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International Conference on Communication, Electronics, and Automation Engineering, 2012

作者： Zhang, Chao Liu, Shao Jie Zhao, Yu Ming Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai 200240 China

ISBN: (纸本)9783642316975

In this paper an algorithm has been presented to remove the shadow from images, which includes two steps. First step is to detect shadow regions using physical features of shadow for an initial result with less shadow. Two properties of shadow, luminance and gray density are taken into account, to get the primary result. The second step is based on morphological methods. Using the similarity of gray density and the gradient value, a refined result can be obtained with the help of real edge of the object and the direction to expand. © 2013 Springer-Verlag.

关键词： Tracking (position)

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Synthesis of Failure-Robust Plans for Multi-Robot systems Under Temporal Logic Specifications 19

Synthesis of Failure-Robust Plans for Multi-Robot Systems Un...

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19th IEEE International Conference on Automation Science and Engineering, CASE 2023

作者： Huang, Feifei Li, Shaoyuan Yin, Xiang Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Department of Automation Shanghai200240 China

ISBN: (纸本)9798350320695

In this study, we address the multi-robot path planning problem for tasks specified by linear temporal logic (LTL) formulae. Unlike existing studies, we take into account the possibility of robot failures, where a failed robot can no longer contribute to the completion of the LTL task. Our objective is to find a failure-robust path, which ensures that the LTL task can always be fulfilled, even if a maximum number of robots fail at any point during execution. To achieve this, we extend the mixed-integer linear programming (MILP) approach to the failure-robust setting. To overcome the computational complexity, we identify a fragment of LTL formulae called the free-union-closed LTL, which allows for more scalable synthesis without considering the global combinatorial issue. We present case studies to demonstrate our findings. Our approach provides a novel solution to the problem of multi-robot path planning under robot failures, offering a practical and efficient way to achieve robustness in the face of unforeseen events. © 2023 IEEE.

关键词： Multipurpose robots

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Multi-rate model predictive control to reject periodic disturbance with reduced ripple

Multi-rate model predictive control to reject periodic distu...

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3rd IFAC Conference on Intelligent control and Automation Science, ICONS 2013

作者： Jin, Mengke Li, Dewei Xi, Yugeng Department of Automation Shanghai Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University 200240 China

ISBN: (纸本)9783902823458

Repetitive model predictive control is an effective method to track a periodic signal as well as reject a periodic disturbance. However, since repetitive controller uses discrete-time model, there always exists ripple when controlling a continuous system with periodic disturbance. This paper proposes a new way for repetitive model predictive control by using multi-rate model. Due to the multi-rate model, the model predictive controller can optimize the system outputs during the period between two sampling times, and then provide a more delicate control action, which can result in the reduced ripple. The simulation demonstrates its effectiveness. Copyright © 2013 IFAC.

关键词： Model predictive control

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control of single-phase CHB grid-connected photovoltaic system under non-uniform irradiation conditions

Control of single-phase CHB grid-connected photovoltaic syst...

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3rd IFAC Conference on Intelligent control and Automation Science, ICONS 2013

作者： Ma, Chao Wu, Jing Li, Ning Li, Shaoyuan Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783902823458

This paper proposes a novel MPPT method, which will provide a correct tracking direction under the condition of non-abrupt atmospheric changes, especially non-irradiation conditions. We also present a model predictive control method based on a cost function, which help to derive the predictions for each possible switching state. The control scheme obtained is capable of controlling the dc-link current to a desired MPPT reference current, while injecting sinusoidal current to the grid with reduced total harmonic distortion. Finally, the simulation results illustrate the effectiveness of our proposed method. Copyright © 2013 IFAC.

关键词： Model predictive control

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Formation control for Unmanned Surface Vehicles Based on Integrative APF and MPC

Formation Control for Unmanned Surface Vehicles Based on Int...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Li, Weilin Wu, Jing Long, Chengnian Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

This paper takes the dual water jet propulsion USV as the research object, and studies formation obstacle avoidance optimization problem. An integrative APF algorithm is proposed to merge path planning and trajectory tracking into one optimization problem, where adaptive searching step is adopted to guarantee that the planned trajectory is reachable. In addition, a distance-triggered codesign of integrative APF and MPC is presented to maintain formation during the obstacle avoidance process. Finally, the results in MATLAB simulation demonstrate the validity and efficiency of the algorithm. © 2022 IEEE.

关键词： MATLAB

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Event-triggered decentralized predictive control for coupled linear systems 36

Event-triggered decentralized predictive control for coupled...

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第36届中国控制会议

作者： YUAN Fenglin ZOU Yuanyuan NIU Yugang Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Key Laboratory of System Control and Information Processing Department of AutomationShanghai Jiao Tong University

ISBN: (纸本)9781538629185

In this paper,we consider the problem of predictive control for a class of coupled linear *** solving a set of local optimization problems with decoupled cost functions and constraints,an event-triggered decentralized predictive control(DPC) scheme is *** event-triggering conditions only involving local information of every subsystem is derived and sufficient conditions of the recursive feasibility and the stability of close-loop control systems are also ***,a numerical example is given.

关键词： Coupled Linear systems Decentralized Predictive control(DPC) Event-Triggered

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A Modified RC and Diode Co-Triggered ESD Clamp Circuit 1

A Modified RC and Diode Co-Triggered ESD Clamp Circuit

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1st Annual International EOS/ESD Symposium on Design and system, IEDS 2020

作者： Yang, Zhaonian Zhang, Yibo Mao, Pan Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

ISBN: (纸本)9781585373284

This paper presents a new ESD clamp circuit which is co-triggered by RC and diode. It is immune to the false triggering caused by fast power-up events due to the diode detection mechanism. With the addition of a common source amplifier, the detection signal is enhanced, and the clamp device is turned on more quickly. The proposed circuit is designed in a 0.18 μm 1.8-V CMOS process and verified by numerical simulation. The characteristics and improvements of the new circuit are discussed. © 2021 EOS/ESD ASSOCIATION INC.

关键词： Diodes

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Urban traffic flow prediction based on road network model

Urban traffic flow prediction based on road network model

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2012 9th IEEE International Conference on Networking, Sensing and control, ICNSC 2012

作者： Xu, Yanyan Kong, Qing-Jie Lin, Shu Liu, Yuncai Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai 200240 China

ISBN: (纸本)9781467303880

This paper addresses an issue of short-term traffic flow prediction in urban traffic networks with traffic signals in intersections. An effective spatial prediction approach is proposed based on a macroscopic urban traffic network model. In contrast with other time series based or spatio-temporal correlation methods, this research focuses on the substantial mechanism of vehicles transmission on road segments and the spatial model of the entire urban network. Furthermore, this approach employs a simple speed-density model based on the macroscopic fundamental diagram (MFD) to obtain a more accurate vehicle travel time on the link. Finally, the microscopic traffic simulation software, CORSIM, is adopted to simulate the real urban traffic, and the proposed method is used to predict the traffic flows generated by CORSIM. The simulation results illustrate that our approach performs effective prediction timely in the rush hours, as well as the suddenly changed traffic states. © 2012 IEEE.

关键词： Vehicle transmissions

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A traffic-network-model-based algorithm for short-term prediction of urban traffic flow

A traffic-network-model-based algorithm for short-term predi...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Kong, Qing-Jie Tu, Shitao Liu, Yuncai Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai 200240 China

ISBN: (纸本)9781467324007

In the research field of Intelligent Transportation systems (ITS), traffic flow prediction is a key technology for traffic guidance and advanced control strategy. Accuracy and immediacy are the main requirements for prediction methods. This paper presents a short-term prediction algorithm of traffic flow rate based on the macroscopic urban road network model. Classified into different typical elements, a traffic road network can be expressed as a matrix. Taking crosses and their links as basic research objects, the proposed prediction method can only use a few real traffic parameters obtained from loop detectors to realize accurate short-term prediction of traffic flow rate. This method can also be adaptable to different kinds of road network. In case study, the real traffic system is simulated with the microscopic traffic simulation platform (CORSIM). In the given simulation environment of road network, the experiment results illustrate that the proposed prediction algorithm can accurately predict flow rate in short term. © 2012 IEEE.

关键词： Forecasting

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A Policy-Guided Reinforcement Learning Method for Encirclement control in Multiobstacle Environment

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IEEE Transactions on Neural Networks and Learning systems 2025年 PP卷 PP页

作者： Gou, Fandi Du, Haikuo Zhao, Chenyu Cai, Yunze Shanghai Jiao Tong University Department of Automation Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Jiao Tong University Department of Electronic Engineering Shanghai 200240 China National Key Laboratory of Air-based Information Perception and Fusion Luoyang 471000 China

The problem of multiagent encirclement with multiobstacle collision avoidance (EMOCA) has been challenging since it is difficult to balance the tradeoff between surrounding a mobile target and avoiding obstacles simultaneously. To address the EMOCA problem, we proposed a novel policy-guided reinforcement learning (RL) method, namely, multiregulator-assisted RL for encirclement control (MRA-RLEC) which leverages the jump-start learning and curriculum learning (CL) mechanism to enhance training efficiency. MRA-RLEC divides the complex encirclement task into a sequence of subtasks, progressively increasing in difficulty. In this process, multiple regulators are utilized to adjust various training aspects, including encirclement condition, obstacle avoidance, and the transition from guide to learned policy execution. Besides, a global encirclement reward decomposition (GERD) method is presented to alleviate reward sparsity, and we design a bidirectional communication protocol to reduce communication. Extensive experiments are carried out to showcase the robustness and superiority of our method, and the practical applicability of MRA-RLEC is demonstrated through experiments conducted in the robot operating system 2 (ROS2)-based simulation platform, Gazebo, using a self-designed omnidirectional vehicle model. © 2012 IEEE.

关键词： Curriculum learning (CL) encirclement control multiagent reinforcement learning (MARL) multiobstacle collision avoidance

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