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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71-80 订阅

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Model Free Adaptive Perimeter control for Two-Region Urban Traffic System with Input and Output Constraints 7

Model Free Adaptive Perimeter Control for Two-Region Urban T...

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Lei, Ting Hou, Zhongsheng Beijing Jiaotong Univ Adv Control Syst Lab Beijing 100044 Peoples R China

ISBN: (纸本)9781538626184

Recent studies on urban traffic systems have shown that there exists a well-defined macroscopic fundamental diagram (MFD) in well-partitioned homogenous regions, which depicts a unimodal and low-scatter relationship between accumulation and trip completion flow. In this paper, a new type of data driven control method called model free adaptive control with input and output constraints (IOC-MFAC) is utilized for perimeter control for two-region urban traffic system, using MFD to choose the desired number of vehicles and generate the output data of the urban traffic system. Different from the protype scheme of MFAC, in this work, the constraints of perimeter control input and the urban traffic system's output are considered. A key advantage of the proposed method is that only the input and output data of the urban traffic system is needed to design the perimeter controller. the effectiveness of IOC-MFAC method is tested via numerical simulation, and the result shows that it works better than some other commonly used perimeter control strategies.

关键词： Macroscopic fundamental diagram (MFD) model free adaptive control with input and output constraints (IOC-MFAC) perimeter control

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A New Measure of Dynamic Similarity for Nonlinear systems based on Gap Metric and Deterministic learning theory 7

A New Measure of Dynamic Similarity for Nonlinear Systems ba...

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Chen, Danfeng Wang, Cong Zhu, Wenbo Foshan Univ Sch Automat Foshan 528231 Peoples R China South China Univ Technol Sch Automat Sci & Engn Guangzhou 510000 Guangdong Peoples R China

ISBN: (纸本)9781538626184

For nonlinear dynamical systems, structural stability is a fundamental concept. It provides a qualitative tool for analyzing the equivalent relation between a nonlinear dynamical system and its perturbed system. Currently, most researches about structural stability, including some applications in practical systems, are mainly limited to qualitative analysis. In this paper, our focus is on the quantitative property of structural stability. A new measure will be proposed from the perspective of structural stability and gap metric under the Deterministic learning theory, which provides more incentives for further applications in pattern recognition, classification as well as fault detection. Simulation studies are included to further demonstrate the effectiveness of this measure.

关键词： similarity measure nonlinear system structural stability gap metric deterministic learning

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On the Design and Analysis of a learning control Algorithm for Point-to-point Tracking Tasks 7

On the Design and Analysis of a Learning Control Algorithm f...

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Lin, Na Chi, Ronghu Zhang, Ruikun Qingdao Univ Sci & Technol Sch Automat & Elect Engn Qingdao 266042 Peoples R China Qingdao Univ Sci & Technol Sch Math & Phys Qingdao 266042 Peoples R China

ISBN: (纸本)9781538626184

A simple iterative learning control approach is proposed to track specific target points in this work. For a general linear system, a P-type point-to-point ILC and a PD-type point-to-point ILC laws are designed, respectively. the two control laws only use the tracking error at the specified point to update the input signal at the corresponding specified point. the input signal between two consecutive specified points remains the same as the input signal at the previous specified point. the proposed method has the advantages of simple structure and easy application. the convergence analysis and simulation results further confirmed the availability of the method.

关键词： Iterative learning control Point-to-point P-type PD-type

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Adaptive Natural Policy Gradient in Reinforcement learning 7

Adaptive Natural Policy Gradient in Reinforcement Learning

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Li, Dazi Qiao, Zengyuan Song, Tianheng Jin, Qibing Beijing Univ Chem Technol Inst Automat Beijing 100190 Peoples R China

ISBN: (纸本)9781538626184

In recent years, the policy gradient method in intensive learning has attracted wide attention with its good convergence performance. At the same time, regulation of hyper parameters is also a matter of concern. Based on the advantages of Actor-Critic structure (AC), the Natural-Gradient Actor-Critic algorithm (NAC) in the discount model is studied in this article. then the Natural-Gradient Actor-Critic with ADADELTA (A-NAC) algorithm is proposed. the use of ADADELTA is adapted to adjust the learning rate in the actor network, and further improves the convergence speed of the NAC algorithm. Simulation results show that NAC/A-NAC have better learning efficiency and faster convergence rate than regular gradient AC methods.

关键词： Actor-Critic natural gradient adadelta adaptive value function approximation reinforcement learning

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A Nonlinear Self-tuning control Method Based on Neural Wiener Model 7

A Nonlinear Self-tuning Control Method Based on Neural Wiene...

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Zhang, Bi Zhao, Xin-Gang Xu, Zhuang Zhao, Ming Chinese Acad Sci Shenyang Inst Automat State Key Lab Robot Shenyang Liaoning Peoples R China

ISBN: (纸本)9781538626184

In this work, a novel nonlinear self-tuning adaptive control scheme based on the neural Wiener model has been proposed to copy with a class of nonlinear uncertain systems. First the parameterization model with uncertain parameters is derived based on a linear transfer function model followed by neural networks. then based on the performance index, the adaptive control strategy includes the system parameters identification and the control law calculation. Since the networks are linearly described by some basis functions, the closed-loop system stability can be ensured under some realistic assumptions. Finally, the proposed controller is applied to a pH control problem. the simulation results have demonstrated that the proposed nonlinear self-tuning control method is applicable, especially for its reliable set-point tracking and adaptive abilities.

关键词： Wiener models self-tuning control neural networks closed-loop stability pH control

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High-Precision Tracking of Piezoelectric Actuator Using Dual-Loop Iterative learning control 7

High-Precision Tracking of Piezoelectric Actuator Using Dual...

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Jian, Yupei Kang, Xin Yang, Wanqiu Min, Da Huang, Deqing Southwest Jiaotong Univ Sch Elect Engn Chengdu 610097 Sichuan Peoples R China

ISBN: (纸本)9781538626184

Suffering from rate-dependent hysteretic nonlinearity, accurate positioning of nanopositioning stage driven by piezoelectric actuators(PEAs) is hard to achieve and effective controllers are urgently needed. In this paper, by assuming that the model of PEA takes a Hammerstein structure, a dual-loop iterative learning control (ILC) scheme is designed to deal with both input hysteresis and linear dynamics of system synchronously. the merit of this controller lies in that, accurate system models are not prerequisite so that the control process is greatly simplified. As a comparison, an extra experiment using single loop ILC is performed to manifest the efficacy of the proposed algorithm. Simulation results show that the dual-loop ILC scheme is superior to the single loop ILC scheme in terms of convergence speed and control accuracy.

关键词： piezoelectric actuator tracking precision dual-loop iterative learning control hysteresis

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Adaptive Neural Network control For Vehicle Active Suspension System with Unknown Dead-Zones 7

Adaptive Neural Network Control For Vehicle Active Suspensio...

引用

ieee 7th data driven control and learning systems conference (ddcls)

作者： Zhang, Yan-Qi Liu, Lei Liu, Yan-Jun Liaoning Univ Technol Coll Sci Jinzhou 121001 Peoples R China

ISBN: (纸本)9781538626184

this paper presents the development of an adaptive neural network (NN) control method for non-linear quarter-vehicle model which has the characteristics of road disturbance, parameter uncertainties and unknown dead-zone. Considering the dead-zone slopes as a model uncertainty, an adaptive NN control scheme is developed depending on backstepping technique. In this paper, uncertain non-linear functions in suspension systems are estimated by NNs. then again, the minimal learning parameters can ensure that the computation and the complexity of system are exceedingly reduced. the stability and the signals boundedness of vehicle suspension system are proved. Finally, a given simulation example shows the feasibility of the designed approach.

关键词： Active suspension systems adaptive neural network control dead-zone inputs road disturbance

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A Modified Q-Filter Model-Inverse Based ILC and Its Application on PMLSM 7

A Modified Q-Filter Model-Inverse Based ILC and Its Applicat...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Cao, Jun Liu, Yang Li, Li Peng, Xiuyan Harbin Inst Technol Ctr Ultra Precis Optoelect Instrument Harbin 150001 Heilongjiang Peoples R China Harbin Engn Univ Coll Automat Harbin 150001 Heilongjiang Peoples R China

ISBN: (纸本)9781538626184

Iterative learning control (ILC) is essential for the achievement of high servo performance for linear motors. this paper investigates a modified Q-filter model-inversion based ILC. Compared to existing model-inversion based ILC algorithms, two distinct features make the modified algorithm appealing: 1) the tradeoff that must be made by the traditional Q-filter model-inversion based ILC between robustness and converged error is removed. 2) the robustness to uncertainties is enhanced without the deterioration of asymptotic. the effectiveness and superiority of the proposed Q-filter are illustrated by both theoretical analysis and experimental results.

关键词： Iterative learning control Wafer stage Linear motor Model-inverse iterative learning control

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Evolutionary Game Gynamics driven by Heterogeneous Self-learning Rules 7

Evolutionary Game Gynamics Driven by Heterogeneous Self-lear...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Zhou, Lei Wu, Bin Vasconcelos, Vitor V. Wang, Long Peking Univ Coll Engn Ctr Syst & Control Beijing 100871 Peoples R China Beijing Univ Posts & Telecommun Sch Sci Beijing 100876 Peoples R China Princeton Univ Dept Ecol & Evolutionary Biol Princeton NJ 08544 USA

ISBN: (纸本)9781538626184

How to achieve full cooperation among large numbers of individuals is essential for both artificial and biological systems. learning rules (or updating rules), which specify how individuals change their behavior over time, are vital to probe this problem. Here, we incorporate individual heterogeneity into the self-evaluation process and propose the heterogeneous self-learning dynamics. When the selection intensity is weak, we analytically derive that the final outcomes of the heterogeneous dynamics can be obtained by combining the outcomes of all the corresponding homogeneous dynamics in well-mixed populations. Meanwhile, a simple condition is found which tells whether one behavior will be more abundant than the other in the long run. All of our analytical results are verified by simulations. Our work thus reveals some interesting characteristics of heterogeneous self-learning dynamics.

关键词： Cooperation Self-learning rules Evolutionary dynamics Game theory

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Iterative learning Identification for Discrete Parabolic Distributed Parameter systems 7

Iterative Learning Identification for Discrete Parabolic Dis...

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ieee 7th data driven control and learning systems conference (ddcls)

作者： Liu, Lanlan Dai, Xisheng Zhou, Xingyu Yu, Shali Guangxi Higher Educ Inst Key Lab Ind Proc Intelligent Control Technol Liuzhou 545006 Peoples R China Guangxi Univ Sci & Technol Sch Elect & Informat Engn Liuzhou 545006 Peoples R China South China Univ Technol Guangzhou Coll Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781538626184

this paper presents an iterative learning identification scheme for discrete parabolic distributed parameter systems with unknown curve surface parameters. the method achieves identification through iterative learning control concepts, a P-type learning identification controller is employed to estimate the spatial-temporal varying curve surface iteratively. then, the sufficient convergence conditions for identification error in the sense of L-2 norm has been presented through rigorous analysis. In the end, numerical simulations are shown to illustrate the effectiveness of the proposed learning identification algorithm.

关键词： Iterative learning identification discrete distributed parameter systems learning convergence

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