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检索条件"任意字段=7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018"

共 474 条记录，以下是241-250 订阅

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Iterative learning control for Singular System with An Arbitrary Initial State

Iterative Learning Control for Singular System with An Arbit...

引用

data driven control and learning systems (ddcls)

作者： Mengji Chen Yinjun Zhang Jianhuan Su School of physics and electrical engineering Hechi University Yizhou Guangxi China Aeronautics and Astronautics Engineering Institute Air Force Engineering University Xi’an Shanxi Province China

ISBN: (纸本)9781538626191

In this paper, a class of a class linear singular system with an arbitrary initial state was proposed based on singular value decomposition. A novel generalized theoretical result is presented by using the D-type learning law. We established the convergence conditions of algorithm. By the matrix theory, we give rigorous convergence proof. the effectiveness of the theoretical result is illustrated in two application examples.

关键词： Iterative learning control Signal processing algorithms Convergence Trajectory Iterative algorithms Physics

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Adaptive Iterative learning control Mechanism for Nonlinear systems subject to High-Order Internal Model

Adaptive Iterative Learning Control Mechanism for Nonlinear ...

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data driven control and learning systems (ddcls)

作者： Wei Zhou Miao Yu School of Information Technology Jiangsu Vocational Institute of Commerce Nanjing College of Electrical Engineering Zhejiang University Hangzhou

ISBN: (纸本)9781538626191

this technical note addresses an adaptive iterative learning control (AILC) problem for nonlinear dynamical systems with partially unknown iteration-varying parameter. Referring to the scheme of state-space, an AILC effort is presented for randomly varying reference tracking together with initial shift problem in iteration domain. Furthermore, the AILC technique is extended to systems with several parameters in discussion. A simulation example confirms the validity of the proposed method.

关键词： Trajectory Iterative learning control Target tracking Nonlinear systems Adaptation models Mathematical model Uncertainty

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Rehabilitation Path Planning Based on Human Motion Output and Ergonomic Index Optimization 11

Rehabilitation Path Planning Based on Human Motion Output an...

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

作者： He, Tianyu Yan, Yangben Wang, Gang Liu, Yongbai Liu, Keping Sun, Zhongbo Changchun University of Technology Department of Control Engineering Changchun130012 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Rehabilitation robots help patients perform rehabilitation training according to the planned path, and reasonable planning of the rehabilitation path can enable patients to obtain better rehabilitation effects. In view of the problems of low degree of personification and poor comfort in the path planning of rehabilitation robots. In this paper, the normalized output function for human-like path planning is obtained, which is based on the inherent virtual constraints or output of the human lower limb, and the constraints are optimized through ergonomic index. First, the human body output data of the subject is collected through the optical motion capture system, after that the original normalized output function is obtained by Fourier fitting, and then the constraints are based on ergonomic indicators. Second, the constrained human body output data is calculated by the golden section algorithm, and finally the final human body standardized output function is obtained by Fourier fitting. Last, the standardized output function based on human output is applied in the path planning of rehabilitation robots, which can make the training of rehabilitation robots have a higher degree of human simulation and comfort, so as to achieve better rehabilitation effect. © 2022 ieee.

关键词： Motion planning

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Feedback-Aided PID-type Iterative learning control against Initial State Error

Feedback-Aided PID-type Iterative Learning Control against I...

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data driven control and learning systems (ddcls)

作者： Hongbo Bi Mingxia Yang Jiaquan Chen College of Electrical and Information Engineering Quzhou University Quzhou China

ISBN: (纸本)9781538626191

this paper presents a PID-type ILC (iterative learning control) algorithms for system which undertaken performance tasks repetitively over a pre-specified finite-time interval in the presence of initial state error, and the convergence analysis shows that the tracking error converges to zero asymptotically as time goes to infinity. Furthermore, a kind of initial rectifying strategy is addressed to eliminate the effect of the fixed initial state error, and the limit trajectory is stated. At last, numerical results are addressed to demonstrate the validity of the proposed learning control algorithms.

关键词： Trajectory Convergence Iterative learning control Sun Task analysis Robustness Nonlinear systems

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ILC for a Kind of Linear Switched systems Specified by Random Time-Iteration driven Switching Signals

ILC for a Kind of Linear Switched Systems Specified by Rando...

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data driven control and learning systems (ddcls)

作者： Xuan Yang Xiaoe Ruan School of Science Xi’an Polytechnic University Xi’an School of Mathematics and Statistics Xian Jiaotong University Xi’an

ISBN: (纸本)9781538626191

the note considers an iterative learning control scheme for a kind of switched repetitive systems. the manipulated systems are specified by arbitrary switching signals with respective to both time variable and iteration index. By employing Lebesgue- p norm, the learning performance is analyzed and a sufficient condition of convergence is derived. Results show that the concerned control law works well for tracking problem of the switched systems when the switching rules are expanded to time-iteration domain. Simulation is included to verify the validity of the approach.

关键词： Switches Switched systems Indexes Iterative learning control Electronic mail Convolution

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An Iterative learning controller for Superheat Degree of VCC System

An Iterative Learning Controller for Superheat Degree of VCC...

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data driven control and learning systems (ddcls)

作者： Xiaohong Yin Xinli Wang Ximei Liu Ronghu Chi Mingming Lin Fanglin Liu School of Automation & Electronic Engineering Qingdao University of Science & Technology Qingdao P. R. China School of Control Science and Engineering Shandong University Jinan P. R. China School of Information Science and Engineering Linyi University Linyi P. R. China

the following topics are dealt with: control system synthesis; nonlinear control systems; adaptive control; fault diagnosis; iterative learning control; iterative methods; learning (artificial intelligence); observers... 详细信息

ISBN: (纸本)9781538626191

关键词： Valves Refrigerants Atmospheric modeling data models Heating systems

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data-Based Adaptive Output Feedback Tracking control for a Class of Nonlinear systems

Data-Based Adaptive Output Feedback Tracking Control for a C...

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data driven control and learning systems (ddcls)

作者： Ling Ren Guoshan Zhang School of Electrical and Information Engineering Tianjin University Tianjin P. R. China

ISBN: (纸本)9781538626191

In this paper, we propose an output feedback tracking control scheme for a class of continuous-time nonlinear systems without specific model. A radial basis function neural network (RBFNN) observer is designed to online estimate the unmeasured inner state variables only using the input and output data. Based on the designed RBFNN observer, a sliding mode controller is derived to guarantee that the system states follow the desired trajectories. Simulation results on an example show the effectiveness and tracking performance of the proposed scheme.

关键词： Observers Artificial neural networks Nonlinear systems Adaptive systems Trajectory Output feedback

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Model Free Adaptive control for a Class of Nonlinear systems with Output Saturation

Model Free Adaptive Control for a Class of Nonlinear Systems...

引用

data driven control and learning systems (ddcls)

作者： Qingfeng Wang Xuhui Bu Yanling Yin School of Electrical Engineering Henan Polytechnic University Jiaozuo

ISBN: (纸本)9781538626191

the problem of model free adaptive control algorithm for a class of nonlinear systems with output saturation constraints is considered in this paper. Based on the compact form dynamic linearization data model, a modified model free adaptive control algorithm using saturated system output is constructed. A sufficient condition for guaranteeing the stability of the modified algorithm is given and the convergence of the tracking error is proved. It is shown that the model free adaptive control using saturation output can also guarantee the convergence of the tracking error. the theoretical results are validated by a numerical example.

关键词： Nonlinear systems Mathematical model control systems Adaptation models Adaptive control Heuristic algorithms data models

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Sampled-data control for T-S Fuzzy systems with Quantized Signals

Sampled-data Control for T-S Fuzzy Systems with Quantized Si...

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data driven control and learning systems (ddcls)

作者： Xiaojing Han Ningwei Cheng Yuechao Ma School of Science Yanshan University P. R. China

ISBN: (纸本)9781538626191

this paper deals with the problem of sampled-data control for T-S fuzzy systems with quantized signals. Based on the constructed Lyapunov-Krasovskii functional(LKF), Jensen's inequality and Free weight matrix, some sufficient conditions are obtained in the form of linear matrix inequalities(LMIs). By combining the input delay approach and dynamic quantizer, the sampled-data controller is designed to guarantee that T-S fuzzy systems with quantized signals is asymptotically stable. Finally, a numerical example is presented to verify the feasibility and effectiveness of the proposed methods.

关键词： Fuzzy systems Delays Quantization (signal) Computational modeling Symmetric matrices control systems Linear matrix inequalities

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Decentralized Robust Adaptive Output-Feedback control for A Class of Large-Scale Stochastic Time-Delay Nonlinear systems

Decentralized Robust Adaptive Output-Feedback Control for A ...

引用

data driven control and learning systems (ddcls)

作者： Qian Wang Qiangde Wang Zhengqiang Zhang Chunling Wei Department of Automation Qufu Normal University Rizhao P.R. China

ISBN: (纸本)9781538626191

the paper solves the problem of decentralized robust adaptive output-feedback control for a class of large-scale stochastic time-delay nonlinear systems. Simulation results show that the closed-loop system is globally stable in probability and the output signals can converge to a small neighborhood of the origin in probability under some milder conditions.

关键词： Adaptive systems Power system dynamics Delays Closed loop systems Nonlinear dynamical systems Symmetric matrices

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