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17th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2023

作者： Varga, Balint Yang, Dongxu Hohmann, Soren Institute of Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798350321104

This paper presents a white-box intention-aware decision-making for the handling of interactions between a pedestrian and an automated vehicle (AV) in an unsignalized street crossing scenario. Moreover, a design framework has been developed, which enables automated parameterization of the decision-making. This decision-making is designed in such a manner that it can understand pedestrians in urban traffic and can react accordingly to their intentions. That way, a human-like response to the actions of the pedestrian is ensured, leading to a higher acceptance of AVs. The core notion of this paper is that the intention prediction of the pedestrian to cross the street and decision-making are divided into two subsystems. On the one hand, the intention detection is a data-driven, black-box model. Thus, it can model the complex behavior of the pedestrians. On the other hand, the decision-making is a white-box model to ensure traceability and to enable a rapid verification and validation of AVs. This white-box decision-making provides human-like behavior and a guaranteed prevention of deadlocks. An additional benefit is that the proposed decision-making requires low computational resources only enabling real world usage. The automated parameterization uses a particle swarm optimization and compares two different models of the pedestrian: The social force model and the Markov decision process model. Consequently, a rapid design of the decision-making is possible and different pedestrian behaviors can be taken into account. The results reinforce the applicability of the proposed intention-aware decision-making. © 2023 IEEE.

关键词： Decision making

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Autoencoder-Based and Physically Motivated Koopman Lifted States for Wind Farm MPC: A Comparative Case Study 63

Autoencoder-Based and Physically Motivated Koopman Lifted St...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Sharan, Bindu Dittmer, Antje Xu, Yongyuan Werner, Herbert Institute of Control Systems Hamburg University of Technology Germany Institute of Flight Systems German Aerospace Center Germany

ISBN: (纸本)9798350316339

This paper explores the use of Autoencoder (AE) models to identify Koopman-based linear representations for designing model predictive control (MPC) for wind farms. Wake interactions in wind farms are challenging to model, and have previously been addressed with Koopman lifted states. In this study we investigate the performance of two AE models: The first AE model estimates the wind speeds acting on the turbines these are affected by changes in turbine control inputs. The wind speeds estimated by this AE model are then used in a second step to calculate the power output via a simple turbine model based on physical equations. The second AE model directly estimates the wind farm output, i.e., both turbine and wake dynamics are modelled. The primary inquiry of this study is whether either of these two AE-based models can surpass previously identified Koopman models based on physically motivated lifted states. We find that the first AE model, which estimates the wind speed and hence includes the wake dynamics, but excludes the turbine dynamics outperforms the existing physically motivated Koopman model. However, the second AE model, which estimates the farm power directly, underperforms when the turbines' underlying physical assumptions are correct. We also investigate specific conditions under which the second, purely data-driven AE model can excel: Notably, when modelling assumptions, such as the wind turbine power coefficient, are erroneous and remain unchecked within the MPC controller. In such cases, the data-driven AE models, when updated with recent data reflecting changed system dynamics, can outperform physics-based models operating under outdated assumptions. © 2024 IEEE.

关键词： Wind turbines

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Event-triggered consensus control of heterogeneous multi-agent systems: model-and data-based approaches

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Science China(Information Sciences) 2023年第9期66卷 151-167页

作者： Xin WANG Jian SUN Fang DENG Gang WANG Jie CHEN School of Automation Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Chongqing Innovation Center Department of Control Science and Engineering Tongji University

This article addresses the model-and data-based event-triggered consensus of heterogeneous leader/follower multi-agent systems(MASs). A dynamic periodic transmission protocol is developed to alleviate the communication and computational burden, where the followers can interact locally with neighbors to approach the dynamics of the leader. Capitalizing on a discrete-time looped-functional, a model-based consensus condition for the closed-loop MASs is derived as linear matrix inequalities(LMIs), along with a design method for obtaining distributed event-triggered controllers and the associated triggering *** collecting noise-corrupted state-input measurements in offline open-loop experiments, a data-based leader/follower MAS representation is derived and employed to address the data-driven consensus control problem without explicit MAS models. This result is subsequently generalized to guarantee an H∞-consensus control performance. Finally, a simulation example is given to corroborate the efficiency of the proposed distributed triggering scheme and the data-driven consensus controller.

关键词： data-driven control multi-agent system consensus looped-functional LMI

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Motion Planning for The Identification of Linear Classifiers with Noiseless Data: A Greedy Approach 63

Motion Planning for The Identification of Linear Classifiers...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Raghavan, Aneesh Johansson, Karl Henrik Royal Institute of Technology Kth Division of Decision and Control Systems Stockholm Sweden

ISBN: (纸本)9798350316339

A given region in 2-D Euclidean space is divided by a unknown linear classifier in to two sets each carrying a label. An agent with known dynamics traversing the given region is able to measure the true label perfectly at its position. By following a trajectory, the agent collects data points comprising of its true position and the label at that position. The objective of the agent is to plan a trajectory across the given region to identify the true classifier with high accuracy while minimizing the control cost across the trajectory. We present the following: (i) the classifier identification problem formulated as a control problem;(ii) geometric interpretation of the control problem resulting in one step modified control problems;(iii) control algorithm that results in a data set which is used to identify the true classifier with high accuracy;(iv) convergence of estimated classifier to the true classifier when observed label is not corrupted by noise;(iv) numerical example demonstrating the utility of the control algorithm. © 2024 IEEE.

关键词： Trajectories

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Structural Conditions for Leak Localization in Potential Flow Networks 63

Structural Conditions for Leak Localization in Potential Flo...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Molno, Victor Sandberg, Henrik Kth Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden

ISBN: (纸本)9798350316339

In this paper, we analyze the leak localization problem in potential flow networks. We present a general model encompassing various physical systems, for example, water distribution networks. In contrast to conventional water distribution network models, our model is neither restricted to any particular type of potential loss function nor to vertex leaks. We consider leak localization via vertex potential analysis, a general description of methods that work by comparing vertex potentials calculated under a leak location hypothesis to measured vertex potentials. We derive conditions on the graph structure of the network and the potential sensor placement, under which it is guaranteed that the leak can be limited, via vertex potential analysis, to a small set of locations. We suggest a bisection method to utilize our conditions. Our conditions are based on one-way edges in graphs, a concept that we introduce. In extension, our results can be used for sensor placement. © 2024 IEEE.

关键词： Graphic methods

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Design of Dual-Rotor Vehicle controller Based on Auto Disturbance Rejection 1

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3rd International Conference on Autonomous Unmanned systems, ICAUS 2023

作者： Sun, Xue Wang, Donghui Zhan, Zhengyong Cui, Yuwei AVIC Xi’an Flight Automatic Control Research Institute Xi’an710065 China Aviation Key Laboratory of Science and Technology On Aircraft Control Xi’an710065 China

ISBN: (数字)9789819710997

ISBN: (纸本)9789819710980

Aiming at the characteristics of dual-rotor vehicle, nonlinear, strong coupling and easy to be interfered, a design method of altitude tracking and attitude stabilization using nonlinear active disturbance rejection controller was proposed. The mathematical model of the dual-rotor vehicle was established through dynamic analysis, and the state coupling was regarded as the internal disturbance. The state observer was used to estimate the state and internal and external disturbance of the system in real time, and then the nonlinear feedback was used to compensate the estimated value of the internal and external disturbance of the model, and the state decoupling control of the dual-rotor vehicle was realized. Finally, through the simulation experiment, and compared with the classical PID control method, the experimental results show that the active disturbance rejection controller can realize the altitude tracking and fast and stable attitude control of the dual-rotor vehicle, and has strong anti-interference and robustness. © Beijing HIWING Scientific and Technological Information institute 2024.

关键词： Nonlinear feedback

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Optimizing Artificial Neural Networks Trough Weight Adjustments 28th

Optimizing Artificial Neural Networks Trough Weight Adjustme...

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28th International Conference on Knowledge Based and Intelligent information and Engineering systems, KES 2024

作者： Akber, Syed Muhammad Abrar Szczesna, Agnieszka Kazmi, Sadia Nishat Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland

Longer training times pose a significant challenge in artificial neural networks (ANNs) as it may leads to increasing the computational costs and decreasing the effectiveness of the model. Therefore, it is imperative to reduce training times in ANNs to enhance the computational efficiency. The initialization of the weights between the layers in ANN plays a vital role in reducing training times. Appropriate weight initialization can help the network converge faster during the training by providing an optimum starting point for the network. Therefore, weight initialization techniques are essential for efficient training of ANNs. This paper revisits and implements different popular weight initialization techniques in ANNs and analyzes their impact on training time. Specifically, this paper implements Gaussian-based, Kaming-based, and Xavier-based weight initiation atop a popular DNN-based network. The experiments are conducted by employing a well-known dataset. The results show that the scenario when no weight initiation is applied consumed the highest training time, whereas different weight initiation techniques contribute in reducing the training times for the network. © 2024 The Authors.

关键词： Deep neural networks

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A proposal on centralised and distributed optimisation via proportional–integral–derivative controllers(PID)control perspective

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IET Cyber-systems and Robotics 2023年第4期5卷 40-48页

作者： Jiaxu Liu Song Chen Shengze Cai Chao Xu School of Mathematical Sciences Zhejiang UniversityHangzhouChina The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhouChina

Motivated by the excellent performance of proportional–integral–derivative controllers(PIDs)in the field of control,the authors injected the philosophy of PID into optimi-sation and introduced two types of novel PID optimisers from a continuous-time view,which benefit from the idea that discrete-time optimisation algorithm can be modelled as a continuous dynamical system/controlled *** centralised optimisation,the au-thors discuss the idea of the first-order PID optimiser and the second-order accelerated PID ***,this framework is extended into distributed optimisation settings,and a distributed PID optimiser is ***,some numerical examples are given to verify our ideas.

关键词： control deep learning deep neural network machine learning

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Research on longitudinal control technology in the transition section of tilt-rotor aircraft based on linear active disturbance rejection control 2

Research on longitudinal control technology in the transitio...

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2023 2nd International Conference on Aerospace and control Engineering, ICoACE 2023

作者： Xu, Shaofeng Chang, Shaoping Shi, Pengfei Wang, Lin AVIC Xi'An Flight Automatic Control Research Institute Xi'an710065 China National Key Laboratory of Science and Technology on Aircraft Control Xi'an710065 China

To solve the problem of strong coupling and control redundancy in the transition section of the tilt-rotor, this paper presents a longitudinal control method based on linear active disturbance rejection control (LADRC), verified by simulation. Firstly, the nonlinear dynamics model of tilt-rotor aircraft based on the mechanism method is established, and the model's accuracy is verified by comparing the trim result with the generic tilt-rotor aircraft simulation (GTRS) model verified by flight test in XV-15. Then, the control and redundant rudder surface assignment strategies for tilt-rotor aircraft are proposed. Then, the vertical and vertical control law of tilt-rotor aircraft is designed, the linear expansion state observer (LESO) model is analyzed and derived, and the linear active disturbance rejection controller suitable for attitude loop control of tilt-rotor is designed. The altitude and velocity loops are controlled. Finally, the proposed linear active disturbance rejection control (LADRC) controller is verified by simulation, and the whole process of tilting transition is simulated. The results show that the proposed control strategy and the controller designed in this paper have strong anti-disturbance ability, fast response speed, and high control precision and can be used in the transition section of tilt-rotor aircraft. The vertical direction shall be well controlled. © Published under licence by IOP Publishing Ltd.

关键词： controllers

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Tracking and Mapping Strategy for Indoor UAV Based on Entropy Theory:An ORB-SLAM3 Extension 41

Tracking and Mapping Strategy for Indoor UAV Based on Entrop...

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第41届中国控制会议

作者： Jian Xu Haoyu Qi Min Xu Yunge Zang Zhen Li Xi Zhang Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

For indoor application,which is an entirely GPS-denied environment,visual simultaneous localization and mapping(SLAM) facilitates the real autonomy of unmanned aerial vehicle(UAV) but raises the challenging requirement on accurate localization with low computational *** address this difficulty,a stereo-camera based SLAM system is proposed by applying Entropy theory to *** an extension to ORB-SLAM3,the additional entropy decision module and map processor are specifically *** decision module can improve computing efficiency by deciding whether keyframes or extra optimization should be ***,the map processor is targeted at loading and maintaining the prior map whenever *** results in indoor laboratory environment show that the developed system can achieve the superior localization accuracy in more efficient computation manner with smaller size of mapping compared with ***,the map can be effectively expanded and corrected even when prior information is invalid,greatly increasing the robustness of SLAM system.

关键词： UAV stereo-camera ORB-SLAM3 entropy theory prior map

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