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检索条件"任意字段=6th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2017"

共 295 条记录，以下是1-10 订阅

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Proceedings of 2017 ieee 6th data driven control and learning systems conference, ddcls 2017

Proceedings of 2017 IEEE 6th Data Driven Control and Learnin...

引用

6th ieee data driven control and learning systems conference, ddcls 2017

ISBN: (纸本)9781509054619

the proceedings contain 138 papers. the topics discussed include: hidden semi-Markov model based monitoring algorithm for multimode processes;fuzzy adaptive iterative learning control for consensus of multi-agent systems with imprecise communication topology structure;improving reinforcement learning output feedback control for unknown nonlinear pure feedback system;analysis of iterative learning control of an oscillating system with pure delay;data-driven vs model-driven imitative learning;a novel repetitive iterative learning control for linear discrete-time systems with time-iteration-varying reference;incipient fault detection and variable isolation based on subspace decomposition and distribution dissimilarity analysis;active disturbance rejection generalized predictive control and its application on large time-delay systems;a forecasting method of air conditioning energy consumption based on extreme learning machine algorithm;iterative learning control for a class of singular distributed parameter systems;quantitative relationship in terms of time-delay tolerance of two kinds of extended state observers;a bootstrap based virtual sample generation method for improving the accuracy of modeling complex chemical processes using small datasets;boundary tracking control for MIMO PDE-ODE cascade systems via learning control approach;and sampled-data iterative learning control for nonlinear systems with iteration varying lengths.

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data-driven Adaptive Iterative learning Predictive control 6

Data-driven Adaptive Iterative Learning Predictive Control

引用

2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Yunkai Lv Ronghu Chi School of Automation & Electronic Engineering Qingdao University of Science & Technology

ISBN: (纸本)9781509054626

A new data-driven predictive iterative learning control(ILC) is proposed for same category discrete nonlinear systems in this work. the controller design only depends on the input/output data of the system and does not need explicit mathematical model. More prediction information along the iteration axis is utilized in the learning control law to improve the control performance. the applicability of the proposed methods is proved by simulation experiments.

关键词： Predictive iterative learning control data-driven control Nonlinear discrete-time systems

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PID-type Iterative learning control for 2-D Roesser Model 6

PID-type Iterative Learning Control for 2-D Roesser Model

引用

2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Tengfei Xiao Xiao-Dong Li School of Data and Computer Science Sun Yat-Sen University

ISBN: (纸本)9781509054626

In many practical applications, the states, inputs and outputs of the systems show 2-dimensional（2-D） property and operate in a repetitive mode. A PID-type iterative learning control（ILC） is designed in this paper for 2-D system which can be described as a Roesser model and operates in a repetitive mode. the convergence conditions of the control algorithm are *** order to demonstrate the effectiveness of the proposed control method, simulations on a numeric example are performed.

关键词： Iterative learning control 2-D system Roesser model

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Iterative learning State Estimation for Nonlinear Repetitive Process 6

Iterative Learning State Estimation for Nonlinear Repetitive...

引用

2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Yu Hui Ronghu Chi School of Automation & Electronic Engineering Qingdao University of Science & Technology

ISBN: (纸本)9781509054626

this paper explores the question about iterative learning observer design about a kind of nonlinear plants have repetitive operating characteristics. Different from traditional methods, the proposed iterative learning state observer is conducted and updated along the iteration direction. Furthermore, the proposed method has data-driven nature and derives from nonlinear systems directly, where no any model information is required except for the input and output measurements. A simulation case was employed to prove the performance of the given observer.

关键词： Iterative learning Observer Non-linear System Iterative learning Method

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High-order Iterative learning control for Nonlinear systems 6

High-order Iterative Learning Control for Nonlinear Systems

引用

2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Guojun Li Dept.of Computer science and Engineering NMAMIT Nitte

ISBN: (纸本)9781509054626

Iterative learning control demands the same initial state in each iteration, which is equal to the desired state. But this condition is unattainable in practice. this paper addresses the problem of some fixed initial state in iterative learning control for high-order nonlinear system. It presents a new control algorithm. In the process of tracking, this algorithm can rectify the initial errors through a step-by-step rectifying controller. the controller rectifies the xn at first, then xn-1 after finishing the rectifying actions of xn, and so on. All of these rectifying actions are finished in a small interval. Furthermore, the algorithm has shown effective in the improvement of tracking performance through simulation.

关键词： High-order Iterative learning control Convergence Nonlinear System Step-by-step Rectifying

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Model Free Adaptive control for Organic Rankine Cycle Processes 6

Model Free Adaptive Control for Organic Rankine Cycle Proces...

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2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Mingming Lin Ronghu Chi Xiaohong Yin Ximei Liu School of Automation & Electronic Engineering Qingdao University of Science & Technology

ISBN: (纸本)9781509054626

In this paper, a data-driven model free adaptive control(MFAC) scheme, based on a novel transformation and linearization of the evaporator model, is developed for superheating regulation in an organic Rankine cycle(ORC) process. the designing procedures of the proposed approach are presented. the main feature of the method is that the controller design depends only on the measured input pump rotating speed and output superheating. Simulation results demonstrate the effectiveness of the proposed controller.

关键词： data-driven Model Free Adaptive control Organic Rankine Cycle Superheating

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A Novel data-driven Predictive control for Networked control systems with Random Packet Dropouts 6

A Novel Data-driven Predictive Control for Networked Control...

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2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Shuo Zhen Zhongsheng Hou Chenkun Yin Advanced Control Systems Laboratory School of Electronics and Information Engineering Beijing Jiaotong University

ISBN: (纸本)9781509054626

A novel data driven predictive control method for networked control systems（NCSs） is presented, where the network links from sensors to controllers and from controllers to actuators are subject to random packet dropouts. In order to make full use of the I/O data of the controlled system to improve system performance, an improved model-free adaptive predictive control（i MFAPC） method is proposed by modifying the criterion function. then, a networked control scheme is developed based on i MFAPC, whose basic principle is to compensate the lost packets by the corresponding predictive values. Finally, the effectiveness of the proposed control scheme for the packet dropout problem in the networked control system is validated through both simulations and experiments.

关键词： data-driven control Networked control System Random Packet Dropouts Model-free Adaptive Predictive control

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Analysis of Iterative learning control of an Oscillating System With Pure Delay 6

Analysis of Iterative Learning Control of an Oscillating Sys...

引用

2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Chengbin Liang JinRong Wang Wei Wei Department of Mathematics Guizhou University Department of Mathematics Guizhou Minzu University

ISBN: (纸本)9781509054626

By using delayed matrix sine and cosine of polynomial degrees methods, learning updating laws are designed for an oscillating system with pure delay to track the reference accurately. Several convergence results of open-loop, closed-loop and open-closed-loop P-type and D-type convergence results are obtained. Two numerical examples are finally given.

关键词： Oscillating System Iterative learning control Delayed Matrix Convergence Analysis

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Distributed Coverage control of Networked Heterogeneous Robots 6

Distributed Coverage Control of Networked Heterogeneous Robo...

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2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Xiaoxia Han Lei Ma Kun Feng Institute of Systems Science and Technology School of Electrical Engineering Southwest Jiaotong University

ISBN: (纸本)9781509054626

the distributed coverage control of networked heterogeneous mobile robots is proposed. the heterogeneous robots are driven to their centroid of multiplicatively-weighted Voronoi regions under the action of the proposed control law, the target position is modified in real-time based on the density distribution of the environment. Two types driving mechanisms are considered in this paper, different control methods are used to drive different robots to their target positions. Simulative and experimental results are given to verify the effectiveness of the improved coverage algorithm.

关键词： Coverage control Heterogeneous robots Kinematic models

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Distributed Cooperative learning Over Networks via Wavelet Approximation 6

Distributed Cooperative Learning Over Networks via Wavelet A...

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2017 ieee 6th data driven control and learning systems conference (ddcls’17)

作者： Jin Xie Weisheng Chen Hao Dai School of Mathematics and Statistics Xidian University School of Aerospace Science and Technology Xidian University

ISBN: (纸本)9781509054626

this paper investigates the problem of the distributed cooperative learning over networks via the wavelet approximation. On the basis of the wavelet approximation(WA) theory, the novel distributed cooperative learning(DCL) method, called DCL-WA, is proposed in this paper. the wavelet series is used to approximate the function of network nodes. For the networked systems, DCL method is used to train the optimal weight coefficient matrices of wavelet series, so as to get the best approximation function of network nodes. An illustrative example is presented to show the efficiency of the proposed strategy.

关键词： Distributed cooperative learning wavelet approximation networked systems

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