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检索条件"任意字段=9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020"

共 506 条记录，以下是341-350 订阅

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A Simplified data-driven Optimal Iterative learning control based on Iterative Extended State Observer

A Simplified Data-driven Optimal Iterative Learning Control ...

引用

data driven control and learning systems (ddcls)

作者： Wei Ai Peilin Lin Xiangyang Li School of Automation Science and Engineering South China University of Technology Guangzhou China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

Inspired by Active Disturbance Rejection based Iterative learning control (ADR-ILC) and data-driven Optimal Iterative learning control (DDOILC), this paper proposes a simplified data-driven optimal iterative control method based on iterative extended state observer (IESO). Accurate estimation of the system uncertainties is observed by IESO during the iterative process. though considering the uncertainties on iterative dynamic linearization method, it is not needed to deduce a new form of the original iterative pseudo partial derivative (PPD). IESO, undertaking as the tool to estimate the whole uncertainties, is added into the DDOILC control law as a separate part. the whole control law is more intuitive and concise than other IESO based DDOILC method which has modified PPD updating law and control law. At the same time the variable gain control mechanism makes the proposed method demonstrate superiority over ADR-ILC in the case of strong nonlinearity. Simulation shows it that can achieve better performance than DDOILC and the other IESO based DDOILC.

关键词： Uncertainty Iterative learning control Parametric statistics Observers Heuristic algorithms Mathematical model Estimation

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L1-PLS Based on Incremental Extreme learning Machine

L1-PLS Based on Incremental Extreme Learning Machine

引用

data driven control and learning systems (ddcls)

作者： Zhiying Sun Jinglin Zhou College of Information Science and Technology Beijing University of Chemical Technology Beijing

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In order to improve the accuracy of the regression model, an L 1 norm partial least square method (IELM-L 1 -PLS) based on an incremental limit learning machine is proposed. the data processing process of the incremental limit learning machine is nested into the framework based on the L 1 norm partial least square method, and the original data is upgraded by extracting the hidden node output matrix in the incremental limit learning machine, and then Regression analysis was performed on the upgraded data using L 1 -PLS. this method is used for experimental verification of actual data. the results show that the L 1 -PLS method based on the incremental limit learning machine can perform better regression analysis on the data.

关键词： Training Regression analysis Least mean squares methods data mining Analytical models Matrix decomposition Linear programming

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Event-triggered based consensus control for a type of multi-agent systems

Event-triggered based consensus control for a type of multi-...

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data driven control and learning systems (ddcls)

作者： Jiantao Shi Nanjing Research Institute of Electronic Technology Nanjing China Key Laboratory of Intellisense Technology CETC Nanjing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In this note, the consensus control problem has been researched for a type of leader-follower multi-agent systems by using the event-triggered strategy. In order to eliminate continuous information transmission between the neighboring agents or nodes, the consensus controller is constructed by using the estimated state information of neighboring agents instead of their real states. the communication instants are determined by the developed event-triggered strategy to minimize the amount of communication between neighboring agents. A type of error convergence analysis based on Lyapunov function has been provided to prove the bounded convergence of the proposed consensus scheme. Finally, a simulation case is given to verify the effectiveness of the given event-based consensus control strategy.

关键词： Multi-agent systems Topology Symmetric matrices Linear matrix inequalities Information processing control systems Switches

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On the Cumulative Number of Confirmed Cases of 2019-nCoV which Based on data-driven Concepts

On the Cumulative Number of Confirmed Cases of 2019-nCoV whi...

引用

data driven control and learning systems (ddcls)

作者： Xuan Wang Zhihui Yang Anhui University of Finance and Economics Bengbu China

On the basis of data-driven, this paper fitted two models of different states which according to the initial data of China9;s fight against COVID-19 epidemic. Depending on the stage of the outbreak, we applied the ... 详细信息

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

On the basis of data-driven, this paper fitted two models of different states which according to the initial data of China's fight against COVID-19 epidemic. Depending on the stage of the outbreak, we applied the two models to predict the cumulative number of confirmed covid-19 cases in the United States and Italy in the early stages of the outbreak. In the early days of the outbreak, the number of confirmed cases in the United States is expected to reach 250000 to 300,000. And if the control measures are effective, there is a high probability that the number of confirmed diagnoses in Italy will not exceed 210,000. Unity can put the difficult away. We should believe that only when countries respect each other and strengthen cooperation can they finally defeat the epidemic.

关键词： Epidemics Government Table lookup Logistics Curve fitting COVID-19 Viruses (medical)

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Design and Implementation of the PI-type Active Disturbance Rejection Generalized Predictive control

Design and Implementation of the PI-type Active Disturbance ...

引用

data driven control and learning systems (ddcls)

作者： Jia Ren Zengqiang Chen Mingwei Sun Qinglin Sun College of Artificial Intelligence Nankai University Tianjin P. R. China Key Lab of Intelligent Robotics of Tianjin Tianjin P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In order to overcome the limitations of the Active Disturbance Rejection control (ADRC) algorithm in large time-delay systems, and the shortcomings of the online calculation of the PI-type Generalized Predictive control (PI-GPC) algorithm. this paper presents a PI-type Active Disturbance Rejection Generalized Predictive control (PI-ADRGPC) algorithm. Simulation analysis is also carried out for linear systems, nonlinear systems and large time-delay systems. the analysis results show that the proposed algorithm has better dynamic performance and stronger disturbance rejection ability than the traditional ADRC and ADRC-GPC algorithm.

关键词： Prediction algorithms Mathematical model control systems Heuristic algorithms Predictive control Linear systems Transfer functions

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On performance analysis of extended state observer for a class of systems with multiple uncertainties and biased measurement

On performance analysis of extended state observer for a cla...

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data driven control and learning systems (ddcls)

作者： Sen Chen Zhiliang Zhao Wenyan Bai School of Mathematics and Information Science Shaanxi Normal University Xi’an China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

this paper studies the state estimation problem of a class of systems with multiple uncertainties and biased measurement. Since the observability of such system is not satisfied, the estimations for states and uncertainties definitely have biases. For the extended state observer which aims to estimate the system states and the dominant term of uncertainties, the quantitative estimating performance is studied in the paper. Furthermore, the biased estimation error is explicitly shown, which can be derived from the following three parts: 1) the biased measurement; 2) the unobservable dominant uncertainty; 3) the non-dominant term of multiple uncertainties. the theoretical analysis in the paper can help practitioners quantitatively evaluate the effectiveness of the designed extended state observer.

关键词： learning systems control systems conferences

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Event-Triggered Consensus Output Tracking Strategy for Multiagent systems Utilizing Model-Free Adaptive control

Event-Triggered Consensus Output Tracking Strategy for Multi...

引用

data driven control and learning systems (ddcls)

作者： Weizhao Song Jian Feng College of Information Science and Engineering Northeastern University Shenyang P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In this article, a model-free-adaptive-control-based (MFAC-based) event-triggered (ET) consensus output tracking problem for multiagent systems (MASs) is investigated. the dynamic models of agents are unknown, and only a subset of agents can acquire the reference trajectory. the consensus tracking algorithm is designed by the real-time input/output data and pseudo-partial-derivative (PPD), which is an important parameter of MFAC approach. An output observer is built to design the centralized ET mechanism. then, the boundedness analysis that the tracking error is uniformly ultimately bounded (UUB) is given. Finally, a simulation experiment is provided to verify the feasibility of the ET consensus output tracking strategy for MASs.

关键词： Topology Adaptation models Trajectory Observers Real-time systems Protocols Multi-agent systems

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Robust Adaptive control of A Disturbed Chua’s Circuit with Circuit Implementation

Robust Adaptive Control of A Disturbed Chua’s Circuit with ...

引用

data driven control and learning systems (ddcls)

作者： Cheng-Cheng Jiang Xiao-Zheng Jin School of Electrical Engineering and Automation Hefei University of Technology Hefei China School of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China

In this paper, a circuit implementation scheme is designed for the adaptive algorithm applied to the disturbed Chua9;s circuit system. Firstly, in order to effectively suppress the adverse effects of unknown distur... 详细信息

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

In this paper, a circuit implementation scheme is designed for the adaptive algorithm applied to the disturbed Chua's circuit system. Firstly, in order to effectively suppress the adverse effects of unknown disturbances on the system, the input of the system is designed by using the method of adaptive parameter adjustment. then, the asymptotic stability of the ADRC system is proved by lyapunov theorem. Besides, the pure circuit implementation scheme of the control algorithm is given by using the combination of some basic analog components. Finally, the software Multisim is used to do the circuit simulation experiments, and the experiment results show that the circuit design scheme of the algorithm is correct.

关键词： Adaptive systems Circuit synthesis control systems Time-varying systems Integrated circuit modeling Asymptotic stability Adaptation models

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Iterative learning control of the Non-repetitive Continuous-time System

Iterative Learning Control of the Non-repetitive Continuous-...

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data driven control and learning systems (ddcls)

作者： Tingting Zhao Xisheng Dai Su Wang Muhammad Shamorooz Aslam School of Electrical and Information Engineering Guangxi University of Science and Technology Liuzhou P. R. China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

this paper considers the convergence for iterative learning control (ILC) of the non-repetitive continuous-time system. the non-repetitive system is characterized by iteration-varying uncertainties in the plant model matrices, the initial state, disturbances and the desired output during a finite time. We employed the P-type learning law to modify the control input, where the learning gain matrix varies with iteration number, then used λ-norm and Gronwall-Bellman's Lemma to prove iteration-varying state and control input are bounded. Moreover the tracking error can converge to zero when the iteration-varying uncertainties all converge with increasing iteration. Numerical simulation illustrates the effectiveness of ILC scheme.

关键词： Convergence Uncertainty Analytical models Trajectory Numerical models Iterative learning control Heuristic algorithms

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Joint Configuration Optimization of Manipulator at Faulty Time Based on Manipulability Maximization

Joint Configuration Optimization of Manipulator at Faulty Ti...

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data driven control and learning systems (ddcls)

作者： Bei Liu Kene Li Zeng Zhang Qiaoliang Mo Xisheng Dai Hongtao Ye School of Electrical and Information Engineering Guangxi University of Science and Technology Liuzhou China

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

When a redundant manipulator suffers a joint failure, the flexibility of the manipulator operation will be affected, which will result in the failure of the task execution. In order to make the manipulator have more fault-tolerant performance, joint configuration optimization of manipulator at faulty time based on manipulability maximization is proposed. In this paper, the manipulability is used as the fault-tolerant performance index of the manipulator. By constructing the equation between manipulability and joint angles, the optimal joint angle is finally obtained at faulty time, making the manipulator manipulability to be maximized.

关键词： Manipulators Jacobian matrices Fault tolerant systems Fault tolerance Planning Optimization End effectors

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