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Chinese control and Decision Conference, CCDC

作者： Pengcheng Hu Chaochen Gu Kaijie Wu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665478977

Aiming at the sudden change of load torque and uncertain external disturbance that multi-axis serial manipulators may face during operation, an improved Active Disturbance Rejection controller (ADRC) assisted by a Nonlinear Disturbance Observer (NLDOB) is designed and implemented in this paper. ADRC realizes the estimation and compensation of known model parameter perturbation, and NLDOB is introduced to estimate and compensate the load torque and other unmodeled dynamic factors of the manipulator. Meanwhile, the lumped control object model of three-bar mechanism and permanent magnet DC motor is established, and the control response curves of improved ADRC, traditional ADRC, and PID under the same conditions are compared and analyzed through simulation. The experimental results show that compared with the traditional ADRC and PID, the improved ADRC has faster response speed, smaller overshoot and stronger robustness.

关键词： Robust control Analytical models Torque Perturbation methods Simulation Estimation DC motors

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Short-term power load forecasting method based on CNN-SAEDN-Res

arXiv

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arXiv 2023年

作者： Cui, Yang Zhu, Han Wang, Yijian Zhang, Lu Li, Yang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China College of Information and Electrical Engineering China Agricultural University Beijing100083 China

In deep learning, the load data with non-temporal factors are difficult to process by sequence models. This problem results in insufficient precision of the prediction. Therefore, a short-term load forecasting method based on convolutional neural network (CNN), self-attention encoder-decoder network (SAEDN) and resi- dual-refinement (Res) is proposed. In this method, feature extraction module is composed of a two-dimensional convolutional neural network, which is used to mine the local correlation between data and obtain high-dimensional data features. The initial load fore-casting module consists of a self-attention encoder-decoder network and a feedforward neural network (FFN). The module utilizes self-attention mechanisms to encode high-dimensional features. This operation can obtain the global correlation between data. Therefore, the model is able to retain important information based on the coupling relationship between the data in data mixed with non-time series factors. Then, self-attention decoding is per-formed and the feedforward neural network is used to regression initial load. This paper introduces the residual mechanism to build the load optimization module. The module generates residual load values to optimize the initial load. The simulation results show that the proposed load forecasting method has advantages in terms of prediction accuracy and prediction stability. Copyright © 2023, The Authors. All rights reserved.

关键词： Convolutional neural networks

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A novel feature enhancement module for small object detection

A novel feature enhancement module for small object detectio...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Ruogu Wang Ning Li Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781728119496

Generic object detection has made great progress in recent years, yet small object detection is still facing a serious problem of missed detection. The problem is caused by two reasons: low resolution in small targets and feature loss during deep convolution downsampling. Some previous studies used feature pyramid structures and multi-scale training predictions to alleviate this problem, but still cannot efficiently utilise the feature information of small targets. In this paper, firstly we propose a novel and effective feature enhancement module to extract more features; secondly, a filter size design method is presented to extract features of matching objects and incorporate context information; finally, an adaptive fusion method is used to process outputs of our module and improve model robustness. We select YOLOv3 as base model and carry out several experiments on a special Small Object Dataset and the results show that our work can achieve an increase of about seven percentage points (35.73%) compared to 28.78% on baseline.

关键词： Training Adaptation models Matched filters Design methodology Object detection Filtering algorithms Feature extraction

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Leader-following consensus for linear multi-agent systems with measurement noises

Leader-following consensus for linear multi-agent systems wi...

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第41届中国控制会议

作者： Kairui Chen Chuance Yan Zhangmou Zhu Ping Li Qijun Ren Junwei Wang School of Mechanical and Electrical Engineering Guangzhou University Key Laboratory of System Control and Information Processing Ministry of Education School of Mathematics and Statistics Guangdong University of Foreign Studies

This paper investigates a leader-following consensus problem for high-order linear multi-agent systems under a directed graph topology,containing a spanning *** is supposed that each agent can obtain full state of itself and receive its neighbors' state with noises,where the intensities of noises are vector functions of relative states of *** achieve leader-following consensus in this scene,a consensus protocol is designed,where the gain matrix is obtained by the algebraic Riccati equation and the coupling strength should be restricted in a given ***,the lower bound of the interval ensures the consensus and the upper bound of the interval is devoted to limit the efects of noises,then the designed protocol could attenuate the noises while driving the multi-agent systems to ***,a simulation example is given to show the correctness of the proposed results.

关键词： Leader-following Consensus Multi-agent systems Directed Graph measurement Noises

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Smith predictor-based nonlinear internal model control for water temperature regulation of combi-boiler systems

Smith predictor-based nonlinear internal model control for w...

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Jiangsu Annual Conference on Automation (JACA 2023)

作者： R. Liu M. Cao S. Li J. Yang Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing 210096 People's Republic of China Department of Aeronautical and Automotive Engineering Loughborough University Loughborough LE11 3TU UK

This paper proposes a reliable and practical water temperature control scheme for combi-boiler systems working in domestic hot water mode. In practice, the water temperature regulation process of a combi-boiler is strongly affected by the nonlinearities of actuators, the variation of system parameters caused by the fluctuation of water flow rate, external disturbances, and large, variable time delays. Although there are some results that can address one or two of these factors, a comprehensive and concise control scheme with consideration of all these factors is lacking. This paper aims to change this situation. First, based on the modeling and identification of real combi-boiler systems, the feedback linearization method is adopted in the controller synthesis to solve the effects of actuator nonlinearity. Next, a Smith predictor-based control structure is designed to eliminate system time delays. Finally, based on the internal model control (IMC) theory, an IMC-based parameter tuning method is proposed for the parameter selection of feedback controllers, in which the model parameters used in the controller synthesis are calculated in real-time based on the system identification results. As a result, the influence of model uncertainties and external disturbances can be effectively attenuated, and only one parameter is required to be tuned for the desired performance. The feasibility and effectiveness of the proposed control scheme are verified by simulations.

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Nonlinear vibration response characteristics of a dual-rotor-bearing system with squeeze film damper

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Chinese Journal of Aeronautics 2021年第10期34卷 128-147页

作者： Xinxing MA Hui MA Haiqin QIN Xumin GUO Chenguang ZHAO Mingyue YU School of Mechanical Engineering and Automation Northeastern UniversityShenyang J10819China Institute of Vibration Shock and NoiseShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern UniversityShenyang 110819China Department of Aeronautical Mechanics Naval Aeronautical and Astronautical University Qingdao CampusQingdao 266041China

Rolling bearing and Squeeze Film Damper(SFD)are used in rotor support structures,and most researches on the nonlinear rotor-bearing system are focused on the simple rotor-bearing *** work emphasizes the comparative analysis of the influence of SFD on the nonlinear dynamic behavior of the dual-rotor system supported by rolling ***,a reduced dynamic model is established by combining the Finite Element(FE)method and the freeinterface method of component mode *** proposed model is verified by comparing the natural characteristics obtained from an FE model with those from the ***,the steady-state vibration responses of the system with or without SFD are solved by the numerical integration *** influences of the ball bearing clearance,unbalance,centralizing spring stiffness and oil film clearance of SFD on the nonlinear steady-state vibration responses of the dual-rotor system are *** show that SFD can effectively suppress the amplitude jump of the dual rotor system sustaining two rotors unbalance *** the ball bearing clearance or unbalance increases,the amplitude jump phenomenon becomes more obvious,the resonance hysteresis phenomenon strengthens or weakens,the resonant peaks shift to the left or the right,*** with unreasonable parameters will aggravate the system vibration,the smaller the oil film clearance,the better the damping performance of the SFD,the larger the centralizing spring stiffness is,the larger resonance amplitudes are.

关键词： dual-rotor rolling bearing squeeze film damper finite element method vibration response

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Spatio-Temporal Transformer-Based Reinforcement Learning for Robot Crowd Navigation

Spatio-Temporal Transformer-Based Reinforcement Learning for...

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IEEE International Conference on Robotics and Biomimetics

作者： Haodong He Hao Fu Qiang Wang Shuai Zhou Wei Liu Yang Chen School of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan China

Ensuring robots can move safely and adhere to social norms in dynamic human environments is a crucial step towards robot autonomous decision-making. In existing work, double serial separate modules are generally used to capture spatial and temporal interactions, respectively. However, such methods lead to extra difficulties in improving the utilization of spatio-temporal features and reducing the conservatism of navigation policy. In light of this, this paper proposes a spatiotemporal transformer-based policy optimization algorithm to more effectively preserve the human-robot interactions. Specifically, a gated embedding mechanism is introduced to effectively fuses the spatial and temporal representations by integrating both modalities at the feature level. Then Transformer is leveraged to encode the spatio-temporal semantic information, with the hope of finding the optimal navigation policy. Finally, a combination of spatio-temporal Transformer and self-adjusting policy entropy significantly reduce the conservatism of navigation policies. Experimental results demonstrate the priority of the proposed algorithm over the state-of-the-art methods.

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High-order Fully-actuated controller Design for a Dual-Quadrotor Suspension system

High-order Fully-actuated Controller Design for a Dual-Quadr...

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

作者： Zhipeng Jiang Xianwei Li Department of Automation Shanghai Jiao Tong University Shanghai P. R. China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai P. R. China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

In this paper, the mathematical model of dual-quadrotor suspension system is established, and the high-order fully-actuated (HOFA) model of the system is derived. Then the direct parametric control method of HOFA nonlinear systems is used to design a controller of the dual-quadrotor suspension system. Simulation results about tracking a circle of the suspension system are presented, which show that HOFA controller have good control effects with relatively smaller tracking errors, while the thrusts of the two quadrotors are within a reasonable range. Compared with a benchmark PD controller in [1], the HOFA controller designed in this paper can mitigate the drastic oscillation in positions of the quadrotor and the load, while the fluctuation of the load attitudes are maintained within a reasonable range.

关键词： Fluctuations Attitude control Simulation Kinematics Mathematical models PD control Nonlinear systems

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Learning-Based Switched Reliable control of Cyber-Physical systems With Intermittent Communication Faults

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 711-724页

作者： Xin Huang Jiuxiang Dong College of Information Science and Engineering Northeastern UniversityShenyang 110819China State Key Laboratory of Synthetical Automation of Process Industries Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern UniversityShenyang 110819China IEEE

This study deals with reliable control problems in data-driven cyber-physical systems(CPSs) with intermittent communication faults, where the faults may be caused by bad or broken communication devices and/or cyber attackers. To solve them, a watermark-based anomaly detector is proposed, where the faults are divided to be either detectable or ***, the fault's intermittent characteristic is described by the average dwell-time(ADT)-like concept, and then the reliable control issues, under the undetectable faults to the detector, are converted into stabilization issues of switched systems. Furthermore,based on the identifier-critic-structure learning algorithm, a datadriven switched controller with a prescribed-performance-based switching law is proposed, and by the ADT approach, a tolerated fault set is given. Additionally, it is shown that the presented switching laws can improve the system performance degradation in asynchronous intervals, where the degradation is caused by the fault-maker-triggered switching rule, which is unknown for CPS operators. Finally, an illustrative example validates the proposed method.

关键词： Adaptive dynamic programming(ADP) communication fault cyber-physical systems(CPSs) data-driven control reliable control

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Model Predictive control Based on Amplitude Decaying Aggregation Strategy for Hydrogen Gas Turbine

Model Predictive Control Based on Amplitude Decaying Aggrega...

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Chinese Automation Congress (CAC)

作者： Aoyun Ma Dewei Li Yugeng Xi Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

The hydrogen gas turbine can be the key technology for carbon-neutral in the future. The flexibility of gas turbine under various operation conditions is an important issue. A state-space model of hydrogen gas turbine with different hydrogen volume ratio mixed fuel is constructed based on Rowen model, and a full-dimensional state observer is designed to obtain the states of state-space model. The model predictive control method based on amplitude decaying aggregation strategy is presented to stabilize the rotational speed of hydrogen gas turbine under various constraints, which are to ensure the safety of operation. The number of variables contained in the optimization problem to be solved online is reduced by aggregation strategy. The simulation results confirmed that the presented method works well, and the effects of the hydrogen volume ratio for the performance of hydrogen gas turbine are discussed.

关键词： Hydraulic turbines Solid modeling Computational modeling Hydrogen Velocity control Predictive models Observers

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