system (CLS) and DBP training algorithm. CLS stability analysis concludes that it is not possible control PDSA end effector position using one position controller for different end effector initial and desired positions. Fuzzy logic methodology is used to integrate several positions controllers in a one controller valid for all operation range. The controller implementation and close loop system simulation are performed in MATLAB for different end effector desired position to validate system performance in all range of operation. © 2024 IEEE.

关键词： Pneumatics

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State Transition Modeling Method for Optimal Dispatching for Integrated Energy System Based on Cyber-Physical System

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Journal of Modern Power Systems and Clean Energy 2024年第5期12卷 1617-1630页

作者： Yi Yang Peng Zhang Can Wang Zhuoli Zhao Loi Lei Lai the Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station College of Electrical Engineering and New EnergyChina Three Gorges UniversityYichangChina the Department of Electrical Engineering School of AutomationGuangdong University of TechnologyGuangzhouChina

The traditional energy hub based model has difficulties in clearly describing the state transition and transition conditions of the energy unit in the integrated energy system(IES).Therefore,this study proposes a state transition modeling method for an IES based on a cyber-physical system(CPS)to optimize the state transition of energy unit in the *** method uses the physical,integration,and optimization layers as a three-layer modeling *** physical layer is used to describe the physical models of energy units in the *** the integration layer,the information flow is integrated into the physical model of energy unit in the IES to establish the state transition model,and the transition conditions between different states of the energy unit are *** optimization layer aims to minimize the operating cost of the IES and enables the operating state of energy units to be transferred to the target *** simulations show that,compared with the traditional modeling method,the state transition modeling method based on CPS achieves the observability of the operating state of the energy unit and its state transition in the dispatching cycle,which obtains an optimal state of the energy unit and further reduces the system operating costs.

关键词： Integrated energy system(IES) cyber-physical system(CPS) state transition modeling optimal dispatching

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Proton Exchange Membrane Fuel Cell Thermal System Modeling and control 10

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

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10th International Conference on Electrical and Electronics engineering, ICEEE 2023

作者： Özdemir, Tuna Han Yasar, Claudia Fernanda Yildiz Technical University Avl Research and Engineering Department of Control and Automation Engineering Istanbul Turkey Yildiz Technical University Department of Control and Automation Engineering Istanbul Turkey

ISBN: (纸本)9798350304299

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. © 2023 IEEE.

关键词： Three term control systems

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Size Matters: Exploring the Impact of Scaling on Quadruped Robot Dynamics 25th

Size Matters: Exploring the Impact of Scaling on Quadruped R...

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25th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2024

作者： Rahvar, Faraz Yilmaz, Abdurrahman Department of Mechatronics Engineering Istanbul Technical University Istanbul Turkey Department of Control and Automation Engineering Istanbul Technical University Istanbul Turkey

ISBN: (纸本)9783031720611

Quadruped robots are indispensable for specialized tasks, particularly in disaster scenarios like earthquakes, where their mobility surpasses that of fixed robots. However, altering their dimensions significantly impacts their mechanical requirements and control systems. This study investigates and compares the principal mechanical parameters affecting the control systems of quadruped robots during scaling, aiming to understand how scalability influences their design across different sizes. Using a standard quasi-direct driven commercial quadruped robot1(Unitree A 1) model featuring dual coaxial motor design and serial link architecture actuators, simulations are conducted at four different sizes, each expanding the robot size by 30%. These simulations analyze static and dynamic forces as the robot walks on a flat surface at a constant speed. To fortify our findings, simulations employ three trajectory scenarios, in each scenario, four robots are scaled in length, increasing by a coefficient of 0.3 from robot 1 to robot 4. The first and second scenarios feature different trajectory lengths, while the third scenario increases the trajectory height while maintaining the length of the second scenario. Specifically, we examine the required torque, energy consumption of the robot motors, reaction forces between the robot feet and terrain, and the mechanical cost of transport. These outcomes encompass critical components of the robot from a mechanical analysis perspective, including joints, providing valuable references for various actuator architecture designs. Our findings reveal a logical pattern in the increase of torques, power consumptions, and reaction forces as the robot scales. These insights lay the groundwork for developing a scalable control architecture for legged robots. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Multipurpose robots

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A Feature Weighted Mixed Naive Bayes Model for Monitoring Anomalies in the Fan System of a Thermal Power Plant

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 719-727页

作者： Min Wang Li Sheng Donghua Zhou Maoyin Chen IEEE the Department of Automation Tsinghua University the College of Control Science and Engineering China University of Petroleum(East China) the College of Electrical Engineering and Automation Shandong University of Science and Technology

With the increasing intelligence and integration,a great number of two-valued variables(generally stored in the form of 0 or 1)often exist in large-scale industrial ***,these variables cannot be effectively handled by traditional monitoring methods such as linear discriminant analysis(LDA),principal component analysis(PCA)and partial least square(PLS)***,a mixed hidden naive Bayesian model(MHNBM)is developed for the first time to utilize both two-valued and continuous variables for abnormality *** the MHNBM is effective,it still has some shortcomings that need to be *** the MHNBM,the variables with greater correlation to other variables have greater weights,which can not guarantee greater weights are assigned to the more discriminating *** addition,the conditional P(x j|x j′,y=k)probability must be computed based on historical *** the training data is scarce,the conditional probability between continuous variables tends to be uniformly distributed,which affects the performance of *** a novel feature weighted mixed naive Bayes model(FWMNBM)is developed to overcome the above *** the FWMNBM,the variables that are more correlated to the class have greater weights,which makes the more discriminating variables contribute more to the *** the same time,FWMNBM does not have to calculate the conditional probability between variables,thus it is less restricted by the number of training data *** with the MHNBM,the FWMNBM has better performance,and its effectiveness is validated through numerical cases of a simulation example and a practical case of the Zhoushan thermal power plant(ZTPP),China.

关键词： Abnormality monitoring continuous variables feature weighted mixed naive Bayes model(FWMNBM) two-valued variables thermal power plant

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XSpace: Self-learning platform for implementation of digital control algorithms 14

XSpace: Self-learning platform for implementation of digital...

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14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Caceres, Pablo Cardenas Cieza Huane, Leslie Y. Horna Vilcahuaman, Ingrid M. Pauyac Estrada, Claudia R. Casano, Celso De-La-Cruz Tafur Sotelo, Julio C. Pontificia Universidad Catolica Del Peru Department of Engineering Electronics Section Lima Peru Degree Program Pontificia Universidad Catolica Del Peru Department of Engineering Control and Automation Master Engineering Lima Peru

ISBN: (纸本)9798350399431

In the electronic engineering undergraduate program, Peruvian universities offer different theoretical courses of Automatic control that do not present enough practical approach to the algorithms that are studied during the progress of these courses;however, the approach to implementation is very important to achieve good performance in the industry and researching. In this work is presented XSpace, an innovative and friendly platform which consists of a robust hardware that allows the student to take it home;this way, the student is given the opportunity to implement digital control algorithms learned in the theoretical classes. The effectiveness of this platform is shown using a proposed methodology which evidences greater interest, efficiency and efficacy in students at the Automatic control area. This project was implemented in the 'control Systems' course at Pontificia Universidad Catolica del Peru (PUCP) from 2020 to 2022. Results are presented through a student survey and a history of average grades during the academic periods the platform was employed. © 2023 IEEE.

关键词： Students

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Sliding mode active disturbance rejection control for uncalibrated visual servoing

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International Journal of Systems, control and Communications 2025年第2期16卷 133-151页

作者： Pu, Cuiping Wu, Yi Ren, Jie Ran, Chenyang College of Mechanical and Electrical Engineering Kunming University Kunming China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Department of Automation Shanghai Jiao Tong University Shanghai China

A sliding mode control algorithm based on a linear extended state observer is proposed to address the multi-source uncertainty of uncalibrated visual servoing in robotic arms. Uncertainty, nonlinearity, coupling, external disturbances, etc. are considered as total disturbances. The linear expansion state observer is designed to observe the total disturbance and compensate for it. This enhances the system’s anti-interference ability. The outer loop adopts sliding mode control law as state feedback. It suppresses the observation errors of the observer and ensures the stability of the system. Sliding mode control based on linear extended observer does not depend on specific tasks and system configurations. It provides a unified design framework for solving the problem of uncalibrated visual servoing. Through numerical simulations of three different disturbance cases, it was compared with PI linear extended state observer and linear active disturbance rejection to verify its good dynamic performance and disturbance rejection performance. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Robotic arms

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