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AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023

作者： Li, Pengyu Yang, Yannian Zhang, Haoyu Liu, Yu Li, Qingxi Noack, Prof. Bernd Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong Shenzhen518055 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong School of Automation Science and Engineering South Guangdong510640 China Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong Shenzhen518055 China AVIC General Aircraft Research Institute Zhuhai Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong519040 China School of Mechanical Engineering and Automation Harbin Institute of Technology Guangdong Shenzhen518055 China

ISBN: (数字)9781624107047

ISBN: (纸本)9781624107047

Contra-rotating rotors have the advantage of compactness and redundancy, which can be observed in many unmanned aerial vehicles. One significant installation parameter for the contra-rotating rotors is the axial distance between the upper and lower rotors, which influences both the time-averaged and unsteady loading of the rotors, as well as the aeroacoustic noise emission. Through experimental methods, each rotor is mounted to a six-component balance to study the impact of the axial distance on the two rotors, and an microphone arc-array is used to study the noise emission and directivity in an anechoic chamber. Two rotors are set at the same rotational speed for all axial distance settings. The results indicate that the increase of axial distance is advantageous for the aerodynamic performance increase and noise reduction, especially in the axial range of 0.1 diameter. The recovery of aerodynamic performance is due to the fully developed slipstream which reduces the mutual influence between the two rotors. The noise reduction is mainly due to the reduced velocity fluctuation alleviates the inter actiontonal noise, although the broadband noise becomes larger as the axial distance increases. © 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Noise abatement

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Approximate Dynamic Inversion for Nonaffine Nonlinear systems With High-Order Mismatched Disturbances and Actuator Saturation

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IEEE ACCESS 2020年 8卷 26247-26256页

作者： Yang, Hao Pei, Hailong South China Univ Technol Key Lab Autonomous Syst & Networked Control Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Minist Educ Guangzhou 510640 Guangdong Peoples R China

In this paper, a novel disturbance-observer-based approximate dynamic inversion (ADI) approach is developed for pure-feedback nonaffine-in-control nonlinear systems (PFNNSs) in the presence of both high-order mismatched disturbances and actuator saturation. Finite-time disturbance observers (FTDOs) are utilized to estimate the disturbances and their derivatives. Then, we rebuild the system with the outputs of FTDOs. Thereafter, ADI is employed to derive the desired virtual and actual control of the nominal system, where no disturbances and saturation are presented. Furthermore, an augmented intermediate subsystem is constructed for the reduced slow subsystem to compensate for the difference between inputs with and without saturation by approximating its inversion. The stability of the closed-loop system is studied using Tikhonov & x2019;s theorem. The proposed method is applied to a numerical example and a one-link robotic system with a brush DC motor. The simulation results demonstrate the validity of the presented approach.

关键词： High-order mismatched disturbances actuator saturation finite-time disturbance observer approximate dynamic inversion singular perturbation theory

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Learning a neural network-based soft sensor with double-errors parallel optimization towards effluent variable prediction in wastewater treatment plants

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024年 366卷 121907页

作者： Li, Dong Yang, Chunhua Li, Yonggang Chen, Yan Huang, Daoping Liu, Yiqi Cent South Univ Sch Automat Changsha 410083 Peoples R China South China Univ Technol Minist Educ Sch Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Wushan Rd Guangzhou 510640 Peoples R China Guizhou Minzu Univ Sch Data Sci & Informat Engn Guiyang 550025 Peoples R China

With the development of machine learning and artificial intelligence (ML/AI) models, data-driven soft sensors, especially the neural network-based, have widespread utilization for the prediction of key water quality indicators in wastewater treatment plants (WWTPs). However, recent research indicates that the prediction performance and computational efficiency are greatly compromised due to the time-varying, nonlinear and highdimensional nature of the wastewater treatment process. This paper proposes a neural network-based soft sensor with double-errors parallel optimization to achieve more accurate prediction for effluent variables timely. Firstly, relying on the Activity Based Classification (ABC) principle, an ensemble variable selection method that combines Pearson correlation coefficient (PCC) and mutual information (MI) is introduced to select the optimal process variables as auxiliary variables, thereby reducing the data dimensionality and simplifying the model complexity. Subsequently, a double-errors parallel optimization methodology with minimizing both point prediction error and distribution error simultaneously is proposed, aiming to enhancing the training efficiency and the fitting quality of neural networks. Finally, the effectiveness is quantitatively assessed in two datasets collected from the Benchmark Simulation Model no. 1 (BMS1) and an actual oxidation ditch WWTP. The experimental results illustrate that the proposed soft sensor achieves precise effluent variable prediction, with RMSE, MAE and R2 values being 0.0606, 0.0486, 0.99930, and 0.06939, 0.05381, 0.98040, respectively. Consequently, this soft sensor can expedite the convergence speed in the neural network training process and enhance the prediction performance, thereby contributing to the effective optimization management of WWTPs.

关键词： Soft sensor Variable selection Neural network optimization Effluent variable prediction Wastewater treatment

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A Framework of Hybrid Force/Motion Skills Learning for Robots

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IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL systems 2021年第1期13卷 162-170页

作者： Wang, Ning Chen, Chuize Di Nuovo, Alessandro Univ West England Bristol Robot Lab Bristol BS16 1QY Avon England South China Univ Technol Coll Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Peoples R China Sheffield Hallam Univ Ctr Automat & Robot Res Sheffield S11WB S Yorkshire England

Human factors and human-centered design philosophy are highly desired in today's robotics applications such as human-robot interaction (HRI). Several studies showed that endowing robots of human-like interaction skills can not only make them more likeable but also improve their performance. In particular, skill transfer by imitation learning can increase the usability and acceptability of robots by users without computer programming skills. In fact, besides positional information, muscle stiffness of the human arm and contact force with the environment also play important roles in understanding and generating human-like manipulation behaviors for robots, e.g., in physical HRI and teleoperation. To this end, we present a novel robot learning framework based on dynamic movement primitives (DMPs), taking into consideration both the positional and contact force profiles for human-robot skills transferring. Distinguished from the conventional method involving only the motion information, the proposed framework combines two sets of DMPs, which are built to model the motion trajectory and the force variation of the robot manipulator, respectively. Thus, a hybrid force/motion control approach is taken to ensure the accurate tracking and reproduction of the desired positional and force motor skills. Meanwhile, in order to simplify the control system, a momentum-based force observer is applied to estimate the contact force instead of employing force sensors. To deploy the learned motion-force robot manipulation skills to a broader variety of tasks, the generalization of these DMP models in actual situations is also considered. Comparative experiments have been conducted using a Baxter robot to verify the effectiveness of the proposed learning framework on real-world scenarios like cleaning a table.

关键词： Force Robot sensing systems Task analysis Observers Dynamics Force sensors Dynamic movement primitives (DMPs) force observer generalization hybrid force motion control robot learning skill transfer

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Multi-Loss Function for Distance-to-collision Estimation

Multi-Loss Function for Distance-to-collision Estimation

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2021 International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2021

作者： Zhang, Xiangzhu Zhang, Lijia Xu, DIng Pei, Hailong South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Min. of Educ. Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong Guangzhou China Guangdong University of Technology School of Computer Science and Technology Guangzhou China

ISBN: (纸本)9781665402453

Estimation of the drone's distance-to-collision is the key to the indoor autonomous obstacle avoidance and navigation of monocular UAVs. At present, the distance-to-collision model mainly uses regression loss or ordinal regression for training Regression loss utilizes the continuity of distance, and ordinal regression loss utilizes the order of distance. To improve the prediction performance of the model, this paper proposes a multi-loss function trained deep learning model based on the linear combination of ordinal regression loss and regression loss. The regression loss can be obtained by adding a distance decoder after the ordinal regression estimation, without changing the original structure of the model. Finally, we test the model performance in public datasets and obtain good results. © 2021 IEEE.

关键词： Regression analysis

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Model Predictive control Technique for Ducted Fan Aerial Vehicles Using Physics-Informed Machine Learning

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DRONES 2023年第1期7卷 4-4页

作者： Manzoor, Tayyab Pei, Hailong Sun, Zhongqi Cheng, Zihuan South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Key Lab Autonomous Syst & Networked Control Sch Automat Sci & EngnMinist Educ Guangzhou 510640 Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

This paper proposes a model predictive control (MPC) approach for ducted fan aerial robots using physics-informed machine learning (ML), where the task is to fully exploit the capabilities of the predictive control design with an accurate dynamic model by means of a hybrid modeling technique. For this purpose, an indigenously developed ducted fan miniature aerial vehicle with adequate flying capabilities is used. The physics-informed dynamical model is derived offline by considering the forces and moments acting on the platform. On the basis of the physics-informed model, a data-driven ML approach called adaptive sparse identification of nonlinear dynamics is utilized for model identification, estimation, and correction online. Thereafter, an MPC-based optimization problem is computed by updating the physics-informed states with the physics-informed ML model at each step, yielding an effective control performance. Closed-loop stability and recursive feasibility are ensured under sufficient conditions. Finally, a simulation study is conducted to concisely corroborate the efficacy of the presented framework.

关键词： aerial robotics flight control machine learning model predictive control trajectory tracking UAV

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Wide-area Monitoring and Analysis of Wide-band Oscillation in New-type Power systems 10

Wide-area Monitoring and Analysis of Wide-band Oscillation i...

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10th China International Conference on Electricity Distribution, CICED 2022

作者： Ma, Ningning Xie, Xiaorong Sun, Yiqian Zhang, Yanjun Li, Yongguang Liu, Pengyin State Key Lab of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Haidian District Beijing100084 China State Grid Xinjiang Electric Power Company Xinjiang Uygur Autonomous Region Urumchi830063 China

ISBN: (数字)9781665452687

ISBN: (纸本)9781665452687

The wide-band oscillation resulting from the interaction between power electronics and the power grid is increasingly evident to the power system. It is necessary to monitor the dynamic behavior of the wide-band oscillation. However, the existing phasor measurement unit (PMU) and the corresponding wide-area measurement system (WAMS) can hardly capture wide-band phasors. To get a better view of wide-band oscillation, a measurement method to capture wide-band phasors is proposed in this paper, as well as a frame of a corresponding wide-area monitoring system for wide-band oscillation (WOMS) is constructed. The prototype of the wide-band phasor measurement unit (WPMU)-based on this measurement method is developed. The essential software and hardware of the WPMU are elaborated. The steady tests and dynamic tests are executed to verify the capability of the WPMU. The results indicate that WPMU and WOMS are highly effective in analyzing wide-band oscillation. © 2022 IEEE.

关键词： Phasor measurement units

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Consensus of Continuous-Time Multiagent systems via Delayed Output Feedback: Delay Versus Connectivity

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IEEE TRANSACTIONS ON AUTOMATIC control 2021年第3期66卷 1329-1336页

作者： Qi, Tian Lu, Renquan Chen, Jie South China Univ Technol Sch Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou 510900 Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510900 Peoples R China Guangdong Univ Technol Guangdong Prov Key Lab Intelligent Decis & Cooper Guangzhou 510900 Peoples R China City Univ Hong Kong Dept Elect Engn Kowloon Hong Kong Peoples R China

This article studies the consensus problem for continuous-time linear time-invariant multiagent systems, in which the agents exchange information through delayed communication channels in a fixed undirected topology. Our primary objective is to characterize explicitly the delay effect on consensus in the framework of distributed dynamic output feedback control and its implication on the graph network connectivity. For this purpose, we tackle and solve the consensus problem in the spirit of gain margin problem, using analytic interpolation techniques. We develop an explicit condition for consensus. The result provides a limit on network connectivity imposed by time delays as well as by the agent's unstable poles and nonminimum phase zeros.

关键词： Optimized production technology Delays Poles and zeros Protocols Output feedback Network topology Delay effects Analytic interpolation consensus multiagent systems (MASs) time delay

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Adaptive Stiffness control of Series Elastic Actuator Manipulators Based on Dynamic System

Adaptive Stiffness Control of Series Elastic Actuator Manipu...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Kunlin Guo Chao Zeng Weiyong Si Ning Wang Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control School of Automation Science and Engineering South China University of Technology Guangzhou China Department of Computer Science University of Liverpool Liverpool UK School of Computer Science and Electronic Engineering University of Essex Colchester Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In traditional control methods, Series Elastic Actuator (SEA) joint manipulators are limited by their hardware and can only perform simple tasks with low stiffness. To address this issue, we propose a stiffness adjustment control strategy for SEA manipulators based on Dynamic systems (DS) with good generalization performance. By enhancing the generalization capability of DS in complex tasks and combining posture control, the SEA manipulators can autonomously adjust control gains and postures according to task requirements to achieve higher stiffness at the end-effector. Experimental results involving the activation of air switches with different stiffness levels and installation angles have demonstrated the effectiveness of our proposed method. The results indicate that compared to traditional methods of adjusting the control gain and retraining DS for similar tasks, our approach exhibits superior generalization performance while maintaining end-effector stiffness during interactions.

关键词： Actuators Computer aided software engineering Automation Adaptive systems control systems End effectors Hardware Dynamical systems Manipulator dynamics

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Multiobjective Optimization of Chaotic Image Encryption Based on ABC Algorithm and DNA Coding

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INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS 2024年第5期34卷 2450057-2450057页

作者： Yu, Jinwei Xie, Wei 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 Guangzhou Guangdong Peoples R China South China Univ Technol Key Lab Autonomous Syst & Networked Control Guangzhou Guangdong Peoples R China South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Guangzhou Guangdong Peoples R China

As digital communication and storage continue to expand, the protection of image privacy information becomes increasingly critical. To safeguard sensitive visual information from unauthorized access, this paper proposes a novel image encryption scheme that integrates multiobjective Artificial Bee Colony (ABC) optimization algorithm and DNA coding. Multiple evaluation metrics including correlation relationship, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), and information entropy are collaboratively optimized by the ABC algorithm. The proposed method begins with the application of the SHA-256 algorithm to generate keys and random sequences using chaotic systems. These sequences are then employed for shuffling, DNA coding, decoding, and diffusion, generating initial encrypted images. Subsequently, the encrypted images serve as individuals within the ABC algorithm to determine optimal parameters of the chaotic systems and the best ciphertext image. Simulation experiments demonstrate that the ciphertext images achieved excellent results in information entropy, pixel correlation coefficient, NPCR, and UACI. The integration of the multiobjective ABC optimization algorithm with DNA coding in our proposed image encryption scheme results in heightened security, as evidenced by superior performance in various metrics.

关键词： Image encryption DNA coding ABC optimization algorithm chaotic system information entropy

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