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Dynamics of coupled implicit and explicit opinions

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arXiv 2023年

作者： Zhang, Qi Wang, Lin Wang, Xiaofan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Automation School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

This paper proposes a dual opinions co-evolution model based on the dual attitudes theory in social psychology, where every individual has dual opinions of an object: implicit and explicit opinions. The implicit opinions are individuals’ inner evaluations affected by the experience, while the explicit opinions are external expressions of the evaluations and are influenced by public opinion. We theoretically analyze the dynamics of coupled dual opinions in an adversarial discussion scenario, in which two opposing groups participate in the discussion. We rigorously give a method to grade the degree of individual bias. When individuals have a slight bias, dual opinions reach a consensus, showing the phenomenon of acceptance. When individuals are moderately or even extremely biased, they will exhibit the phenomenon of outward compliance, that is, their publicly explicit opinions conform to public opinion, while implicit opinions will reach a persistent disagreement and even polarization. Our investigation indicates that dual opinions may not be monotone initially but eventually converge monotonically. Besides, we analyze the influence of parameters on the co-evolutionary process and results. Numerical simulations of the dual opinions formation process produce inward and outward conformity phenomena, namely acceptance and compliance. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamics

A novel feature enhancement module for small object detection

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A novel feature enhancement module for small object detectio...

IEEE International Conference on Industrial Technology (ICIT)

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

ISBN: (纸本)9781728119496

Generic object detection has made great progress in recent years, yet small object detection is still facing a serious problem of missed detection. The problem is caused by two reasons: low resolution in small targets and feature loss during deep convolution downsampling. Some previous studies used feature pyramid structures and multi-scale training predictions to alleviate this problem, but still cannot efficiently utilise the feature information of small targets. In this paper, firstly we propose a novel and effective feature enhancement module to extract more features; secondly, a filter size design method is presented to extract features of matching objects and incorporate context information; finally, an adaptive fusion method is used to process outputs of our module and improve model robustness. We select YOLOv3 as base model and carry out several experiments on a special Small Object Dataset and the results show that our work can achieve an increase of about seven percentage points (35.73%) compared to 28.78% on baseline.

关键词： Training Adaptation models Matched filters Design methodology Object detection Filtering algorithms Feature extraction

Model Predictive control Based on Amplitude Decaying Aggregation Strategy for Hydrogen Gas Turbine

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Model Predictive Control Based on Amplitude Decaying Aggrega...

Chinese Automation Congress (CAC)

作者： Aoyun Ma Dewei Li Yugeng Xi Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

The hydrogen gas turbine can be the key technology for carbon-neutral in the future. The flexibility of gas turbine under various operation conditions is an important issue. A state-space model of hydrogen gas turbine with different hydrogen volume ratio mixed fuel is constructed based on Rowen model, and a full-dimensional state observer is designed to obtain the states of state-space model. The model predictive control method based on amplitude decaying aggregation strategy is presented to stabilize the rotational speed of hydrogen gas turbine under various constraints, which are to ensure the safety of operation. The number of variables contained in the optimization problem to be solved online is reduced by aggregation strategy. The simulation results confirmed that the presented method works well, and the effects of the hydrogen volume ratio for the performance of hydrogen gas turbine are discussed.

关键词： Hydraulic turbines Solid modeling Computational modeling Hydrogen Velocity control Predictive models Observers

High-order Fully-actuated controller Design for a Dual-Quadrotor Suspension system

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High-order Fully-actuated Controller Design for a Dual-Quadr...

Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Zhipeng Jiang Xianwei Li Department of Automation Shanghai Jiao Tong University Shanghai P. R. China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai P. R. China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

In this paper, the mathematical model of dual-quadrotor suspension system is established, and the high-order fully-actuated (HOFA) model of the system is derived. Then the direct parametric control method of HOFA nonlinear systems is used to design a controller of the dual-quadrotor suspension system. Simulation results about tracking a circle of the suspension system are presented, which show that HOFA controller have good control effects with relatively smaller tracking errors, while the thrusts of the two quadrotors are within a reasonable range. Compared with a benchmark PD controller in [1], the HOFA controller designed in this paper can mitigate the drastic oscillation in positions of the quadrotor and the load, while the fluctuation of the load attitudes are maintained within a reasonable range.

关键词： Fluctuations Attitude control Simulation Kinematics Mathematical models PD control Nonlinear systems

Unsupervised Learning of 3D Scene Flow from Monocular Camera

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arXiv 2022年

作者： Wang, Guangming Tian, Xiaoyu Ding, Ruiqi Wang, Hesheng Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai 200240 China

Scene flow represents the motion of points in the 3D space, which is the counterpart of the optical flow that represents the motion of pixels in the 2D image. However, it is difficult to obtain the ground truth of scene flow in the real scenes, and recent studies are based on synthetic data for training. Therefore, how to train a scene flow network with unsupervised methods based on real-world data shows crucial significance. A novel unsupervised learning method for scene flow is proposed in this paper, which utilizes the images of two consecutive frames taken by monocular camera without the ground truth of scene flow for training. Our method realizes the goal that training scene flow network with real-world data, which bridges the gap between training data and test data and broadens the scope of available data for training. Unsupervised learning of scene flow in this paper mainly consists of two parts: (i) depth estimation and camera pose estimation, and (ii) scene flow estimation based on four different loss functions. Depth estimation and camera pose estimation obtain the depth maps and camera pose between two consecutive frames, which provide further information for the next scene flow estimation. After that, we used depth consistency loss, dynamic-static consistency loss, Chamfer loss, and Laplacian regularization loss to carry out unsupervised training of the scene flow network. To our knowledge, this is the first paper that realizes the unsupervised learning of 3D scene flow from monocular camera. The experiment results on KITTI show that our method for unsupervised learning of scene flow meets great performance compared to traditional methods Iterative Closest Point (ICP) and Fast Global Registration (FGR). The source code is available at: https://***/IRMVLab/3DUnMonoFlow. Copyright © 2022, The Authors. All rights reserved.

关键词： Unsupervised learning

Meta-ZSDETR: Zero-shot DETR with Meta-learning

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Meta-ZSDETR: Zero-shot DETR with Meta-learning

International Conference on Computer Vision (ICCV)

作者： Lu Zhang Chenbo Zhang Jiajia Zhao Jihong Guan Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China Department of Computer Science & Technology Tongji University China

Zero-shot object detection aims to localize and recognize objects of unseen classes. Most of existing works face two problems: the low recall of RPN in unseen classes and the confusion of unseen classes with background. In this paper, we present the first method that combines DETR and meta-learning to perform zero-shot object detection, named Meta-ZSDETR, where model training is formalized as an individual episode based meta-learning task. Different from Faster R-CNN based methods that firstly generate class-agnostic proposals, and then classify them with visual-semantic alignment module, Meta-ZSDETR directly predict class-specific boxes with class-specific queries and further filter them with the predicted accuracy from classification head. The model is optimized with meta-contrastive learning, which contains a regression head to generate the coordinates of class-specific boxes, a classification head to predict the accuracy of generated boxes, and a contrastive head that utilizes the proposed contrastive-reconstruction loss to further separate different classes in visual space. We conduct extensive experiments on two benchmark datasets MS COCO and PASCAL VOC. Experimental results show that our method outperforms the existing ZSD methods by a large margin.

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Meta-ZSDETR: Zero-shot DETR with Meta-learning

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arXiv 2023年

作者： Zhang, Lu Zhang, Chenbo Zhao, Jiajia Guan, Jihong Zhou, Shuigeng Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China Department of Computer Science & Technology Tongji University China

关键词： Object detection

Signal Temporal Logic control Synthesis among Uncontrollable Dynamic Agents with Conformal Prediction

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arXiv 2023年

作者： Yu, Xinyi Zhao, Yiqi Yin, Xiang Lindemann, Lars Thomas Lord Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China

The control of dynamical systems under temporal logic specifications among uncontrollable dynamic agents is challenging due to the agents’ a-priori unknown behavior. Existing works have considered the problem where either all agents are controllable, the agent models are deterministic and known, or no safety guarantees are provided. We propose a predictive control synthesis framework that guarantees, with high probability, the satisfaction of signal temporal logic (STL) tasks that are defined over a controllable system in the presence of uncontrollable stochastic agents. We use trajectory predictors and conformal prediction to construct probabilistic prediction regions for each uncontrollable agent that are valid over multiple future time steps. Specifically, we construct a normalized prediction region over all agents and time steps to reduce conservatism and increase data efficiency. We then formulate a worst-case bilevel mixed integer program (MIP) that accounts for all agent realizations within the prediction region to obtain an open-loop controller that provably guarantee task satisfaction with high probability. To efficiently solve this bilevel MIP, we propose an equivalent MIP program based on KKT conditions of the original bilevel formulation. Building upon this, we design a closed-loop controller, where both recursive feasibility and task satisfaction can be guaranteed with high probability. We illustrate our control synthesis framework on two case studies. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

Model Predictive Monitoring ofDynamical systems for SignalTemporal Logic Specifications

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arXiv 2022年

作者： Yu, Xinyi Dong, Weijie Li, Shaoyuan Yin, Xiang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

Online monitoring aims to evaluate or to predict, at runtime, whether or not the behaviors of a system satisfy some desired specification. It plays a key role in safety-critical cyber-physical systems. In this work, we propose a new monitoring approach, called model predictive monitoring, for specifications described by Signal Temporal Logic (STL) formulae. Specifically, we assume that the observed state traces are generated by an underlying dynamical system whose model is known but the control law is unknown. The main idea is to use the dynamic of the system to predict future states when evaluating the satisfaction of the STL formulae. To this end, effective approaches for the computation of feasible sets of STL formulae are provided. We show that, by explicitly utilizing the model information of the dynamical system, the proposed online monitoring algorithm can falsify or certify of the specification in advance compared with existing algorithms, where no model information is used. We also demonstrate the proposed monitoring algorithm by several real world case studies. Copyright © 2022, The Authors. All rights reserved.

关键词： Specifications