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arXiv 2022年

作者： Zheng, Wenzhe He, Zhiyu He, Jianping Zhao, Chengcheng Fang, Chongrong Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China China State Key Laboratory of Industrial Control Technology Zhejiang University China

We study the problem of resilient average consensus for multi-agent systems with misbehaving nodes. To protect consensus value from being influenced by misbehaving nodes, we address this problem by detecting misbehaviors, mitigating the corresponding adverse impact and achieving the resilient average consensus. In this paper, general types of misbehaviors are considered, including deception attacks, accidental faults and link failures. We characterize the adverse impact of misbehaving nodes in a distributed manner via two-hop communication information and develop a deterministic detection-compensation-based consensus (D-DCC) algorithm with a decaying fault-tolerant error bound. Considering scenarios where information sets are intermittently available due to link failures, a stochastic extension named stochastic detection-compensation-based consensus (S-DCC) algorithm is proposed. We prove that D-DCC and S-DCC allow nodes to asymptotically achieve resilient average consensus exactly and in expectation, respectively. Then, the Wasserstein distance is introduced to analyze the accuracy of S-DCC. Finally, extensive simulations are conducted to verify the effectiveness of the proposed algorithms. © 2022, CC BY.

关键词： Stochastic systems

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Multi-period Optimal control for Mobile Agents Considering State Unpredictability

arXiv

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arXiv 2022年

作者： Qu, Chendi He, Jianping Li, Jialun The Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

The optimal control for mobile agents is an important and challenging issue. Recent work shows that using randomized mechanism in agents’ control can make the state unpredictable, and thus improve the security of agents. However, the unpredictable design is only considered in single period, which can lead to intolerable control performance in long time horizon. This paper aims at the trade-off between the control performance and state unpredictability of mobile agents in long time horizon. Utilizing random perturbations consistent with uniform distributions to maximize the attackers’ prediction errors of future states, we formulate the problem as a multi-period convex stochastic optimization problem and solve it through dynamic programming. Specifically, we design the optimal control strategy considering both unconstrained and input constrained systems. The analytical iterative expressions of the control are further provided. Simulation illustrates that the algorithm increases the prediction errors under Kalman filter while achieving the control performance requirements successfully. Copyright © 2022, The Authors. All rights reserved.

关键词： Mobile agents

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Multi-period Optimal control for Mobile Agents Considering State Unpredictability

Multi-period Optimal Control for Mobile Agents Considering S...

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IEEE Conference on Vehicular Technology (VTC)

作者： Chendi Qu Jianping He Jialun Li Dept. of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9781665454698

关键词： Vehicular and wireless technologies Perturbation methods Heuristic algorithms system performance Mobile agents Optimal control Predictive models

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Autonomous Navigation for Mobile Robots with Weakly-Supervised Segmentation Network

Autonomous Navigation for Mobile Robots with Weakly-Supervis...

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IEEE Conference on Vehicular Technology (VTC)

作者： Peinan Huang Jialun Li Jianping He Dept. of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665454698

This paper investigates autonomous navigation for mobile robots with a low-cost monocular camera. The main challenge lies in: i) how to accurately detect prior unseen obstacles and acquire obstacles position from monocular images without depth information, and ii) how to get the constraints for path planning to generate safe and stable path for the robot. To accurately locate surrounding obstacles using only a monocular camera, we adopt a weakly-supervised semantic segmentation network trained from LIDAR data and perform inverse perspective transformation based on ground plane constraint. Meanwhile, to reduce segmentation noise, we establish a probability occupancy map based on the distance between robot and obstacles. For path generations, we present a novel search-and-optimization based planning approach to get boundary constraints in Frenet frame and generate stable local path with consecutive image inputs. In the simulation, segmentation Intersection over Union (IoU) of the drivable area achieves more than 99% and the average mapping accuracy is less than 10cm, showing feasibility and robustness of our navigation scheme.

关键词： Training Navigation Semantic segmentation Robot vision systems Cameras Path planning Stability analysis

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Jointly Learning Time-Structure-History Graph Embedding for Temporal Knowledge Graph Reasoning

Jointly Learning Time-Structure-History Graph Embedding for ...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Hao Duan Haoyu Jin Kang Chen Shaochong Du Tao Fang Hong Huo Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

The Temporal Knowledge Graph(TKG) reasoning is an imperative task for various applications of TKG. However, reasoning over TKGs which aims to predict future facts has been less explored. Intuitively, entities and relations in TKG change differently over time, and the variations are different. It also can be observed that what happens in the past may affect the future. Apart from these, structure information that exists in the neighborhood of a given entity in a KG has been proven to be important. Inspired by these, a novel graph embedding method for TKG reasoning, called time-structure-history graph embedding (TSHGE), is proposed in this paper. TSHGE consists of three progressive learning units. The first time information learning unit employs a novel time-aware mechanism to encode the time influence on entities and relations. Then a relation-aware GAT (Graph Attention Network) is used in the structure information learning unit to model the 1-hop neighborhoods of all entities in a KG at each timestamp in TKG. Finally, the history information learning unit utilizes GRU (Gated Recurrent Unit) to learn history information from various facts. Then the ultimate embedding representations of entities and relations can be obtained for the prediction of future facts. The evaluations on three public TKG datasets have demonstrated the effectiveness and superiority of TSHGE for predicting future facts.

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A Unified Framework for Verification of Observational Properties for Partially-Observed Discrete-Event systems

arXiv

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arXiv 2022年

作者： Zhao, Jianing Yin, Xiang Li, Shaoyuan Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing the Ministry of Education of China Shanghai200240 China

In this paper, we investigate property verification problems in partially-observed discrete-event systems (DES). Particularly, we are interested in verifying observational properties that are related to the information-flow of the system. Observational properties considered here include diagnosability, predictability, detectability and opacity, which have drawn considerable attentions in the literature. However, in contrast to existing results, where different verification procedures are developed for different properties case-by-case, in this work, we provide a unified framework for verifying all these properties by reducing each of them as an instance of HyperLTL model checking. Our approach is based on the construction of a Kripke structure that effectively captures the issue of unobservability as well as the finite string semantics in partially-observed DES so that HyperLTL model checking techniques can be suitably applied. Then for each observational property considered, we explicitly provide the HyperLTL formula to be checked over the Kripke structure for the purpose of verification. Our approach is uniform in the sense that all different properties can be verified with the same model checking engine. Furthermore, our unified framework also brings new insights for classifying observational properties for partially-observed DES in terms of their verification complexity. Copyright © 2022, The Authors. All rights reserved.

关键词： Discrete event simulation

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Robust sliding model predictive control with disturbance compensation in application to AUV pitch-axis motion

Robust sliding model predictive control with disturbance com...

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第34届中国控制与决策会议

作者： Jiuwu Hui Jingqi Yuan State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment Department of Automation and the Key Laboratory of System Control and Information Processing/Ministry of EducationShanghai Jiao Tong University

Constraints on the control input and system states as well as uncertain disturbances are the practical challenges in many motion control *** this paper,a disturbance observer(DO) with two-step disturbance compensation algorithm is proposed to deal with disturbances and enhance the robustness of the controller,while a discrete sliding mode predictive control(DSMPC) scheme is designed to handle saturation constraints on the control input and system states with the application to an autonomous underwater vehicle(AUV).The DSMPC combines the model predictive control(MPC) with the discrete sliding mode control(DSMC) using linear matrix inequalities *** stability of the proposed DSMPC are proved via Lyapunov stability ***,simulation results are presented to illustrate the effectiveness of the whole control scheme.

关键词： Disturbance observer Two-step compensation algorithm Discrete sliding mode predictive control Inequality constraints and AUV pitch-axis motion control

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Optimal Multi-Robot Path Planning for Cyclic Tasks using Petri Nets

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IFAC-PapersOnLine 2022年第28期55卷 9-15页

作者： Peng Lv Guangqing Luo Xiang Yin Ziyue Ma Shaoyuan Li Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai 200240 China School of Electro-Mechanical Engineering Xidian University Xi'an 710071 China

In this paper, we investigate the problem of optimal multi-robot path planning for a cyclic task represented by a particular type of linear-temporal logic (LTL) formulae. Specifically, the team of robot needs to fulfill a given LTL formula and at the same time, accomplishes some particular tasks infinitely often. To avoid the state-space explosion when the number of robot increases, we use Petri nets to model the team of multi-robot. Our goal is to find an optimal infinite sequence in the prefix-suffix form for each robot such that the average cost per task is minimized. We propose an efficient planning method based on the notion of basis reachability graph (BRG), which is a compact representation of the reachability space of the PN. We demonstrate the computational efficiency of our method through illustrative examples.

关键词： Petri Nets Linear Temporal Logic Multi-Robot systems Task Planning

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Trailer Tag Hitch: An Automatic Reverse Hanging system Using Fiducial Markers 7th

Trailer Tag Hitch: An Automatic Reverse Hanging System Using...

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7th International Conference on Cognitive systems and information processing, ICCSIP 2022

作者： Lu, Dongxi Yuan, Wei Lian, Chaochun Yao, Yongchun Cai, Yan Yang, Ming Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China University of Michigan - Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China SAIC-GM-Wuling Automobile Co. Ltd. Guangxi Liuzhou545007 China

ISBN: (纸本)9789819906161

Unmanned tractor-trailer vehicles are widely used in factory transportation scenarios. However, the trailer hitching process is still manually operated. The automatic trailer hitching is the precondition of fully unmanned logistics. Existing auto hitching methods directly detect the trailer or coupler features, making them hard to generalize and deploy to various types of trailers and couplers. To address this problem, this paper proposes a trailer hitch system using fiducial markers. The system is divided into two modules: hitch coupler pose estimation and visual servoing. An algorithm based on AprilTag detection is used for hitch coupler pose estimation. The pose messages guide the tractor to reverse to the trailer. An algorithm based on decoupled lateral-longitudinal control is used for visual servoing. The proposed system is experimented on 4 different tractor-trailer vehicles with 254 tests under various conditions. Large scale test condition variations include initial position and orientation, light illumination, indoor/outdoor scenario, and fiducial marker damage. Overall success rate of 95% shows that the proposed system is robust to environment variation and different kinds of trailers. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Light trailers

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controller Design for Switched LPV systems with Hidden semi-Markov Mode Switching 11

Controller Design for Switched LPV Systems with Hidden semi-...

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11th International Conference on Intelligent control and information processing, ICICIP 2021

作者： Wang, Jianfeng Chen, Zhiru Sun, Yichong Li, Zhan Pei, Dacheng Cai, Bo China Institute of Marine Technology & Economy Beijing China Beijing Machine and Equipment Institute Beijing China Harbin Institute of Technology Key Laboratory of System Control and Information Processing Harbin China

ISBN: (纸本)9781665425155

This paper is concerned with issue of stability analysis and control synthesis for a class of switched LPV systems with stochastic mode switching. The stochastic switching process is further regarded as hidden semi-Markov switching by using concepts of semi-Markov kernel and emission probability. With the construction of a novel Lyapunov function that depends on accessible-mode, parameter as well as elapsed time, the mean-square stability (MSS) criteria are developed for the closed-loop system with the usage of designed controller. Numerically testable stability criteria are established in sense of MSS by introducing the upper bound sojourn time and some mathematical techniques. The theoretical results are testified by a numerical example to demonstrate the effectiveness of the designed stabilizing controller. © 2021 IEEE.

关键词： Stability criteria

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