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2022 Chinese Automation Congress, CAC 2022

作者： Zeng, Kaiji Liu, Wei South China University of Technology Ministry of Education School of Automation Science and Engineering Key Laboratory of Autonomous Systems and Networked Control Guangzhou510641 China

ISBN: (纸本)9781665465335

We investigate a sampled-data tracking control for uncertain Euler-Lagrange systems in this paper. What makes our result interesting is that our system and exosystem encompass some uncertain parameters that belong to some compact domain that can be specified arbitrarily large. To handle the uncertainties in both the Euler-Lagrange systems and the exosystem, we need to resort to not only the adaptive control technique but also the internal model method. By proposing a sampled-data control law, we solve the problem with guaranteed tracking performance, that is, the tracking errors can converge exponentially, by any fast specified rate, to any small specified neighborhood of the origin. © 2022 IEEE.

关键词： Lagrange multipliers

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Uncertainty and Reliability Analysis of Neural Networks Based Soft-sensors with Applications in Wastewater Treatment

Uncertainty and Reliability Analysis of Neural Networks Base...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Yiqi Yuan, Jingyi Huang, Daoping Key Laboratory of Autonomous Systems and Networked Control Ministry of Education The School of Automation Science & Engineering South China University of Technology Guangzhou510640 China

ISBN: (纸本)9781665465335

To overcome the transparency and interpretability issues of neural network-based soft sensing, a data-driven framework by combining neural network prediction models and sensitivity analysis methods is constructed in this paper, with application in wastewater treatment plant analysis. The results show that readily biodegradable substrate effluent (SS-e) and NH4+ + NH3 nitrogen effluent (SNH-e) are both important input factors affecting the difficult-to-measured effluent quality, chemical oxygen demand (COD), by resorting to PAWN sensitivity analysis and four neural network models. In addition, four neural network models worked together with bilateral sensitivity analysis for the input perturbation analysis, which shows that the addition of Gaussian perturbation to SS-e and flow rate influent (Q-in) has a greater effect on the prediction which results large fluctuations of output results. Finally, the effectiveness of this framework is confirmed based on above results. © 2022 IEEE.

关键词： Sensitivity analysis

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The Application of Transfer Learning in P300 Detection

The Application of Transfer Learning in P300 Detection

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IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Liu, Yang Yang, Chenguang Li, Zhijun South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781538673546

The main task of a Brain-Computer Interface (BCI) is to use the EEG signals to realize communication of the human brain and computers or other external devices. This paper mainly studies the classification of P300 signals with the method of transfer learning. Convolutional neural network (CNN) and support vector machine (SVM) are used as the basic learning algorithm for transfer learning. Fine-tuning (FT) with which we built the CNN-FT model is introduced for CNN. Tradaboost algorithm, a novel transfer learning framework, is applied in SVM method to construct the SVM-TL model. These two models are trained, tested, compared and analyzed on the Data set II of BCI Competition III. The results show that CNN-FT model is better than CNN model and SVM-TL model is better than SVM model.

关键词： Support vector machines Classification algorithms Brain modeling Hidden Markov models Kernel Training data Electroencephalography

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Development of a neuro-feedback game based on motor imagery EEG

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第12期77卷 15929-15949页

作者： Yang, Chenguang Ye, Yuhang Li, Xinyang Wang, Ruowei South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Guangdong Peoples R China Univ Essex Sch Comp Sci & Elect Engn Colchester Essex England

Electroencephalogram (EEG) has widely been used to monitor subjects/patients' mental states. Using the monitor results as feedback, neuro-feedback enables patients to learn to regulate their physiological and psychological states so that improvements in physical and psychological subjects/patients' states could be achieved. By analyzing EEG components generated by motor imagery, a mind-controlled game based on motor imagery is developed, including the design of BCI and the design of the video game. In the game, neuro-feedback is realized to in a visual manner, through which the users could learn to improve attention span. Based on motor imagery, EEG signal is classified into two categories, the left and right hand motor imagery. The accuracy of classification is up to 70%. The bandpower analysis results show that users' attention level improves during the experiment. In this neuro-feedback game system, EEG signal is not only used for monitoring but also used for game control. The game provides an attention state measurements for users. With the neuro-feedback in the BCI, the user and the game form a close loop interactively. The proposed BCI video game could not only be used for entertainment and relaxation purpose, but attention-span training purpose.

关键词： EEG Neuro-feedback BCI Motor imagery Video game Attention

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Omnidirectional Mobile Robot control based on Mixed Reality and sEMG Signals

Omnidirectional Mobile Robot Control based on Mixed Reality ...

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Chinese Automation Congress (CAC)

作者： Wu, Mulun Xu, Yanbin Yang, Chenguang Feng, Ying South China Univ Technol Key Lab Autonomous Syst & Networked Control Coll Automat Sci & Engn Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781728113128

Robots are an important part of social production now, and their control methods have become an important research topic. There is a greater need for remote control and richer ways of interacting. In this paper, virtual reality and the surface electromyography(sEMG) signals are combined with the control of the omnidirectional mobile robot(OMR), and the programs of two devices, the HoloLens and the MYO armband, are respectively programmed and developed, so that they can work together to control the OMR. The basic control method is that HoloLens wearer controls the movement direction of the OMR through gesture or gaze. MYO armband wearer generate different sEMG signals through different gesture to control the velocity of the OMR. When two devices are used together, they can control all the motion of the OMR.

关键词： Omnidirectional Mobile Robot Virtual Reality Surface Electromyography Teleoperation

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Semi-Global Robust Practical Output Voltage Tracking for Single-Phase UPS Inverters via Sampled-Data control 42

Semi-Global Robust Practical Output Voltage Tracking for Sin...

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42nd Chinese control Conference, CCC 2023

作者： Zeng, Kaiji Liu, Wei Sun, Weijie Liu, Weidong Ministry of Education School of Automation Science and Engineering South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Guangzhou510641 China

ISBN: (纸本)9789887581543

This paper deals with the sampled-data semi-global robust practical output voltage tracking problem for single-phase voltage source uninterruptible power supply inverters. We construct an aperiodic sampled-data state feedback control law in an internal model principle framework. Lyapunov analysis shows that as long as the upper bound of the sampling time interval of the controller is less than an explicitly computable threshold, our problem can be handled by the proposed sampled-data control law. And the tracking error is guaranteed to approach a given neighborhood of the origin asympotically. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Uninterruptible power systems

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Modelling of piezoelectric actuating systems subjected to variable loads and frequencies and applications to prescribed performance control

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INTERNATIONAL JOURNAL OF control 2023年第9期96卷 2356-2373页

作者： Feng, Ying Hu, Zedong Liang, Mingwei South China Univ Technol Coll Automat Sci & Engn Guangzhou 510640 Peoples R China South China Univ Technol Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou 510640 Peoples R China

Piezoelectric actuators can offer micro/nano-level precision actuating ability and have been employed in different applications. For the piezoelectric actuating systems, the output actuating performance is affected not only by the internal non-smooth hysteresis but also by the operating load and the excitation frequency. To improve the actuating precision, predicting the nonlinear behaviour of the piezoelectric actuating system is essential for effective designs of control approaches. In this paper, a modified rate-dependent Prandtl-Ishlinskii model is presented to explore the coupling effects analytically between the internal hysteresis and the operating frequency with the external loads and predict the output behaviour of the piezoelectric actuating system accurately. The proposed modelling method is testified on a piezoelectric actuating platform under broad ranges of excitation frequencies (1-80 Hz) and external loads (0-0.5 kg), and the comparison results using the rate-dependent Prandtl-Ishlinskii (RDPI) model are also provided to prove the precision of the proposed method. Combining with the modified RDPI model, a guaranteeing preselected tracking controller is developed to ensure the output performance, and a set of tracking experiments under different frequencies with load is performed. The experimental results compared with PID control performance validate the effectiveness of the proposed prescribed performance control method and its high actuating performance against the adverse effects from the external hysteresis nonlinearities and external loads.

关键词： Piezoelectric actuator hysteresis prescribed performance control

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State and parameter identification of linearized water wave equation via adjoint method

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Science China(Information Sciences) 2024年第10期67卷 283-297页

作者： Yang YU Cheng-Zhong XU Hai-Long PEI Jinpeng YU School of Automation Qingdao University LAGEP Batiment CPE University Claude Bernard-Lyon 1 School of Automation Science and Engineering Key Laboratory of Autonomous Systems and Networked ControlMinistry of Education Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle SystemSouth China University of Technology

In this paper, we focus on the state and parameter identification problem of a hydrodynamical system. This system is modeled as a linearized water wave equation(LWWE), a hyperbolic state-space model coupled with a Laplace equation. We assume that the wave elevation at two distinct points is the only measurement of water waves. We show that the state and water depth can be reconstructed from this point measurement records. The identification problem is recast as an optimization problem over an infinite-dimensional space. We propose the adjoint method-based identification algorithm to generate an estimated state and water depth. We then performed a numerical simulation to show the effectiveness of our designed algorithm by comparing it with existing studies.

关键词： linearized water wave equation (LWWE) point observation state estimation parameter identification adjoint method numerical simulation

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Fully distributed consensus of second-order multi-agent systems using adaptive event-based control

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Science China(Information Sciences) 2018年第12期61卷 199-201页

作者： Wei ZHU Qianghui ZHOU DANDan WANG Gang FENG Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Key Lab of Industrial Internet of Things & Networked Control Ministry of EducationChongqing University of Posts and Telecommunications Department of Mechanical and Biomedical Engineering City University of Hong Kong

Dear editor,In recent years, the distributed consensus of multiagent systems (MASs) has attracted compelling attention because of its potential applications in many fields such as sensor networks, unmanned aerial vehicle (UAV) formation flying, and multiple signals tracking. The central task in the distributed consensus of MASs is to design distributed control protocols to achieve the consensus

关键词： In MAS Fully distributed consensus of second-order multi-agent systems using adaptive event-based control

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Development of a fast transmission method for 3D point cloud

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第19期77卷 25369-25387页

作者： Yang, Chenguang Wang, Zunran He, Wei Li, Zhijun South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou Guangdong Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing Peoples R China

In this paper, a transmission method of the 3D point cloud data of the object upper body is proposed. The key idea of the method is to reduce the amount of transmission data in the condition of retaining the necessary information. In our system, the unnecessary information is removed by using filters and the segmentation algorithm. Three P frames (Predicted frame) are inserted between two I frames (Intra frame) to further improve the transmission rate. The I frame of large size includes all the vision information that is related to the object upper body, while the P frame includes only the information of the small change in the current frame, whose size is smaller than the former. In order to acquire the information of the P frame, first, a human face detection algorithm based on the machine learning technology is implemented. Then, a coarse-to-fine approach is used to detect the nose tip which helps to improve the precision of acquiring the human faces information. The experiment result demonstrates that the proposed method is able to reduce the time delay of processing and transmission and to lower the compression ratio with an allowable distortion rate.

关键词： 3D point cloud Point cloud transmission Point cloud filter Point cloud compression Point cloud segmentation Human face detection Nose tip detection

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