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On-line and real-time controller tuning architecture based on Youla-Kucera controller parameterization

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND control 2024年

作者： Xie, Wei Wei, Haixiang Li, Weisheng Li, Lili Zhang, Langwen South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China South China Univ Technol Guangdong Prov Key Lab Tech & Equipment Macromol A Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou Peoples R China South China Univ Technol Guangdong Engn Technol Res Ctr Unmanned Aerial Veh Guangzhou Peoples R China

This paper presents an on-line and real-time controller tuning architecture based on Youla-Kucera controller parameterization. First, a coarse controller is designed to satisfy nominal performance of closed-loop system. Second, Youla parameter is used to construct an on-line and real-time fine tuning mechanism including a group of controller candidates under arbitrary switching strategy. The mechanism can adjust the control performance on-line to achieve the balance between dynamic and steady-state performance without resulting in any closed-loop stability problems.

关键词： controller parameterization stability of linear systems linear systems switched systems robust control

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Twinning quality sensors in wastewater treatment process via optimized echo state network-based soft sensors

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APPLIED SOFT COMPUTING 2024年 164卷

作者： Fang, Gang Liu, Yiqi South China Univ Technol Sch Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou 510640 Peoples R China South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Sch Automat Sci & Engn Guangzhou 510640 Peoples R China

The presence of a large amount of quality-related but hard-to-measure variables usually makes effective monitoring of industrial processes difficult, and even impossible. Soft computing techniques and digital twins can revolutionize standard approaches to solve this issue, even though industrial data are frustrated by nonlinearity, disturbances, and dynamic behaviors. In this light, this paper proposes a data-driven soft sensor with the help of the Fourier amplitude sensitivity test (FAST) and improved probabilistic regularized echo state network (IPRESN), then to twin the quality hardware sensors. Within this framework, the initial step is to rely on the FAST method to measure the collaborated importance of multiple process variables with respect to each quality variable. This quantification facilitates the selection of auxiliary variables for the training of IPRESN. Furthermore, a probabilistic regularization method is learned to improve the robust performance of the echo state network (ESN) by re-designing a new objective function to minimize the mean and variance of the modeling error. Additionally, the whale optimization algorithm (WOA) is improved and then used to optimize the critical hyperparameters of ESN, thus mitigating the risks associated with suboptimal hyperparameter selection. The effectiveness of the proposed method is verified through a Benchmark Simulation Model 2 (BSM2) and a full-scale wastewater treatment plant data set. The findings show the potential of the proposed method in facilitating digital twin implementations for hardware sensors.

关键词： Soft sensor Improved echo state network Fourier amplitude sensitivity test Wastewater treatment Quality prediction

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Formation control of Discrete-time Multi-agent systems Based on Distributed Filter Observer

Formation Control of Discrete-time Multi-agent Systems Based...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Huanli Gao Wei Li Ming Qiu He Cai School of Automation Science and Engineering South China University of Technology Guangzhou China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou China Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle Systems Guangzhou China Department of Shanhaiguan District People’s Armed Forces Qinhuangdao City China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper explores the formation control of discrete multi-agent systems under external communication disturbance. Firstly, leveraging the modified algebraic Riccati equation, a disturbed output based discrete filter observer is proposed to minimize network information exchange and mitigate disturbance effects. Then, the formation control issue is transformed into a cooperative output regulation problem, which a certainty equivalent state feedback controller solves. The effectiveness of the control strategy is demonstrated by numerical simulations.

关键词： State feedback Riccati equations Observers Information filters Numerical simulation Filtering theory Formation control

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Adaptive dynamic programming enhanced admittance control for robots with environment interaction and actuator saturation

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INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS 2021年第1期5卷 89-100页

作者： Zhan, Hong Huang, Dianye Yang, Chenguang South China Univ Technol Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou 510640 Peoples R China Tech Univ Munich Dept Informat D-85748 Munich Germany Univ West England Bristol Robot Lab Bristol BS16 1QY Avon England

This paper focuses on the optimal tracking control problem for robot systems with environment interaction and actuator saturation. A control scheme combined with admittance adaptation and adaptive dynamic programming (ADP) is developed. The unknown environment is modelled as a linear system and admittance controller is derived to achieve compliant behaviour of the robot. In the ADP framework, the cost function is defined with non-quadratic form and the critic network is designed with radial basis function neural network which introduces to obtain an approximate optimal control of the Hamilton-Jacobi-Bellman equation, which guarantees the optimal trajectory tracking. The system stability is analysed by Lyapunov theorem and simulations demonstrate the effectiveness of the proposed strategy.

关键词： Adaptive dynamic programming Admittance control Robot-environment interaction Actuator saturation Optimal control Neural network

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Probabilistic fatigue life prediction using multi-layer perceptron with maximum

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INTERNATIONAL JOURNAL OF FATIGUE 2024年 187卷

作者： Zhu, Yifeng Hu, Zican Luo, Jiaxiang Song, Peilong China Ship Sci Res Ctr Wuxi Peoples R China Natl Key Lab Ship Struct Safety Wuxi Peoples R China South China Univ Technol Sch Automat Sci & Engn Guangzhou Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou Peoples R China Minist Educ Precis Elect Mfg Equipment Engn Ctr Guangzhou Peoples R China

In the structural fatigue fields, such as aerospace, maritime, and civil engineering, the accurate construction of the Probability -Stress -Life (P -S -N) curve is crucial for preventing unexpected structural failures and is fundamental to the engineering design process. Conventional methods usually assume that the fatigue life distribution follows a normal or weibull distribution, which overlooks the differences of life distribution at different stress levels and introduces subjective errors. To address this issue, this paper proposes a new approach based a multi -layer perceptron model with maximum entropy algorithm (MPME) for probabilistic fatigue life prediction. During the derivation of life probability distribution function in this approach, the type not require any pre -assumption, thus effectively avoiding the introduction of subjective errors. Specifically, the dispersed information of fatigue life is quantified as various life distribution statistical features such as mean, variance, skewness, and kurtosis. Next, learn the continuous functional relationship between stress and these features using a multi -layer perceptron (MLP). Finally, the target probability distribution is derived using the maximum entropy algorithm, with the predicted distribution features obtained from the MLP serving as constraints for it. In addition, to ensure the consistency between the prediction of MLP and physical laws, we encode physical knowledge into the network loss to guide the updating of network parameters. Experimental results of two different material fatigue data demonstrate that, compared to traditional deterministic modelbased methods and machine learning methods, the MPME in this paper can more accurately predict the probabilistic fatigue life.

关键词： Multi-layer perceptron Probability fatigue life prediction Fatigue life distribution P-S-N curve

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Working Properties of Compliant Actuators Based on Magnetorheological Elastomer 6

Working Properties of Compliant Actuators Based on Magnetorh...

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6th IEEE International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Li, Chongbin Feng, Ying Yoong, Hou-Pin Liang, Mingwei Chen, Jiapeng South China Univ Technol Sch Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Peoples R China Univ Malaysia Sabah Fac Engn Kota Kinabalu 88400 Sabah Malaysia

ISBN: (纸本)9780738133645

Novel designs and control methods have been addressed in areas from sensing technology to robotics with the development of smart materials and compliant actuating components, which are showing some good actuating performances compared with the traditional actuating components utilizing air valves, hydraulic pumps and electro-motors. In this paper, the working properties of a class of compliant actuators utilizing liquid alloy conductors, and magnetorheological elastomers (MREs) are discussed. The magnetorheological (MR) effect in the complaint MRE actuators are analyzed so the working properties between input (voltage)and the output (displacement) can be modeled analytically.

关键词： Coils Actuators Force Muscles Robot sensing systems Valves Sensors

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Design and Implementation of a Group control Communication System for Intelligent Rubber Tapping Robots

Design and Implementation of a Group Control Communication S...

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第42届中国控制会议

作者： Fuchun Liu Dong Jiang Xiaoyang Chen Xujian Chen Shengfeng Huang School of Automation Science and Engineering South China University of Technology Key Laboratory of Autonomous Systems and Networked ControlMinistry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong Beijing Normal University Hong Kong Baptist United International College

With the development and promotion of electric rubber tapping equipment,China has gradually mechanized rubber tapping,but the degree of automation could be *** paper designs an intelligent rubber tapping remote monitoring system based on Internet of Things(IoT) technology that is applied to single-motor driven rubber tapping robots and uploads the status data of robots in the rubber plantation to the cloud database for storage,data analysis,and display in the backend management system in order to realize the intelligent and digital upgrade of rubber tapping *** can achieve remote group control of the robots in the rubber plantation at the same time using a cloud-based human-machine *** system consists of a terminal electronic control subsystem,a communication subsystem,and a cloud-based backend management *** system uses LoRa RF technology and Narrowband IoT(NBIoT) technology to design a star-shaped network to connect the robots to the cloud for unified management and provide data support for later tapping decisions.

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Practical Prescribed Time control Framework for Decentralized Robust Steering of Connected Automated Vehicles Under Deception Attacks

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2025年

作者： Qi, Xuelei Li, Chen Ni, Wei Sheng, Quan Z. Ma, Hongjun Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Macquarie Univ Sch Comp Sydney NSW 2109 Australia Univ Technol Sydney Fac Engn & Informat Technol Ultimo NSW 2007 Australia CSIRO Data61 Marsfield NSW 2122 Australia South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Sch Automat Sci & Engn Minist Educ Guangzhou 510641 Peoples R China South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou 510641 Peoples R China

Effective vehicle control contributes to the safety and efficiency of connected automated vehicles (CAVs). Many existing solutions do not consider the maximum effective communication distance and bearing angle constraints between vehicles. This article proposes a novel prescribed performance method to handle distance and angle constraints to achieve vehicle stability under deception attacks. A key aspect is that the above two constraints are successfully transformed from inequality-constrained form to equivalent equation unconstrained form through introducing error transformations, and we prove that the errors of distance and angle are strictly contained within the boundary of the performance function. Another key aspect is to use adaptive bias radial basis function neural network (RBFNN) to approximate unknown nonlinear functions and deception attacks in the system and integrate the approximated results into recursive construction to design adaptive laws and multilane merging control laws. Analysis shows that all signals in a closed-loop system are practical prescribed time stable. Simulations validate that our control method has a faster convergence time than the existing advanced two-dimensional (2-D) vehicle approach and can adaptively adjust convergence to predefined sets under different attack intensities.

关键词： Merging Vehicle dynamics Safety Artificial neural networks Cyberattack Australia Resistance Radial basis function networks Nickel Mathematical models Adaptive bias radial basis function neural network (RBFNN) connected automated vehicle (CAV) cooperative lane-merging control deception attack practical prescribed time control RBFNN

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Convolutional-Attention Hybrid Deep-Learning Model With Transfer Learning for Quality Inspection of DC Motors

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2024年 73卷 1页

作者： Xie, Wei Li, Yanfu Wei, Haixiang Zhang, Langwen South China Univ Technol Sch Automati Sci & Engn Guangdong Prov Key Lab Tech & Equipment Macromol A Key Lab Autonomous Syst & Networked Control Guangzhou 510641 Guangdong Peoples R China South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Guangzhou 510641 Guangdong Peoples R China South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China

Direct current (dc) gear motor is widely used in mechanical and electronic devices, known for the advantages of simple structure, small size, high torque, wide speed range, and high reliability. Accidents caused by motor quality issues or malfunctions can have serious negative consequences, highlighting the need for dc gear motor quality inspections. Addressing the limitations in the generalization and accuracy of current deep-learning-based motor fault detection methods, this work proposes a hybrid convolution and self-attention deep-learning classification network model named ConvNeXt-T-MSA. The model is applied to the quality inspection of dc gear motors, and the time-frequency diagram of the motor vibration signal obtained by a short-time Fourier transform is used as the model input. The model combines convolution and self-attention and optimizes model performance through transfer learning to alleviate the data scarcity issues. The proposed approach achieves effective quality inspection and grade classification for dc gear motors. Multiple 12FN20-37 dc gear motors are used to construct a dc motor quality inspection dataset. For the 12FN20-37 dataset, the proposed method achieves an accuracy of 99.7%, and the accuracy on the public dataset CWRU is 99.9%. Based on the designed network model, we design a dc gear motor quality inspection system. Another 40 12FN20-37 dc geared motors are used to conduct real-time testing. A total of 800 tests are performed and an accuracy rate of 95% is achieved. The average total sampling and detection time for each time is 1.52 s. The results indicate that the system can accomplish the task of dc motor quality inspection with good generalization and accuracy.

关键词： ConvNeXt-T-MSA deep learning hybrid model motor detect self-attention transfer learning

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A difference-algebraic interval observer design for perturbed discrete-time descriptor systems

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EUROPEAN JOURNAL OF control 2023年 69卷

作者： Liu, Long-wen Xie, Wei Zhang, Lang-wen South China Univ Technol Coll Automat Sci & Technol Guangzhou 510641 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510641 Peoples R China South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Guangzhou 510641 Peoples R China Minist Educ Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

This paper investigates a difference-algebraic (DA) interval observer (IO) design technique for perturbed discrete-time descriptor systems. The existence condition of the IO with a DA structure is first estab-lished, along with the canonical implementation of descriptor systems and its non-negativity criterion. Then, combined with such an IO, a triangular block transformation (TBT) is further introduced to reduce the universal IO design conservatism on cooperativity construction. Besides, the general and particular solutions to the TBT&DA-based IO are successively proposed not only to clearly show the available design parameters but also to achieve a convenient construction process. Three simulation results demonstrate the validity and superiority of the proposed methods. (c) 2022 European control Association. Published by Elsevier Ltd. All rights reserved.

关键词： Difference-algebraic structure Interval observer Descriptor system Triangular block transformation

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