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第35届中国控制与决策会议

作者： Peng Liu Hongliang Fang Jiang-Wen Xiao Yan-Wu Wang Xiao-Kang Liu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education

When a large number of distributed power and renewable energy are connected to the smart grid,the volatility and intermittency of renewable energy bring some challenges to the smart ***,accurate medium-term load forecasting is essential because it is conducive to the stability of the power grid and can provide data support for the power generating *** factors affect medium-term load forecasting and the real-time electricity price is a very important factor among *** this paper,a multi-scale model based on LSTM model is proposed to extracts features from 3 different time scales including half-hourly time scale,daily time scale and monthly time *** first,the half-hourly data is processed by a half-hourly data processing layer to extract the half-hourly ***,its output is concatenated with the daily load data and is input into a daily data processing ***,the daily features are concatenated with the monthly load data and they are input into a monthly data processing layer to extract the monthly features and get the final forecasting *** case study results demonstrate that the proposed multi-scale model has better performance than the single-scale models.

关键词： Deep learning medium-term load forecasting LSTM real-time electricity price

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DUAL-QUATERNION BASED FINITE-TIME ADAPTIVE control FOR spaceCRAFT AUTONOMOUS PROXIMITY MANEUVER

DUAL-QUATERNION BASED FINITE-TIME ADAPTIVE CONTROL FOR SPACE...

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IAF Astrodynamics Symposium 2021 at the 72nd International Astronautical Congress, IAC 2021

作者： Wang, Liangyue Guo, Yanning Ma, Guangfu Lyu, Yueyong Zhang, Haibo Harbin Institute of Technology China Beijing Institute of Control Engineering China National Key Laboratory of Science and Technology on Space Intelligent Control China

ISBN: (纸本)9781713843078

The autonomous proximity maneuver phase is the prerequisite part of the on-orbit service, and it presents a set of challenges. One such challenge is that the service spacecraft is required to complete the proximity task within the specified time while satisfying some attitude-position coupled constraints, such as field of view (FOV) constraint, collision avoidance constraint. This paper addresses the problem of six degrees of freedom (6-DOF) finite-time pose control with multiple constraints. Firstly, the FOV and collision avoidance constraints are represented as pyramid envelopes closer to the actual case than the commonly used cone and sphere envelope with less conservative. In particular, a novel method is presented to model the pyramid envelope in the dual-quaternion frame. Then, based on the pyramid constraints model properties, a new convex artificial potential function (APF) with only one global minimum is designed, which combines the pose constraints with the control design process. An APF based finite-time control law is proposed to control the rotational and translational motion reaching the desired states in a specified time without violating the constraints. Moreover, the adaptive update law guarantees the control system's robustness in the presence of disturbance and parameter uncertainties. The practical finite-time stability is demonstrated through the finite-time Lyapunov theory. Numerical results are carried out to show the effectiveness of the proposed control law. © 2021 by International Astronautical Federation (IAF). All rights reserved.

关键词： Collision avoidance

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Asymptotic Sampling Behavior for a Class of Nonlinear Robot Systems in Multirate Case

Asymptotic Sampling Behavior for a Class of Nonlinear Robot ...

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Chinese Automation Congress (CAC)

作者： Cheng Zeng Nan Chi Special Key Laboratory of Artifificial Intelligence and Intelligent Control of Guizhou Province GuiYang School of Science GuiZhou Institute of Technology Guizhou China School of Science GuiZhou Institute of Technology GuiYang Guizhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The manuscript aims the stability of the two degree of freedom robot systems based on the corresponding discrete-time plant, which can generate from the sampling in the case of a new multirate input and hold. Furthermore, the asymptotic expression and stable conditions of discretization robot model and corresponding sampling zero dynamics are also desired. Moreover, the control strategy of the corresponding robot plant is acquired by using the sampling zero dynamic stable approach.

关键词： Asymptotic stability Automation 2-DOF Stability analysis Data models Nonlinear dynamical systems Robots

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Output Formation Tracking control for Heterogeneous Multi-Agent Systems with Application to Unmanned Aerial and Ground Vehicles 41

Output Formation Tracking Control for Heterogeneous Multi-Ag...

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第41届中国控制会议

作者： Peixuan Shu Yu Hu Yongzhao Hua Xiwang Dong Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University Shenyuan Honors College Beihang University Beijing Institute of Astronatical Systems Engineering Institute of Artificial Intelligence Beihang University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Distributed output formation tracking control problem for heterogeneous multi-agent systems(HMASs) was studied in this *** HMASs include multi-rotor unmanned aerial vehicles(UAVs) and unmanned ground vehicles(UGVs) with nonholonomic constraints.A formation tracking protocol was proposed for the follower UAVs and UGVs to track the virtual leader's output trajectory while keeping a predefined time-varying *** this protocol,a distributed observer was first designed for each follower to estimate the states of the ***,a local formation controller based on feedback linearization was designed for UAVs,while a nonlinear controller was presented for UGVs to tackle the nonholonomic *** effectiveness of this protocol was proved by the Lyapunov stability ***,a cooperative searching experiment with two quadrotors and a wheeled vehicle was performed under the ultra wide band(UWB) positioning system,and the experiment results matched the simulation well.

关键词： Formation tracking control heterogeneous multi-agent systems UAV UGV

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NBA-guided heuristic sampling algorithm for multi-robot task planning under temporal logic

NBA-guided heuristic sampling algorithm for multi-robot task...

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第43届中国控制会议

作者： Jiong Luo Yongzhao Hua Shunfu Ding Xiwang Dong Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University Institute of Artificial Intelligence Beihang University Institute of Unmanned System Beihang University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Aiming at the task planning problem of multi-robot under linear temporal logic(LTL), this paper proposes an improved sampling planning algorithm based on Nondeterministic Büchi automaton(NBA) guidance. Firstly, this paper defines a kind of LTL task planning problem, which mainly focuses on the meaningful key nodes in the task execution of each robot, and there are many sequential dependencies of task constraints. Then, an improved sampling algorithm framework is proposed,which uses a more efficient way to build a search tree and reduces the number of nodes in the tree. Furthermore, the sampling points are guided by NBA to ensure that sampling is conducive to the advancement of time-series tasks. And considering the task feasible region of each robot, the auction algorithm is introduced to optimize the local matching relationship, which greatly improves the quality of sampling points. Finally, numerical simulation is carried out to solve the LTL task planning problem. The optimality and stability of the algorithm are obviously improved, and the time consumption of this algorithm is obviously better than that of the existing advanced algorithms.

关键词： Multi-robot systems sampling-based planning temporal logic task planning NBA-guided

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A 2-18 GHz 8-W Distributed GaN Power Amplifier Based on Input and Output Matching Network

A 2-18 GHz 8-W Distributed GaN Power Amplifier Based on Inpu...

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International Conference on Microwave and Millimeter Wave technology Proceedings

作者： Ziqi Pu Xu Zhu Liang Qi Yong Wang Pei-Ling Chi Tao Yang University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing China

A high efficiency non-uniform distributed power amplifier (NDPA) based on a 0.15 μm Gallium Nitride (GaN) HEMT process is proposed. The amplifier contains eight amplification cells and uses artificial transmission line theory to design the drain transmission line with decreasing characteristic impedance. To improve the efficiency of the amplifier, the amplifier is class AB biased and designed for optimum impedance matching using the matching networks. The electromagnetic simulation results of the designed amplifier show that the small signal gain of the amplifier is more than 12.6 dB and the saturated output power (P sat ) is more than 39.1 dBm with power-added efficiency (PAE) of larger than 28.5% in the frequency range of 2-18 GHz. The core area of the chip is 3.0×1.8 mm 2 .

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Admittance Based Robot Force control Framework for Server Board Assembly 25

Admittance Based Robot Force Control Framework for Server Bo...

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25th IEEE International Conference on Industrial technology, ICIT 2024

作者： Ma, Yunlong Wang, Yaonan Jiang, Yiming Zhou, Xianen Zhu, Ge Zhu, Qing Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China Xiangjiang Laboratory Hunan China College of Electrical and Information Engineering Hunan University Changsha China School of Robotics Hunan University Changsha China National Engineering Research Center for Robot Vision Perception and Control Technology Hunan University Changsha China ZTE Corporation Shenzhen China

In server board assembly tasks, the effect of vision-based robot assembly schemes is not ideal due to the small installation gap and the blocking of vision. Adding force sensors and force controllers can be a good solution to the above problems and increase the flexibility in the assembly process. In this paper, we propose a force control strategy applied to a server board assembly task. The method is divided into two main parts. In the first part, the zero offset of the force sensor and the load gravity are calibrated and compensated, so that the external force on the load is accurately obtained. In the second part, the admittance controller is designed to achieve compliant behavior between the robot and the environment. Finally, the experimental verification of the board insertion is carried out on the experimental platform. Experimental results verify the effectiveness and practicability of the proposed method. © 2024 IEEE.

关键词： controllers

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Adaptive Spatial Modeling and Multi-Scale Attention Aggregation for Semantic Segmentation of Remote Sensing Images

Adaptive Spatial Modeling and Multi-Scale Attention Aggregat...

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Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Wenying Yang Yuchuan Zhang Yuxuan Jin Yupei Wang Liang Chen National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing Institute of Technology Chongqing Innovation Center Chongqing China School of Artificial Intelligence Jianghan University Wuhan China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing Institute of Technology Beijing China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing Institute of Technology Chongqing Innovation Center Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

As remote sensing technology advances and high-resolution sensors are deployed, the analysis of high-resolution remote sensing images encounters challenging issues, such as intra-class variability, and inter-class similarity, due to the unobvious appearance and complicated background. The high-resolution remote sensing images pose critical issues for precise semantic segmentation due to these fundamental issues. To this end, we propose an adaptive hierarchical aggregation network. Different from the previous approach of modeling semantic interdependencies solely within a single feature map in the channel dimension, we introduce multi-scale channel-wise feature aggregation to capture global contextual dependencies. Meanwhile, we design an adaptive detail-aware module to model long-range spatial dependencies, adaptively extracting effective details from different levels as compensation. Additionally, this module utilizes depth-wise separable convolution to selectively filter out irrelevant spatial details from lower-level feature maps. The outputs of the two modules are fused layer by layer to achieve refined feature representation, thereby generating precise pixel-level segmentation results. Our experiments are conducted on the Vaihingen dataset and the Potsdam dataset. The experimental results demonstrate that the proposed algorithm surpasses several existing state-of-the-art approaches.

关键词： Image sensors Adaptation models Adaptive systems Semantic segmentation Semantics Filtering algorithms Feature extraction Data processing Sensors Remote sensing

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Imitation Learning of Robotic Arm with Hierarchical Training Based on Human Videos

Imitation Learning of Robotic Arm with Hierarchical Training...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Jichuan Liu Jun Shi Jingyi Hou Zhijie Liu Wei He Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China Chinese Aeronautical Establishment Beijing P. R. China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

Human videos encapsulate a diverse spectrum of operational behaviors, serving as invaluable pedagogical resources for imitation learning. In this paper, we introduce an algorithmic framework aimed at emulating expert operational skills gleaned from human videos. The proposed algorithm computes the positional movements of individual steps within a robotic arm by quantifying the disparities between successive frames of the videos, which enables the emulation of skills exhibited in the demonstrations. In detail, we begin by utilizing image translation to seamlessly transition human demonstrations into the realm of the robotic arm, mitigating morphological differences across the multi-joint mechanical structure. Subsequently, we incorporate a keypoint detection network to extract structured information from the transformed images, generating a latent representation that encapsulates motion details for the learning process of the policy network. Experimental results affirm the efficacy of our approach in replicating operational skills.

关键词： Training Automation Imitation learning Semantics Emulation Manipulators Feature extraction

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ROLO-SLAM: Rotation-Optimized LiDAR-Only SLAM in Uneven Terrain with Ground Vehicle

arXiv

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arXiv 2025年

作者： Wang, Yinchuan Ren, Bin Zhang, Xiang Wang, Pengyu Wang, Chaoqun Song, Rui Li, Yibin Meng, Max Q.-H. School of Control Science and Engineering Shandong University Jinan China Shenzhen Key Laboratory of Robotics Perception and Intelligence The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

LiDAR-based SLAM is recognized as one effective method to offer localization guidance in rough environments. However, off-the-shelf LiDAR-based SLAM methods suffer from significant pose estimation drifts, particularly components relevant to the vertical direction, when passing to uneven terrains. This deficiency typically leads to a conspicuously distorted global map. In this article, a LiDAR-based SLAM method is presented to improve the accuracy of pose estimations for ground vehicles in rough terrains, which is termed Rotation-Optimized LiDAR-Only (ROLO) SLAM. The method exploits a forward location prediction to coarsely eliminate the location difference of consecutive scans, thereby enabling separate and accurate determination of the location and orientation at the front-end. Furthermore, we adopt a parallel-capable spatial voxelization for correspondence-matching. We develop a spherical alignment-guided rotation registration within each voxel to estimate the rotation of vehicle. By incorporating geometric alignment, we introduce the motion constraint into the optimization formulation to enhance the rapid and effective estimation of LiDAR's translation. Subsequently, we extract several keyframes to construct the submap and exploit an alignment from the current scan to the submap for precise pose estimation. Meanwhile, a global-scale factor graph is established to aid in the reduction of cumulative errors. In various scenes, diverse experiments have been conducted to evaluate our method. The results demonstrate that ROLO-SLAM excels in pose estimation of ground vehicles and outperforms existing state-of-the-art LiDAR SLAM frameworks. Copyright © 2025, The Authors. All rights reserved.

关键词： Magnetic levitation vehicles

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