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Experimental investigation on noise characteristics of small scale vertical axis wind turbines in urban environments

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RENEWABLE ENERGY 2022年 200卷 970-982页

作者： Li, Shoutu Chen, Qin Li, Ye Probsting, Stefan Yang, Congxin Zheng, Xiaobo Yang, Yannian Zhu, Weijun Shen, Wenzhong Wu, Faming Li, Deshun Wang, Tongguang Ke, Shitang Lanzhou Univ Technol Sch Energy & Power Engn Lanzhou 730050 Peoples R China Gansu Prov Technol Ctr Wind Turbines Lanzhou 730050 Peoples R China Key Lab Fluid Machinery & Syst Lanzhou 730050 Peoples R China State Key Lab Aerodynam Mianyang 621000 Sichuan Peoples R China Shanghai Jiao Tong Univ Sch Naval Architecture Ocean & Civil Engn Multiple Funct Towing Tank Lab Shanghai 200240 Peoples R China South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Key Lab Autonomous Syst & Networked Control Minist Educ Guangzhou 510640 Peoples R China Yangzhou Univ Sch Hydraul Energy & Power Engn Yangzhou 225127 Jiangsu Peoples R China CRRC Zhuzhou Inst Co Ltd Wind Power Business Unit Zhuzhou 412000 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Aerosp Engn Nanjing 210001 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing 211100 Peoples R China

Noise pollution from wind turbines has been receiving significant attention with the rapid increase in global wind power installation, especially in urban environments where population density is high. Several countries tried to quantify the relation between wind turbine design characteristics and noise impact levels. To date, no quantitative results have been presented, while it is believed that the vertical axis wind turbine has advantages compared to horizontal axis wind turbines in certain applications. With the purpose to enhance understanding of noise pollution caused by vertical axis wind turbines in the urban environment, a systematic experimental test campaign in an anechoic wind tunnel was conducted. The results demonstrate that low-frequency noise increasingly affects humans when the wind speed increases. The blade-passing frequency is identified as a major parameter in the generation of low-frequency noise. More importantly, the noise pollution from various designs is discussed to analyze the impacts on humans and various animals. These designs are analyzed according to national standards from different countries. It is found that an optimal design of a vertical axis wind turbine is suitable for the urban environment with minimal noise impact.

关键词： Wind energy Vertical axis wind turbine Small scale wind turbine Noise impact Urban environment Acoustics wind tunnel test

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New Discrete-Time Models of Zeroing Neural Network Solving systems of Time-Variant Linear and Nonlinear Inequalities

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2020年第2期50卷 565-576页

作者： Shi, Yang Zhang, Yunong Sun Yat Sen Univ Sch Informat Sci & Technol Guangzhou 510006 Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Peoples R China SYSU CMU Shunde Int Joint Res Inst Foshan 528300 Peoples R China Minist Educ Key Lab Machine Intelligence & Adv Comp Guangzhou 510006 Peoples R China

In this paper, a new one-step-ahead numerical differentiation rule termed 5-instant discretization formula is proposed for the first-order derivative approximation with higher computational precision. Then, by exploiting the proposed formula to discretize the continuous-time zeroing neural network [or termed, continuous-time Zhang neural network (ZNN)] models, two new discrete-time zeroing neural network [or termed, discrete-time ZNN (DTZNN)] models are proposed, analyzed and investigated for solving systems of discrete time-variant inequalities, including the system of discrete time-variant linear inequalities and the system of discrete time-variant nonlinear inequalities. For comparative purposes, the recently developed Taylor-type DTZNN models and the widely used Euler-type DTZNN models are also presented. Theoretical analyses show that the proposed DTZNN models are convergent, and their steady-state residual errors have an O(g(4)) pattern with g denoting the sampling gap. Comparative numerical experimental results further substantiate the efficacy and superiority of the proposed DTZNN models for solving the systems of discrete time-variant inequalities.

关键词： 5-instant discretization formula (5IDF) convergence discrete-time zeroing neural network (DTZNN) residual error systems of time-variant inequalities

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A novel redesign framework to extend the application scope of a class of disturbance-rejection algorithms

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2020年第1期30卷 321-337页

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

In this paper, a novel redesign method is developed for a class of disturbance-rejection algorithms so that they can be applied to pure-feedback nonaffine-in-control nonlinear systems with matched and mismatched disturbances. First, a series of augmented dynamical equations, which evolve faster than the original system, are constructed to establish a boundary-layer subsystem to derive the virtual and actual inputs for the nominal system. Then, the composite interconnected system is studied in the standard singular perturbed form. In the slow timescale, the reduced slow subsystem (RSS) is transformed into the chain of integrators form in the error coordinate, for which the existing antidisturbance methods can be employed. The tracking performance of the closed-loop system is approximated by RSS under singular perturbation theory. The proposed redesign method is adopted to three existing disturbance-rejection algorithms for a pure-feedback nonaffine-in-control numerical example in the presence of matched and mismatched disturbances. The effectiveness is demonstrated by simulation experimental results.

关键词： disturbance-rejection matched and mismatched disturbances nonaffine-in-control pure-feedback systems singular perturbation

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Disturbance observer enhanced variable gain controller for robot teleoperation with motion capture using wearable armbands

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autonomous ROBOTS 2020年第7期44卷 1217-1231页

作者： Huang, Darong Yang, Chenguang Ju, Zhaojie Dai, Shi-Lu South China Univ Technol Sch Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou 510640 Peoples R China Univ West England Bristol Robot Lab Bristol BS16 1QY Avon England Univ Portsmouth Sch Comp Portsmouth POI 2DJ Hants England

Disturbance observer (DOB) based controller performs well in estimating and compensating for perturbation when the external or internal unknown disturbance is slowly time varying. However, to some extent, robot manipulators usually work in complex environment with high-frequency disturbance. Thereby, to enhance tracking performance in a teleoperation system, only traditional DOB technique is insufficient. In this paper, for the purpose of constructing a feasible teleoperation scheme, we develop a novel controller that contains a variable gain scheme to deal with fast-time varying perturbation, whose gain is adjusted linearly according to human surface electromyographic signals collected from Myo wearable armband. In addition, for tracking the motion of operator's arm, we derive five-joint-angle data of a moving human arm through two groups of quaternions generated from the armbands. Besides, the radial basis function neural networks and the disturbance observer-based control (DOBC) approaches are fused together into the proposed controller to compensate the unknown dynamics uncertainties of the slave robot as well as environmental perturbation. Experiments and simulations are conducted to demonstrated the effectiveness of the proposed strategy.

关键词： Disturbance observer Motion capture Radial basis function neural networks Teleoperation Variable gain control

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DIDO: Deep Inertial Quadrotor Dynamical Odometry

arXiv

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arXiv 2022年

作者： Zhang, Kunyi Jiang, Chenxing Li, Jinghang Yang, Sheng Ma, Teng Xu, Chao Gao, Fei State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou313000 China Alibaba DAMO Academy Autonomous Driving Lab Hangzhou311121 China

—In this work, we propose an interoceptive-only state estimation system for a quadrotor with deep neural network processing, where the quadrotor dynamics is considered as a perceptive supplement of the inertial kinematics. To improve the precision of multi-sensor fusion, we train cascaded networks on real-world quadrotor flight data to learn IMU kinematic properties, quadrotor dynamic characteristics, and motion states of the quadrotor along with their uncertainty information, respectively. This encoded information empowers us to address the issues of IMU bias stability, quadrotor dynamics, and multi-sensor calibration during sensor fusion. The above multisource information is fused into a two-stage Extended Kalman Filter (EKF) framework for better estimation. Experiments have demonstrated the advantages of our proposed work over several conventional and learning-based methods. © 2022, CC BY.

关键词： Extended Kalman filters

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A Novel Fractional-Order Model of Medium-Frequency Respiratory Impedance

A Novel Fractional-Order Model of Medium-Frequency Respirato...

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International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Hongwei Wang Bin Li Hongqiang Mo Yuanda Xu Zhaoxiang Xu Yanqing Xie School of Automation Science and Engineering South China University of Technology Guangzhou P.R. China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education South China University of Technology Guangzhou P.R. China Department of Critical Care Medicine The First Affiliated Hospital Guangzhou Medical University Guangzhou P.R. China The First Affiliated Hospital Guangzhou Medical University Guangzhou P.R. China

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

Respiratory impedance in the medium-frequency range reflects the dynamic properties of airways and lung tissues, and plays an important role in the early diagnosis of pulmonary diseases. Fractional-order models can characterize complex dynamics with fewer parameters compared to integer-order models, and have been used to represent the medium-frequency characteristics of the respiratory impedance. There have been multiple fractional-order models, but there is no consensus on which model is most reasonable. This paper proposes a novel fractional-order model, which consists of a viscous resistance, an inertia resistance, and an elastic resistance. Unlike existing models, in the proposed model, the inertial resistance is represent with a fractional-order term, while the other two resistances are represent with integer-order terms. The proposed model was employed to represent the medium-frequency respiratory impedance determined by appling impulse oscillometry to 8 healthy subjects. The results in terms of fitting error and determination coefficient indicate that the proposed model fits the data well. Furthermore, when examining the variation of the parameters of the model over time, the results indicate that the parameters are highly correlated with tidal volume. However, the parameters of other existing fractional-order models did not exhibit this correlation.

关键词： Resistance Solid modeling Correlation Fluctuations Atmospheric modeling Pulmonary diseases Lungs Fitting Signal processing Impedance

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Output Regulation of Nonlinear systems by an Emulation-Based Approach

Output Regulation of Nonlinear Systems by an Emulation-Based...

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American control Conference (ACC)

作者： Jieshuai Wu Maobin Lu Fang Deng Jie Chen School of Automation Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Department of Control Science and Engineering Tongji University Shanghai China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing China

In this paper, we investigate the semi-global robust output regulation problem of a class of nonlinear networked control systems by an emulation approach. We propose a class of sampled-data control laws to solve this problem. In particular, by the emulation approach, we first develop a class of sampled-data dynamic output feedback control laws. Then, based on the internal model principle, we convert the semi-global robust output regulation problem into a semi-global robust stabilization problem of an augmented hybrid system composed of the internal model and the original system. Next, we show that semi-global robust stabilization of the augmented hybrid system can be achieved by a sampled-data control law and thus leading to the solution of the semi-global robust output regulation problem. Finally, an example is given to illustrate our control approach.

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Targeting wastewater quality variables prediction: Improving sparrow search algorithm towards optimizing echo state network

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JOURNAL OF WATER PROCESS ENGINEERING 2024年 65卷

作者： Liu, Yiqi Sun, Yue Fang, Gang Ye, Hongtao Cai, Zefan 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 Guangdong Engn Technol Res Ctr Unmanned Aerial Veh Sch Automat Sci & Engn Guangzhou 510640 Peoples R China Guangxi Univ Sci & Technol Sch Automat Liuzhou 545036 Peoples R China ShunDe Polytech Coll Intelligent Manufacture Foshan 528333 Peoples R China

In the wastewater treatment processes (WWTPs), the absence of hardware sensors, along with the high nonlinearity, dynamics and nexus effect among wastewater data, usually makes accurate measurement of critical quality-related variables difficult. Therefore, this paper proposes a soft sensor framework, EAGSSA-RESN, to better the prediction accuracy of key quality-related variables. Firstly, by improving the least absolute shrinkage and selection operator (Lasso) together with Hilbert-Schmidt independence criterion (HSIC), auxiliary variables strongly correlated with predictor variables are selected as model inputs. Secondly, inspired by the artificial gorilla troop optimizer, the improved elite chaotic reverse learning and a nonlinear adaptive weighting factor are assimilated into an enhanced adaptive gorilla sparrow search algorithm (EAGSSA) to strengthen the optimization performance. Finally, the parameters of the ridge-regression echo state network (RESN) are optimized by EAGSSA, thus enabling the realization of a new parameter-free soft sensor for quality-related variables. Two datasets from different WWTPs indicate that the EAGSSA-RESN framework outperforms the RESN optimized by the original sparrow search algorithm, with RMSE being reductions of 25.41 %, 7.45 %, 6.34 %, 24.97 % in BOD5, COD, DBO-S, and DQO-S variables, respectively. The results confirm that the proposed soft sensor is a reliable and powerful tool for predicting wastewater quality variables with higher prediction accuracy and better robustness.

关键词： Wastewater treatment Echo state network Sparrow search algorithm Soft sensor

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An Incremental Learning Framework to Enhance Teaching by Demonstration Based on Multimodal Sensor Fusion

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FRONTIERS IN NEUROROBOTICS 2020年 14卷 55页

作者： Li, Jie Zhong, Junpei Yang, Jingfeng Yang, Chenguang South China Univ Technol Sch Automat Sci & Engn Key Lab Autonomous Syst & Networked Control Guangzhou Peoples R China Nottingham Trent Univ Sch Sci & Technol Nottingham England Guangzhou Chinese Acad Sci Shenyang Inst Automat Guangzhou Peoples R China Univ West England Bristol Robot Lab Bristol Avon England

Though a robot can reproduce the demonstration trajectory from a human demonstrator by teleoperation, there is a certain error between the reproduced trajectory and the desired trajectory. To minimize this error, we propose a multimodal incremental learning framework based on a teleoperation strategy that can enable the robot to reproduce the demonstration task accurately. The multimodal demonstration data are collected from two different kinds of sensors in the demonstration phase. Then, the Kalman filter (KF) and dynamic time warping (DTW) algorithms are used to preprocessing the data for the multiple sensor signals. The KF algorithm is mainly used to fuse sensor data of different modalities, and the DTW algorithm is used to align the data in the same timeline. The preprocessed demonstration data are further trained and learned by the incremental learning network and sent to a Baxter robot for reproducing the task demonstrated by the human. Comparative experiments have been performed to verify the effectiveness of the proposed framework.

关键词： incremental learning network teaching by demonstration teleoperation data fusion robot learning

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Constrained Predictive Tracking control for Unmanned Hexapod Robot with Tripod Gait

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DRONES 2022年第9期6卷 246-246页

作者： Gao, Yong Wang, Dongliang Wei, Wu Yu, Qiuda Liu, Xiongding Wei, Yuhai South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China Shantou Univ Coll Engn Shantou 515063 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

Since it is difficult to accurately track reference trajectories under the condition of stride constraints for an unmanned hexapod robot moving with rhythmic gait, an omnidirectional tracking strategy based on model predictive control and real-time replanning is proposed in this paper. Firstly, according to the characteristic that the stride dominates the rhythmic motion of an unmanned multi-legged robot, a body-level omnidirectional tracking model is established. Secondly, a quantification method of limb's stretch and yaw constraints described by motion stride relying on a tripod gait is proposed, and then, a body-level accurate tracking controller based on constrained predictive control is designed. Then, in view of the low tracking efficiency of the robot under the guidance of common reference stride, a solution strategy of variable stride period and a real-time replanning scheme of reference stride are proposed based on the limb constraints and the integral mean, which effectively avoid the tracking deviation caused by the guidance of constant reference strides. Finally, the effectiveness and practicability of the proposed control strategy are demonstrated through the comparative analysis and simulation test of a hexapod robot WelCH with omnidirectional movement ability to continuously track the directed curve and the undirected polyline trajectory.

关键词： multi-legged robot trajectory tracking model predictive control stride constraint stride replanning

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