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检索条件"任意字段=8th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2019"

共 336 条记录，以下是51-60 订阅

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Consensus tracking of linear multi-agent systems with exogenous disturbances 8

Consensus tracking of linear multi-agent systems with exogen...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Wang, Tongshu Zhang, Xuxi College of Science Harbin Engineering University Harbin150001 China

ISBN: (纸本)9781728114545

this paper investigates the problem of consensus tracking for linear multi-agent systems with exogenous disturbances, which the disturbances are generated by linear external exosystems. To solve consensus tracking problem, a distributed adaptive controller for each follower has been considered. For the exogenous disturbances caused by the external systems, a disturbance observer is designed to deal with exogenous disturbances. Supposing that the communication graph among followers is undirected. then, by applying the Lyapunov function method, the consensus tracking problem with exogenous disturbances was proved. Finally, a simulation is given to illustrate the effectiveness of our results. © 2019 ieee.

关键词： Multi agent systems

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Disturbance observer-based inverse optimal tracking control of the unmanned aerial helicopter 8

Disturbance observer-based inverse optimal tracking control ...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Ma, Haoxiang Chen, Mou Wu, Qingxian Nanjing University of Aeronautics and Astronautics Jiang Su China

ISBN: (纸本)9781728114545

the attitude and altitude tracking control problem of an unmanned aerial helicopter (UAH) with unknown external disturbances is solved by employing an optimal control method in this paper. An inverse optimal control approach is adopted which avoids solving the associated Hamilton-Jacobi-Bellman (HJB) equation. A disturbance observer-based control (DOBC) method is utilized to deal with the unknown disturbances. To ensure the convergence of all tracking errors, a particular control Lyapunov function is selected via inverse optimal method. the performance of this developed control method is illustrated by simulation results. © 2019 ieee.

关键词： Antennas

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data-driven based iterative learning control for unknown linear discrete-time system by adaptive system identification 8

Data-driven based iterative learning control for unknown lin...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Zhu, Wenbo Fang, Yong Huang, Lixun Shanghai Institute for Advanced Communication and Data Science Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai200444 China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou450000 China

ISBN: (纸本)9781728114545

this paper considers an iterative learning control (ILC) scheme for unknown linear discrete-time system. ILC updates the system input using error information from previous iteration to sequentially improve the tracking performance. the asymptotic convergence may not be guaranteed when the system model information is uncertain. In this paper, we introduce the adaptive Fourier decomposition (AFD) algorithm to deal with the system identification problem. this adaptive approximation algorithm estimates a system representation using input/output data only. the learning gain of ILC satisfying the convergence condition is obtained according to the estimated system parameters. the effectiveness of system approximation and the tracking performance of ILC based on input/output measurements are verified with simulation results. © 2019 ieee.

关键词： Approximation algorithms

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Differentiator-based disturbance observer 8

Differentiator-based disturbance observer

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Li, Xiangyang Gao, Zhiqiang Ai, Wei Tian, Senping School of Automation Science and Engineering South China University of Technology Guangzhou510641 China Center for Advanced Control Technologies Cleveland State University Department of Electrical and Computer Engineering ClevelandOH44115 United States

ISBN: (纸本)9781728114545

the analysis of nonlinear disturbance observer (NDO) is first given in detail and an equivalent differentiator structure is used to explain the NDO. the design procedure of NDO is given according to this equivalent structure. then the structure and principle of the generalized differentiator-based disturbance observer (DBDO) is given and compared with NDO in their structure and algorithm. As one of DBDO, tracking differentiator (TD) based disturbance observer is applied to compare NDO in simulations. Simulations for disturbance estimation show that both NDO and TD based disturbance observer have very effective disturbance estimation performance but the later has less design restriction. © 2019 ieee.

关键词： Nonlinear disturbance observer (NDO) Differentiator-based disturbance observer (DBDO) Tracking differentiator (TD) Disturbance observer-based control (DOBC) NDO disturbance observer design process DIFFERENTIATORS

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Finite-duration consensus of multi-agent systems using a generic attracting law 8

Finite-duration consensus of multi-agent systems using a gen...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Sun, Mingxuan Li, Xing Data Driven Intelligent Systems Laboratory College of Information Engineering Zhejiang University of Technology Hangzhou310023 China

ISBN: (纸本)9781728114545

this paper is concerned with the convergence rate improvement of consensus of multi-agent systems, for which we introduce a generic attracting law (GAL), involving three terms which specify a generic action for improvement of convergence performance. the conventional double power-rate attracting law is modified for forming GAL, by adding a proportional term, and the convergence rate of the system can be dramatically improved. through the two-phase analysis, an estimate for the upper bound of the settling time function is given, by which the obtained upper bound depends upon the initial state, and is finite without regard to the value of the initial state. the GAL is adopted for the purpose of consensus of multi-agent systems. A nonlinear protocol is designed to make the system undertaken achieve finite-duration consensus, and numerical results are presented to validate its effectiveness. © 2019 ieee.

关键词： Multi agent systems

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Time series classification based on FCN multi-scale feature eensemble learning 8

Time series classification based on FCN multi-scale feature ...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Zhou, Wenshuo Hao, Kuangrong Tang, Xuesong Xiao, Yan Wang, Tong Engineering Research Center of Digitized Textile Apparel Technology Ministry of Education College of Information Science and Technology Donghua University Shanghai201620 China

ISBN: (纸本)9781728114545

Time series classification problem (TSC) is of great significance in the fields of finance, health care and environment. the full convolutional network is prominent in the classification of time series, but the feature length of the original data extracted by the network is fixed. Since the highly distinguishable local features in time series may have different scales, this paper proposes a multi-scale feature ensemble full convolutional network (MFCN) to extract different scale features and improve the classification accuracy of the network. Finally, 11 excellent time series classification models were compared on 44 UCR data sets, and the results showed that the proposed method obtained the minimum classification accuracy error in 16 data sets, and the average accuracy was also the highest, reaching 87.7%. © 2019 ieee.

关键词： Time series

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Research and application of active disturbance rejection based iterative learning control for the brushless DC motor 8

Research and application of active disturbance rejection bas...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

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

ISBN: (纸本)9781728114545

though the BLDC motor exhibits high potential for applications in motion control systems with high precision, the nonlinear characteristics of the motor give a big challenge in its application. To compensate the uncertainty and nonlinearity in the motor cycle, especially the torque ripple during commutation, a new algorithm, active disturbance rejection based iterative learning control (ADR-based ILC) is presented to achieve better dynamic characteristics and realize commutation torque ripple reduction. Regarding the motor rotation cycle as the iteration cycle, and the angle position as the space domain, this algorithm is based on a linear iterative extended state observer (LIESO) in the rotation iterative domain, which can estimate explicitly the uncertainty of the BLDC system according to the tracking error during the rotation cycle process. Based on the uncertainty compensation strategy, simulation results show that ADR-based ILC scheme ensures good dynamic performance, robustness, adaptability and demonstrate prominent torque ripple reduction ability. © 2019 ieee.

关键词： Brushless DC motors

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Adaptive iterative learning control of nonlinear systems with input saturation 8

Adaptive iterative learning control of nonlinear systems wit...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Shi, Huihui Chen, Qiang Chen, Kaijie Sun, Mingxuan Data Driven Intelligent Systems Laboratory College of Information Engineering Zhejiang University of Technology Hangzhou310023 China

ISBN: (纸本)9781728114545

this paper presents an adaptive iterative learning control for a class of nonlinear systems with input saturation. the input saturation is approximated by a smooth hyperbolic tangent function based on the mean-value theorem. then, an integral Lyapunov function is constructed to avoid the potential singularity problem caused by the differential of unknown gain functions. A radial basis function neural network (RBFNN) is employed to approximate the unknown system nonlinearity, and the combined adaptive laws are designed to estimate NN weight and the bound of the approximation error, respectively. With the proposed scheme, the tracking error is guaranteed to converge into a neighborhood of zero in the sense of $L^systems$-norm within the finite iterations, and numerical simulations show the effectiveness of the proposed scheme. © 2019 ieee.

关键词： Nonlinear systems

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Adaptive fuzzy control for a constrained robot in the presence of input nonlinearity 8

Adaptive fuzzy control for a constrained robot in the presen...

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8th ieee data driven control and learning systems conference, ddcls 2019

作者： Kong, Linghuan He, Wei Institute of Artificial Intelligence University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9781728114545

An adaptive fuzzy finite-time control policy is developed for an uncertain $n$-link robot with input saturation and time-varying output constraints. Compared with previous works, the introduced finite-time stability criterion is used for the tracking control of the robot. Furthermore, cot-type Barrier Lyapunov functions (BLFs) are introduced for guaranteeing output constraints, which can be considered as a substitution of other BLFs. A fuzzy approximation-based adaptive finite-time control scheme is constructed for stabilizing the robotic system. With Lyapunov theory, it has been proved that all the error signals are semi-global practical finite-time stable (SGPFS). At last, the effectiveness of the proposed scheme is verified by simulation results. © 2019 ieee.

关键词： Lyapunov functions

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Model-free adaptive sliding mode vector control for dynamic positioning podded propulsion motor based on anti-load disturbance 8

Model-free adaptive sliding mode vector control for dynamic ...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Yao, Wenlong Wang, Jiali Pang, Zhen Chi, Ronghu School of Automation and Electrical Engineering Qingdao University of Science and Technology Qingdao266061 China

ISBN: (纸本)9781728114545

this paper is concerned with a model-free adaptive sliding mode (MS) vector controller design for unstable dynamic speed performance caused by load disturbance in dynamic positioning (DP) podded permanent magnet synchronous propulsion motor (PMSPM) control system. PMSPM dynamic speed equation and speed discrete system are first established. then, the sliding mode controller is designed, and the model-free adaptive controller is introduced for the discrete time system considering load disturbance, the ESO algorithm is introduced to estimate the disturbance unknowns and give the pseudo partial derivative estimation algorithm. Finally, a MS vector control scheme for PMSPM is proposed by combining vector control and verified by MATLAB/Simulink. the dynamic speed performance of PMSPM verifies the effectiveness of the controller design. © 2019 ieee.

关键词： Vectors

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