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检索条件"任意字段=10th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2021"

共 359 条记录，以下是201-210 订阅

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Discrete Active Disturbance Rejection Iterative learning control Based on Dynamic Linearization 11

Discrete Active Disturbance Rejection Iterative Learning Con...

引用

11th ieee data driven control and learning systems conference, ddcls 2022

作者： Ai, Wei Li, Xinling Li, Xiangyang School of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

A discrete active disturbance rejection iterative learning control method based on dynamic linearization is proposed for a class of discrete-time, nonlinear and non-affine system that run repeatedly within a finite time. the controlled system is dynamically linearized into an affine form related to the control input within the iteration domain. the control gain is initialized through the pseudo partial derivative of dynamic linearization model when needed and then fixed. the estimated errors of parameter, system uncertainty and external disturbance are compacted into a nonlinear term as the total disturbance of the system. Via iterative sliding mode scheme, the iterative extended state observer is designed to estimate the total disturbance and a discrete active disturbance rejection iterative learning control law is proposed. the convergence of the iterative extended state observer and tracking errors of the system are analyzed. the proposed method is a new intuitive and concise data-driven control method which does not need the system model information. the effectiveness of the proposed method is verified by simulations. © 2022 ieee.

关键词： Disturbance rejection

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Adaptive exponentially asymptotic tracking control for a one-link manipulator 10

Adaptive exponentially asymptotic tracking control for a one...

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： Liang, Yanjun Li, Yuan-Xin Department of Automation Qingdao University Shandong Province Qingdao China College of Information with the College of Science Liaoning University of Technology Jinzhou121001 China

ISBN: (纸本)9781665424233

this article addresses the asymptotic tracking issues of a one-link manipulator system. To realize the exponentially asymptotic tracking performance, the exponential term has been introduced into the Lyapunov function and the bounds estimation method and the smooth modification function are used to guarantee the zero-error tracking. In addition, the neural networks (NNs) is devised to cope with the uncertain disturbance and unknown nonlinearlities. At last, a simulation example has been shown to verify the raised scheme. © 2021 ieee.

关键词： Lyapunov functions

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Anomaly detection method based on multi-criteria evaluation for energy data of steel industry 10

Anomaly detection method based on multi-criteria evaluation ...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Wu, Hao Jin, Feng Zhao, Jun Wang, Wei Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Dalian University of Technology Ministry of Education Dalian116024 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9781665424233

the stability and integrity of the monitoring data in the energy system of the iron and steel industry is of great significance for ensuring the safety of the system. Aiming at the data with periodic characteristics in the steel energy system, an abnormal data detection method based on multi-criteria evaluation is proposed in this study. the data time series is divided according to its periodic characteristics, and each sub-period sequence are evaluated through the quasi-measures established in this paper. then the outlier detection of the periodic time series is realized through the AFCM (Adaptive fuzzy C-means) of these evaluation results. the simulation results based on the actual operating data of a steel enterprise show that this method can identify the local abnormal state in the original time series and improve the detection efficiency. © 2021 ieee.

关键词： Anomaly detection

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A Photovoltaic MPPT Method Based on Mnemonic Enhancement Optimization with the Use of Past Experience data 10

A Photovoltaic MPPT Method Based on Mnemonic Enhancement Opt...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Xia, Tao Zhang, Zhengjiang Hu, Guiting Huang, Shipei Yan, Zhengbing National-Local Joint Engineering Laboratory of Electrical Digital Design Technology Wenzhou University Wenzhou325035 China

ISBN: (纸本)9781665424233

the output characteristics of photovoltaic cells are easily affected by the external environment, so the study of maximum power point tracking (MPPT) technology is of great significance for improving the energy conversion efficiency of photovoltaic cells. Aiming at the problem that the traditional perturbation observation based MPPT method cannot consider the tracking speed and vibration amplitude at the same time, a mnemonic enhancement optimization (MEO) based MPPT method is proposed. this method preserves the past experience data of MPPT, and uses the experience data to estimate a good starting point for MPPT when the external environment changes. BP neural network and interpolation can be applied for the estimation of a good starting point, which can speed up the procedure of MPPT. Compared with other methods through simulations, the results demonstrate that the proposed method can significantly improve the tracking speed and adapt to severe weather. © 2021 ieee.

关键词： Perturbation techniques

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An Active Vibration control Method for Typical Piping System of Nuclear Power Plant 10

An Active Vibration Control Method for Typical Piping System...

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： Zhang, Xiaomeng Sui, Tao Zhang, Haishuai Zhang, Yanzhu Liu, Lu Zhang, Shuo School of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China School of Marine Science and Technology Northwestern Polytechnical University Xi'an710072 China School of Mathematics and Statistics Northwestern Polytechnical University Xi'an710072 China

ISBN: (纸本)9781665424233

this paper proposes a fractional-order PD controller to suppress the vibration of the typical pipeline system of a nuclear power plant. In view of the characteristics of typical pipeline systems of nuclear power plants, mathematical models are established and dynamic equations are derived to make complex systems digitized for analysis and research. A piping system vibration damping controller based on fractional-order PD control is designed. the fractional-order PD controller introduces a differential order on the basis of the traditional integer-order PD controller to improve the matching degree of the model. Under this system structure, the quadratic performance index is designed, and the particle swarm optimization algorithm is used to optimize the controller parameters to optimize the effect of suppressing vibration. the simulation results show that in the typical pipeline system of nuclear power plant, the fractional-order PD controller designed by this method can suppress the vibration of the system better than the traditional integer-order PD controller. © 2021 ieee.

关键词： Nuclear power plants

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Formation Consensus of Stochastic Multi-agent System based on Probability Density Compensation 10

Formation Consensus of Stochastic Multi-agent System based o...

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： Wang, Jing Zhang, Xuerou Zhou, Jinglin Key Laboratory of Beijing for Fieldbus Technology and Automation North China University of Technology Beijing100144 China College of Information Science and Technology Beijing University of Chemical Technology Beijing100029 China

ISBN: (纸本)9781665424233

Due to the randomness of multi-agent system, it is difficult to achieve strict formation consensus, generally, not all agents in the system can obtain global information. therefore, this paper designs a distributed controller to make multiagent system achieve formation consensus in the sense of probability, which combines two parts of sliding mode controller and probability density function compensator. Sliding mode controller is used for rough tuning, so that the formation of agents can be controlled within a certain range. Probability density function compensator uses the minimum entropy criterion to train the weights, so as to realize the compensation of the random part of the system and play the role of fine tuning. the control algorithm minimizes the entropy of the system output error and optimizes the control effect. Finally, the simulation results show the effectiveness of the proposed method. © 2021 ieee.

关键词： Multi agent systems

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Optimal Adaptive control for Nonlinear Uncertain systems 10

Optimal Adaptive Control for Nonlinear Uncertain Systems

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： Chen, Siyu Na, Jing Huang, Yingbo Yang, Jun Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Kunming650500 China National University of Singapore Department of Biomedical Engineering Singapore117575 Singapore

ISBN: (纸本)9781665424233

How to achieve a compromise between the accuracy of parameter estimation and the robustness of system is still a challenging task in adaptive control field. To address this issue, a novel optimal adaptive control (OAC) strategy is proposed for a model reference adaptive control (MRAC) system with uncertain dynamics. To realize this purpose, a low-pass filter operation is first employed for the linearized system to derive the parameter estimation error information. then, a cost function concerning the tracking error and estimation error is established. then, the MIT rule is introduced to reconstruct a new optimal adaptive law driven by the parameter estimation error information. In this framework, both the tracking error and parameter estimation error can converge to zero simultaneously. the asymptotic stability of the closed-loop system is analyzed in terms of the Lyapunov theorem. Finally, comparative simulation results are provided to exemplify the effectiveness of the proposed control method. © 2021 ieee.

关键词： Model reference adaptive control

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Iterative learning Based Train Stop control with Initial State Shifts for Urban Rail Transit 10

Iterative Learning Based Train Stop Control with Initial Sta...

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： Yu, Ruochuan Tang, Tao Yin, Chenkun Xun, Jing Xi, Jiayi Zheng, Xiaobin State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Advanced Control Systems Laboratory School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China Traffic Control Technology Co. Ltd Beijing100070 China Beijing Transport Institute Beijing100073 China

ISBN: (纸本)9781665424233

In this paper, a partitioned terminal iterative learning control (TILC) strategy for urban rail transit with initial state shifts is proposed to solve the accurate stop problem. A supervised machine learning method is used to pre-processing the historical operation data (i.e. the initial speed and the position data pairs in the stopping stage). And for each category the TILC algorithm is applied, realizing the update of the control law in a small range. Simulation results show that the proposed algorithm can achieve the stop accuracy of ±15cm even though the initial state varies over a certain range during the iterations. this meets the general requirement of accurate train stop for urban rail transit (±30cm). © 2021 ieee.

关键词： Iterative methods

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Improved Repetitive control with Model-Assisted Extended State Observer for Optoelectronic Tracking System 10

Improved Repetitive Control with Model-Assisted Extended Sta...

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： Nie, Kang Li, Zhijun Guo, Tong Mao, Yao Key Laboratory of Optical Engineering Chinese Academy of Sciences Chengdu610209 China Institute of Optics and Electronics Chinese Academy of Sciences Chengdu610209 China University of Chinese Academy of Sciences Beijing100039 China

ISBN: (纸本)9781665424233

the optoelectronic tracking system is a high-precision tracking and positioning device. the uncertainties and disturbances exist in the working process, especially on the moving optoelectronic platforms in recent years. To sufficiently achieve the required motion performance, the suppression of disturbances and the robustness against uncertainties are of increasing importance. In this paper, we propose an improved repetitive control (IRC) method with model-assisted extended state observer to reject periodic and non-periodic disturbances. this two-degree-of-freedom control framework is used with one degree to further estimate and eliminate broadband disturbances and the other to further reject periodic disturbances. IRC can mitigate the magnitude amplification of the non-periodic disturbances caused by conventional repetitive control (CRC). And it only requires the error, input, and output signals of the system without depending on the accurate model parameters. Finally, the effectiveness of the proposed method is verified by simulation and experiment, and the improved performances on estimation accuracy and disturbance suppression are compared in the tip-tilt mirror system. © 2021 ieee.

关键词： State estimation

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Model-free adaptive control for MIMO nonlinear systems under packet dropout and DoS attack 10

Model-free adaptive control for MIMO nonlinear systems under...

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10th ieee data driven control and learning systems conference, ddcls 2021

作者： Zhao, Xuyang Bu, Xuhui Yu, Wei Liang, Jiaqi Zhang, Wenwen School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo454000 China

ISBN: (纸本)9781665424233

the control problem for multiple-input multiple-output (MIMO) nonlinear systems against stochastically occurring packet dropout and periodic denial-of-service (DoS) jamming attacks is studied in this paper. Firstly, two independent Bernoulli distributions are applied to model random packet dropout and periodic DoS attack. then combining with the model, a model-free adaptive control (MFAC) algorithm is put forward. Meanwhile, we analyze the stability of the algorithm theoretically and the results indicated that the tracking error is convergent under the presence of packet dropout and periodic DoS attack. Finally, a numerical example results verify the validity of the algorithm. © 2021 ieee.

关键词： Nonlinear systems

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