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An Iterative Learning Approach for Train Trajectory Tracking control 1

IFAC Proceedings Volumes 2011年第1期44卷 14916-14921页

作者： Heqing Sun Zhongsheng Hou Tao Tang Advanced Control Systems Lab Beijing Jiaotong University Beijing China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

Abstract This work presents an iterative learning control (ILC) based automatic train operation (ATO) algorithm to address trajectory tracking problem. The train motion dynamics is first described by a modified discrete model with position as its independent variable, since train motion dynamics repeats along position axis more exactly. ILC method is combined with error feedback to achieve trajectory tracking. Meanwhile, the case with input constraints is considered. Rigorous theoretical analysis confirms that proposed algorithm can guarantee the asymptotic convergence of train speed to desired profile along iteration axis. Its effectiveness is further verified through case studies with intensive simulations.

关键词： Iterative Learning control Feedback-feedforward control Input Constraints Automatic Train Operation Trajectory Tracking

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Data driven multiagent systems consensus tracking using model free adaptive control 28

Data driven multiagent systems consensus tracking using mode...

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28th Chinese control and Decision Conference, CCDC 2016

作者： Xuhui, Bu Zhongsheng, Hou Jiaqi, Liang Piaopiao, Xu School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo454000 China Advanced Control Systems Lab School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9781467397148

This paper proposes a distributed model free adaptive control scheme that can be applied to multi-agent systems to solve consensus tracking problem under the fixed communication topology. The agent's dynamics are modeled by unknown nonlinear functions. In addition, the desired consensus trajectory is only accessible to a subset of the followers. By introducing the concept pseudo-partial derivative, the dynamical linearization model of each agent has been established and then the distributed model free adaptive control scheme has been designed to enable all agents to achieve the desired trajectories. The main feature of the approach is that consensus tracking control can be solved only depending on the I/O data of each agent. By the theoretical analysis, it is shown that tracking error is convergent and output and control input sequences are bounded. An illustrative example is given to demonstrate the effectiveness of the proposed design methods. © 2016 IEEE.

关键词： Consensus tracking Data driven design Model Free Adaptive control Multi-agent systems

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Designing an Undamped Oscillator Using Fractional Order Delayed systems

Designing an Undamped Oscillator Using Fractional Order Dela...

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International Conference on control, Engineering & Information Technology (CEIT)

作者： Moein Allahdinian Hasaruyeh Mohammad Haeri Advanced Control Systems Lab. Sharif University of Technology Tehran Iran

ISBN: (纸本)9781538676424

This paper studies undamped oscillation in fractional order delayed systems. Laplace transformation and Mittag-Leffler function is adopted to solve the fractional order delayed differential equations. We seek to find a relation between the system parameters and the oscillation frequency and then adjust the system's coefficients so that all the roots of the characteristic equation, except the roots on the imaginary axis, lie on the left-hand side of the imaginary axis. We also obtain amplitude of the oscillation using the asymptotic behavior of the Mittag-Leffler function and calculate the transfer function residue at the frequency of oscillation. Since the other roots of the characteristic equation lie in the left-hand side of the imaginary axis, their contribution decay to zero as time tends to infinity. Finally, numerical simulation results are provided to verify the analysis.

关键词： Oscillators Mathematical model Asymptotic stability Differential equations Stability analysis control engineering Information technology

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Iterative learning control based ramp metering tracking iteration-varying trajectories with internal model

Iterative learning control based ramp metering tracking iter...

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2009年中国控制与决策会议(2009 Chinese control and Decision Conference)

作者： Jingwen Yan Zhongsheng Hou Advanced Control Systems Lab Beijing Jiaotong University Beijing 100044 China

In this work, we focus on iterative learning control (ILC) based ramp metering for tracking iteration-varying trajectories which are described by an internal model between two consecutive iterations. The internal model is inserted into the ILC law, which is different from the classical one. A dynamic linearization of the freeway macroscopic traffic flow model along the iteration axis and lifting technique are used for theoretical analysis, which eliminate the needs for identical initialization condition and -norm that are two fundamental ILC issues in the time domain. Intensive simulations show the superiority of this control strategy compared with the classical ILC.

关键词： Iterative Learning control ramp metering iteration-varying trajectories internal model

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MFAC-based balance control for freeway and auxiliary road system with multi-intersections

MFAC-based balance control for freeway and auxiliary road sy...

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Asian control Conference

作者： Zhihui Cheng Zhongsheng Hou Shangtai Jin Advanced Control Systems Lab. Beijing Jiaotong University Beijing China

ISBN: (纸本)9781479978632

In order to solve the traffic resources wasting problem caused by the unbalanced density between freeway and auxiliary road, a model free adaptive control (MFAC) based balance control scheme is proposed for freeway and auxiliary road system with multi-intersections. Only depending on the traffic flow rate as input data and the density of freeway and intersections of auxiliary road as output data, the proposed control scheme guarantees density balance between freeway and auxiliary road. The simulation results on the MATlab platform show the effectiveness of the proposed control scheme.

关键词： Traffic control Roads Mathematical model Simulation Timing Estimation

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DualRefine: Self-Supervised Depth and Pose Estimation Through Iterative Epipolar Sampling and Refinement Toward Equilibrium

DualRefine: Self-Supervised Depth and Pose Estimation Throug...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Antyanta Bangunharcana Ahmed Magd Kyung-Soo Kim Mechatronics Systems and Control Laboratory Vehicular Systems Design and Control Lab Korea Advanced Institute of Science and Technology (KAIST) Republic of Korea

Self-supervised multi-frame depth estimation achieves high accuracy by computing matching costs of pixel correspondences between adjacent frames, injecting geometric information into the network. These pixel-correspondence candidates are computed based on the relative pose estimates between the frames. Accurate pose predictions are essential for precise matching cost computation as they influence the epipolar geometry. Furthermore, improved depth estimates can, in turn, be used to align pose estimates. Inspired by traditional structure-from-motion (SfM) principles, we propose the DualRefine model, which tightly couples depth and pose estimation through a feedback loop. Our novel update pipeline uses a deep equilibrium model framework to iteratively refine depth estimates and a hidden state of feature maps by computing local matching costs based on epipolar geometry. Importantly, we used the refined depth estimates and feature maps to compute pose updates at each step. This update in the pose estimates slowly alters the epipolar geometry during the refinement process. Experimental results on the KITTI dataset demonstrate competitive depth prediction and odometry prediction performance surpassing published self-supervised baselines 1 1 https://***/antabangun/DualRefine.

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Tracking and Disturbance Rejection in Non-minimum Phase systems 33

Tracking and Disturbance Rejection in Non-minimum Phase Syst...

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第三十三届中国控制会议

作者： ZHAO Shen SUN Li LI Donghai GAO Zhiqiang Facility for Rare Isotope Beams Michigan State University State Key Lab of Power Systems Department of Thermal EngineeringTsinghua University Center for Advanced Control Techniques Cleveland State UniversityClevelandOH 44115United States

ISBN: (纸本)9781479947249

This paper concerns with the problems of tracking control and disturbance rejection for two types of non-minimum phase(NMP) systems associated with the right half plane(RHP) zeroes and with time delay,*** the achievable closed-loop bandwidth for such systems is usually very limited,obtaining good tracking and disturbance rejection becomes great challenges in the control *** disturbance rejection,this paper mainly focuses on the method of active disturbance rejection control(ADRC),where modifications in tuning,in ESO and in ADRC structure are made to make the solutions more effective for the NMP systems;for fast tracking,a unique feedforward design is combined with ADRC solution to overcome the bandwidth *** proposed methods are validated in simulation with satisfactory performance and give practitioners a set of tools to deal with the problems of the NMP systems.

关键词： non-minimum phase system,time delay,active disturbance rejection control,feedforward control,combined design

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A study of fuzzy hysteresis modeling and control of a shape emory wire actuator

A study of fuzzy hysteresis modeling and control of a shape ...

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21st Biennial Conference on Mechanical Vibration and Noise, presented at - 2007 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2007

作者： Mehrabian, Ali Reza Hashemi, S. Vahid Williams, Eric Elahinia, Mohammad Advanced Dynamic and Control Systems Lab. School of Mechanical Engineering University of Tehran P.O.Box: 14875-347 Tehran Iran Dynamic and Smart Systems Laboratory University of Toledo Nitschke Hall 4045 OH 43606 United States

ISBN: (纸本)0791848027

This paper describes the development of fuzzy systems for modeling the hysteresis behavior of shape memory alloy (SMA) actuators. Due to their simplicity and ease of actuation, SMA actuators are very attractive for applications such as miniature robots for micro manufacturing. However, SMAs have not been widely used for motion control applications due to their nonlinear behavior and control difficulties. One approach to design a position controller for SMA systems is to employ an inverse-model of the system in the control loop to compensate the hysteresis properties of the material. Fuzzy systems, due to their nonlinear learning and adaptation abilities, are good candidates for obtaining inverse-models. In this paper two fuzzy modeling approaches are employed and compared to develop a model for a SMA wire actuator. A set of experiments are conducted to generate the training data. The test stand includes a Nickel-Titanium (TiNi) SMA wire, a position sensor, a bias spring and a current amplifier. By comparing the performance of the two employed fuzzy modeling techniques, it is revealed that the approach based on fuzzy Gustafson-Kessel (GK) clustering shows a better performance in the modeling of the hysteresis in the SMA wire. Thus, GK clustering algorithm is employed to develop the inverse-model for the SMA. The reported results demonstrate the ability of the employed fuzzy algorithm for modeling the hysteresis in the system, and the merits of the introduced inverse-model in the control of the position of the SMA. Copyright © 2007 by ASME.

关键词： Shape memory effect

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Dual-stage Optimal Iterative Learning control for Nonlinear Non-affine Discrete-time systems

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自动化学报 2007年第10期33卷 1061-1065页

作者： CHI Rong-Hu HOU Zhong-Sheng Advanced Control Systems Lab School of Electronics and Information Engineering Beijing Jiaotong University Beijing 100044 Institute of Autonomous Navigation and Intelligent Control School of Automation and Electronics Engineering Qingdao University of Science and Technology Qingdao Shandong 266042

根据沿着重复轴的一种新动态 linearization 技术，双阶段的最佳的反复的学习控制为非线性、非仿射的分离时间的系统被介绍。双阶段显示二个最佳的学习阶段分别地被设计反复地改进控制输入顺序和学习获得。主要特征是控制器设计和集中... 详细信息

根据沿着重复轴的一种新动态 linearization 技术，双阶段的最佳的反复的学习控制为非线性、非仿射的分离时间的系统被介绍。双阶段显示二个最佳的学习阶段分别地被设计反复地改进控制输入顺序和学习获得。主要特征是控制器设计和集中分析仅仅取决于动态系统的 I/O 数据。换句话说，没有知道系统的任何另外的知识，我们能容易选择控制参数。模拟学习沿着重复轴说明介绍方法的几何集中，在哪个马路的一个例子控制为它的内在的工程重要性是引人注目的交通反复的学习。

关键词：非线性系统离散时间系统自适应控制迭代学习控制匝道交通调节

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Na?ve Bayes Based Fault Classification Applied to a Metro Vehicle

Na?ve Bayes Based Fault Classification Applied to a Metro Ve...

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第30届中国过程控制会议（CPCC 2019）

作者： Jingyu Liu Xian Yu Shangtai Jin Advanced Control Systems Lab School of Electric and Information Engineering Beijing Jiaotong University

In the train operation process, metro vehicle log records a series of data information in real *** the large quantity and high complexity in structure for the data information, it is difficult to directly classify the data included in the vehicle log and to recognize the fault information conveyed by those data relying on *** way by experience would bring about the problems of low accuracy, low efficiency and high *** overcome the problems, a fault classification method based on Na?ve Bayes(NB) algorithm is first applied in this paper to classify the data in the vehicle *** classifier is trained and built with 8 nominal attributes of metro vehicle log, where category with the highest conditional probability is considered as the category of *** vehicle log of the train CD1111 is used to be classified and an accuracy of approximate 98.14% is obtained, which demonstrates the effectiveness of NB algorithm.

关键词： fault classification Na?ve Bayes metro vehicle log

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