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control Input Inference of Mobile Agents under Unknown Objective

IFAC-PapersOnLine 2023年第2期56卷 2134-2139页

作者： Chendi Qu Jianping He Xiaoming Duan Shukun Wu The Dept. of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

Trajectory and control secrecy is an important issue in robotics security. This paper proposes a novel algorithm for the control input inference of a mobile agent without knowing its control objective. Specifically, the algorithm first estimates the target state by applying external perturbations. Then we identify the objective function based on the inverse optimal control, providing the well-posedness proof and the identifiability analysis. Next, we obtain the optimal estimate of the control horizon using binary search. Finally, the agent's control optimization problem is reconstructed and solved to predict its input. Simulation illustrates the efficiency and the performance of the algorithm.

关键词： Mobile Agents control Input Inference Optimal control Trajectory Secrecy

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Toward Enhancing Cyber-Physical system Security with system Unidentifiability

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IFAC-PapersOnLine 2023年第2期56卷 1692-1697页

作者： Xiangyu Mao Jianping He Chongrong Fang Yunfeng Peng The Dept. of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

A substantial amount of research has shown that most attacks on cyber-physical systems rely on knowledge of system models, where the models can be obtained using identification methods. Hence, achieving unidentifiability is an attractive way for the security of systems. This paper focuses on the unidentifiability of systems and designs a controller against the attacks relying on identification. The key insight is that we propose a quantitative evaluation to measure the unidentifiability of the system. This evaluation can be taken as a criterion for evaluating the security of the system. Different from the existing research, the evaluation gives the exact number of unidentifiable parameters in the system. Moreover, we give the necessary and sufficient condition for each parameter to be unidentifiable. Finally, we design a controller based on this evaluation to maximize the number of unidentifiable parameters. Simulation demonstrates the effectiveness of our algorithm.

关键词： system Identification Security and Unidentifiability Fisher information

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Online-Learning-Enabled Distributionally Robust Motion control via Uncertainty Propagation and Ambiguity Set Compression

Online-Learning-Enabled Distributionally Robust Motion Contr...

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IEEE Conference on Decision and control

作者： Han Wang Chao Ning Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We develop a safe, efficient, and flexible motion control framework for collision-free navigation of robots in uncertain and dynamic environments. With the gathered real-time data at each control time, the motion distribution of obstacles is estimated from data streams by leveraging the Dirichlet process mixture model. We propose a novel uncertainty propagation method, which theoretically admits the derivation of obstacle position distributions over the entire prediction horizon only based on the current position and motion distribution of obstacles. To enhance the robustness against estimated distribution errors, an ambiguity set utilizing local-moment information of position distributions is constructed. Additionally, we introduce a compression scheme to automatically adjust the complexity (granularity) of the ambiguity set by aggregating distributions that are close in Wasserstein space, thereby flexibly striking a trade-off between control performance and computation time. The distributionally robust collision avoidance constraint based on the compressed ambiguity set is reformulated into separating hyperplanes, which are applied in the model predictive controller to obtain the optimal collision-free trajectory. To resolve the infinite-dimensionality issue inherent in the computation of the separating hyperplanes, we equivalently derive a tractable semi-definite programming formulation exploiting distributionally robust optimization techniques. The efficacy of the proposed framework is demonstrated through simulation.

关键词： Uncertainty Simulation Programming Robustness Real-time systems Trajectory Safety Collision avoidance Robots Streams

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Data-Driven Robust Optimization for Energy Chemical Processes under Uncertainties: A Review and Tutorial 4

Data-Driven Robust Optimization for Energy Chemical Processe...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Ning, Chao Li, Longyan Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

In recent years, data-driven robust optimization (DDRO) is becoming a popular and effective paradigm to address the challenging issue of uncertainty in energy chemical processes. This paper provides an overview of recent advances in the field of DDRO, with a primary focus on its methods and applications in process industries. Firstly, a brief introduction to various robust optimization model formulations and solution algorithms is presented. Secondly, research achievements of machine-learning enabled uncertainty sets, the corresponding DDRO, and variant techniques are summarized and analyzed in a systematic manner. Additionally, tutorial-like numerical examples are used to illustrate merits of DDRO compared with conventional robust optimization. Finally, fruitful applications of DDRO in energy chemical processes are encapsulated and categorized from domain perspectives. © 2022 IEEE.

关键词： Optimization

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A Timeslot Clustering-Based Hybrid Traffic Scheduling in Time-Sensitive Networking

A Timeslot Clustering-Based Hybrid Traffic Scheduling in Tim...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Zhihao Yang Shouliang Wang Qimin Xu Xin Li Cailian Chen Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

The development of Industrial Internet of Things necessitates deterministic transmission of hybrid traffic with varying real-time requirements. Time-Sensitive Networking offers schemes combining scheduling mechanisms like the Time-Aware Shaper (TAS) and Cyclic Queuing and Forwarding (CQF). Current methods utilize the combination of TAS&CQF to schedule Time-Triggered (TT) and Audio-Video Bridging (AVB) traffic under corresponding mechanisms, respectively. However, the prior TT traffic orchestration restricts the scheduling solution space of AVB traffic, decreasing the effectiveness of combination and finally resulting in low schedulability. In this paper, we focus on enhancing the schedulability of TT&AVB scheduling by integrating TAS and Cyclic Specified Queuing and Forwarding (CSQF), which brings larger scheduling solution space to AVB traffic. The integration of TAS&CSQF is proposed by analyzing the impact of TAS on CSQF to expand the allocatable resource for AVB traffic. Then TAS&CSQF scheduling model is formulated to ensure deterministic requirements. Within this model, Timeslot Clustering Optimization (TCO) is proposed to optimize the scheduling solution space of AVB traffic and slice timeslot by refining the scheduling of TAS. Based on TCO, Flow Congestion Metric (FCM) is designed to improve schedulability by the congestion level of each link. An FCM-based algorithm is further presented to generate TT&AVB solutions incrementally. Simulation results demonstrate that our method reduces scheduling time cost by over 168 times and improves schedulability by 32% for 3000 flows compared to existing methods.

关键词： Measurement Schedules Job shop scheduling Simulation Refining Real-time systems Internet Informatics Optimization Industrial Internet of Things

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Research on High-Precision Contouring control of Gantry Dual-Drive H-Type Planar Motion Platform

Research on High-Precision Contouring Control of Gantry Dual...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Chao Chen Haoyu Li Chaochen Gu Department of Automation Ministry of Education of China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

The H-type two-axis linear plane motion platform with dual gantry drive is one of the most crucial components in contour processing equipment. The dual gantry structure employs independently controlled dual-side motors to collectively drive the motion of the gantry crossbeam axis. While the introduction of dual gantry drive brings higher single-axis positioning accuracy and greater operational speed to contour processing *** these issues, this paper starts with the dynamic modeling of the dual gantry H-type plane motion platform. It modifies and extends the task coordinates within the framework of the Global Task Coordinate Frame (GTCF). Subsequently, it effectively addresses the coordination between axes and the synchronization of dual drive in the task space, obtaining both motion coordination and dual-axis synchronization capabilities, leading to more accurate contour error calculation and evaluation. The paper includes a comprehensive design of experiments to assess the dual gantry synchronization performance in contour control. The proposed control method is compared with the traditional GTCF-based contour control method, demonstrating the effectiveness and superiority of the integrated coordination and synchronization contour control method.

关键词： Accuracy Uncertainty Tracking Robot kinematics Dynamics Aerospace electronics Motors

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Self-Supervised Depth Estimation Based on the Consistency of Synthetic-real Image Prediction 8

Self-Supervised Depth Estimation Based on the Consistency of...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Tong, Wei Gao, Yubing Wu, Edmond Q. Zhu, Li-Min School of Mechanical Engineering Nanjing University of Science and Technology Jiangsu210014 China Ministry of Education Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China

ISBN: (纸本)9798350300178

Learning-based multi-view stereo aims to restore the real scene from multiple images with overlapping areas. The mainstream self-supervised MVS method trains the model based on the assumption that spatial points from different perspectives share the same color information. To further suppress the interference from specular reflection and illumination noise, this work proposes a self-supervised MVS network based on the consistency of synthetic-real image prediction. The network first applies the coarse-to-fine manner to gradually refine the depth map, and the source images are projected to the reference view to generate the synthesized reference image. Then the synthesized image with real source images are re-input into the network to form a cycled network, and the consistency constraint of the prediction results of the two periods is introduced to improve the color anti-interference of the self- supervised MVS model. The comprehensive experiments on the public dataset show that the proposed work can further improve the reconstruction performance of the benchmark model, which verifies the effectiveness of the proposed work. © 2023 IEEE.

关键词： Forecasting

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Leader-Follower Consensus on Matrix-Weighted Switching Networks

Leader-Follower Consensus on Matrix-Weighted Switching Netwo...

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International Conference on control and Automation (ICCA)

作者： Kai Wang Lulu Pan Haibin Shao Dewei Li Yuanlong Li Shaoying He Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper examines the consensus problem on leader-follower matrix-weighted undirected switching networks. First, we introduce the leader-follower matrix-weighted integral network for analyzing such a category of networks. The connection between the null space of matrix-valued Laplacian associated with the integral network and that associated with the series of switching matrix-weighted networks has been established. Under some mild assumptions, sufficient conditions for leader-follower consensus under matrix-weighted periodic switching networks are provided. Simulation results are presented to demonstrate the theoretical results.

关键词： Sufficient conditions Laplace equations Automation Simulation Null space Switches

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Robust and Real-Time Road Edge Detection with Flexible LiDAR Configuration

Robust and Real-Time Road Edge Detection with Flexible LiDAR...

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Chinese control and Decision Conference, CCDC

作者： Jia-Chen Li Jun-Guo Lu Ming Wei Hong-Yi Kang Qing-Hao Zhang Key Laboratory of System Control and Information Shanghai Jiao Tong University Shanghai China Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Road edge detection is an important component in autonomous driving for along-side scenarios. The road edge is defined as a boundary line where there is a height change from the road surface. However, the traditional LiDAR-based methods are not sensitive enough for small height difference. In addition, the point cloud needs to be provided in a channel-based organization, which means that at most one LiDAR’s data can be used for edge detection. In this paper, a novel road edge detection method is proposed to utilize flexible LiDAR configuration, e.g., multiple LiDARs. Specifically, the raw point cloud is first sorted in polar coordinates, and coarse edge points are generated according to height gradient for accurate ground segmentation. The non-ground points are further used to determine the road types based on occupancy map and beam models. The final edge points in the region of interest are extracted by dynamic slide window. Our method is evaluated on unmanned ground vehicle equipped with two Robosense LiDARs, and extensive experiments are conducted to demonstrate the effectiveness of our method.

关键词： Point cloud compression Laser radar Accuracy Roads Image edge detection Organizations Real-time systems

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Prioritize Team Actions: Multi-Agent Temporal Logic Task Planning with Ordering Constraints

Prioritize Team Actions: Multi-Agent Temporal Logic Task Pla...

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IEEE International Conference on Automation Science and Engineering (CASE)

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

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we investigate the problem of linear temporal logic (LTL) path planning for multi-agent systems, introducing the new concept of ordering constraints. Specifically, we consider a generic objective function that is defined for the path of each individual agent. The primary objective is to find a global plan for the team of agents, ensuring they collectively meet the specified LTL requirements. Simultaneously, we aim to maintain a pre-determined order in the values of the objective function for each agent, which we refer to as the ordering constraints. This new requirement stems from scenarios like security-aware planning, where relative orders outweigh absolute values in importance. We present an efficient algorithm to solve this problem, supported by proofs of correctness that demonstrate the optimality of our solution. Additionally, we provide a case study in security-aware path planning to illustrate the practicality and effectiveness of our proposed approach.

关键词： Uncertainty Computer aided software engineering Automation information security Linear programming Path planning Planning Logic Multi-agent systems

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