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检索条件"机构=Department of Control Science and Engineering Harbin Inst. of Technology Harbin"

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Non-Singular Fast Terminal Sliding Mode control with Super-Twisting ESO for Spacecraft Formation Flying Systems

Non-Singular Fast Terminal Sliding Mode Control with Super-T...

引用

2023 China Automation Congress, CAC 2023

作者： Li, Yufei Tang, Feilong Zhong, Xiaoqing Xiang, Zhihua Ju, Yinhao Huan, Baizheng School of Aerospace Engineering Beijing Institute of Technology Beijing China Harbin Institute of Technology Department of Control Science and Engineering Harbin China Institute of Telecommunication Satellite China Academy of Space Technology Beijing China

ISBN: (纸本)9798350303759

In this article, we analyze how spacecraft formation can save more fuel and achieve more accurate relative position motion in the configuration control under the influence of external disturbances and perturbations. A non-singular fast terminal sliding mode controller(NFTSMC) combined with Super-Twisting extended state observer(STESO) is proposed for disturbance rejection control of spacecraft formation configuration. In this paper, we will establish the kinematics model of spacecraft relative motion, and linearize this model. Then, the convergence of STESO and the stability of the combination of NFTSMC and STESO are analyzed respectively. Finally, sufficient numerical simulations will be provided to verify the feasibility of the algorithm. © 2023 IEEE.

关键词： Disturbance rejection

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Estimation of RoA for Nonlinear Systems Based on Gaussian Processes

Estimation of RoA for Nonlinear Systems Based on Gaussian Pr...

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International Conference on Electronic engineering and Informatics (EEI)

作者： Yucheng Chen Yupeng Zhu Hongming Zhu Quanqi Zhang Chengwei Wu Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

This paper employs Gaussian Processes (GPs) to estimate uncertainty dynamics inherent in nonlinear systems. A control policy ensuring the system satisfies initial stability constraints is derived using linear quadratic regulator (LQR). By modeling the Lyapunov function based on uncertain dynamics as GPs, the stability of the system dynamics in the Lyapunov sense is ensured. To discretize the Lyapunov function with Lipschitz continuity, a finite number of discrete points are chosen to represent the properties of the function. The region of attraction (RoA) based on Lyapunov function is widely utilized as a safe constraint in the field of control. Additionally, the maximum uncertainty dynamics are chosen as the boundary for exploration to expand the evaluation of the RoA. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed approach.

关键词： Uncertainty Regulators System dynamics Estimation Gaussian processes Stability analysis Nonlinear dynamical systems Informatics Thermal stability Lyapunov methods

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Active steering angle tracking control of steer-by-wire system under different external disturbance

Active steering angle tracking control of steer-by-wire syst...

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Chinese control and Decision Conference, CCDC

作者： Xin Zhao Linhui Zhao Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In the context of vehicle intelligence, steer-by-wire (SbW) has great potential for development and has become a current research hotspot. A challenging key technology of the SbW system is the steering angle tracking control under the effect of wheel-ground coupling resistance torque. In this paper, a method is proposed to provide the wheel-ground coupling resistance torque of the system by controlling the motor to track the desired torque to apply reaction force to the SbW system, which is referred to as reaction force analog control. The reaction force analog control strategy based on proportional integral (PI) control is proposed for the brushless DC motor (BLDC) with Hall sensor. Meanwhile, a method for estimating the angle and velocity of the BLDC based on Hall sensor is presented for field-oriented control. Besides, a steering angle tracking control strategy based on PI control is designed for the permanent magnet synchronous motor (PMSM) with resolver to achieve excellent steering performance. The proposed algorithms are validated with different driving test cycles from ISO standards via hardware-in-loop experiments. The experimental results show that the designed reaction force analog control can accurately track the desired resistance torque and the proposed active steering angle tracking controller achieves high-precision steering angle tracking performance under external disturbance, which it well meets the requirements of embedded applications.

关键词： Resistance Couplings Uncertain systems Torque Accuracy Roads Force

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A Reinforcement Learning Solution to the Nonlinear Spacecraft Pursuit-Evasion Game Problem

A Reinforcement Learning Solution to the Nonlinear Spacecraf...

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IEEE International Conference on Cyber technology in Automation, control, and Intelligent Systems

作者： Haoqi Huang Guangtao Ran Yueyong Lyu Guangfu Ma Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

The pursuit-evasion game of non-cooperative spacecrafts under nonlinear dynamics is currently a hot topic in orbital gaming. We describe the above pursuit-evasion game model using differential game theory, transforming the gaming problem into a bilateral optimal control problem. Using elliptical orbit line-of-sight (LOS) dynamics with simple field-of-view constrains as the system model, we solve the Nash equilibrium solution for the two-body pursuit-evasion under the assumption of complete information. Due to the difficulty in obtaining analytical solutions for the Nash equilibrium, we adopt a reinforcement learning (RL)-based adaptive dynamic programming method. We obtain the approximate Nash equilibrium solution with RL method eventually and provide a successful simulation example.

关键词： Space vehicles Optimal control Line-of-sight propagation Games Reinforcement learning Differential games Nash equilibrium Orbits Nonlinear dynamical systems Dynamic programming

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Generative Adversarial Network with In-Betweening for Fine-Grained Skeleton-Based Action Generation

Generative Adversarial Network with In-Betweening for Fine-G...

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Annual Conference of Industrial Electronics Society

作者： Xiangyuan Qi Zhen He Qiang Wang Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Human action generation has shown critical value in both industry application and academic research, especially fine-grained skeleton-based action generation. At present, there are several main ways to achieve fine-grained skeleton-based action generation. In this work, we utilize a generative adversarial network with in-betweening, in order to generate natural and continuous skeleton sequences and better capture complex motion details. In-betweening can be viewed as a prediction task based on the past and future context. Besides, it is convenient to control the result in a personalized way and combine the framework with other network structures to further improve the performance. In particular, two simple discriminators are applied on different timescales and LSTM serves as the foundation of the action generator because of its capability of effectively capturing long-term dependencies and processing sequence data of different lengths. The target noise added to the input of the generator can contribute to the robustness of the system and further improve the performance. Moreover, a novel Tai Chi dataset composed of fine-grained skeleton-based action data is created using high quality motion capture technology. The model is evaluated on two fine-grained skeleton-based datasets, LaFAN1 and Tai Chi, which contain common daily actions and professional sports actions respectively, and it achieves superior performance both qualitatively and quantitatively.

关键词： Hands Training Noise Generative adversarial networks Generators Robustness Motion capture Skeleton Long short term memory Sports

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Friction Modeling and control Compensation for Electromechanical Braking Systems

Friction Modeling and Control Compensation for Electromechan...

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Conference on Vehicle control and Intelligence (CVCI)

作者： Jing Houhua Lin Qinggan Liu Mingqi Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798331504892

ISBN: (纸本)9798331504908

Influenced by the electrification and intelligence of automobile chassis, electromechanical braking has become the future brake-by-wire trend choice by virtue of its simpler mechanism and faster servo performance, while system friction, as a key factor of its servo control, must be handled properly. This work studies the system friction modeling of electromechanical braking system and the corresponding control compensation approach. First, by evaluating the structure and working principle of the electromechanical braking system, the system model is produced, the braking control test rig is built and the system characteristic test is carried out. Then, the friction model parameters were identified from the experimental data based on the examination of system features. Finally, the brake control performance after friction compensation was experimentally validated by the physical rig, which verified the effectiveness of the friction model and its control compensation.

关键词： Analytical models Accuracy Parameter estimation Friction Force Clamps Force control Servomotors Optimization Testing

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Hyperparameter Optimization of Object Detection Networks Based on Large Language Models

Hyperparameter Optimization of Object Detection Networks Bas...

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Annual Conference of Industrial Electronics Society

作者： Yushuo Hu Qiang Wang Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Abstract: Since the emergence of deep learning, the configuration of hyperparameters has been one of the most significant problems that people have paid attention to. However, traditional hyperparameter optimization techniques typically have drawbacks such as expensive calculation consumption and lengthy training time. With the development of large language models (LLMs), particularly models such as generative pre-trained transformer (GPT), it is achievable to utilize the models’ analysis ability to guide parameter space search. This paper investigates the use of LLMs for hyperparameter optimization in machine learning problems. To evaluate the effectiveness of this strategy, four object detection models, including YOLOv5, YOLOv8, Faster R-CNN, and R-FCN, were used to conduct experiments. At the same time, we compared the distinctions between this approach and traditional ways. The experimental results indicate that combining LLMs with the hyperparameter optimization process can perform comparably or better than conventional methods.

关键词： YOLO Deep learning Training Analytical models Neural networks Hyperparameter optimization Transformers Neural architecture search Optimization Information analysis

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Lightweight Object Detection Networks Oriented for Embedded Weeding

Lightweight Object Detection Networks Oriented for Embedded ...

引用

IEEE inst.umentation and Measurement technology Conference

作者： Yushuo Hu Qiang Wang Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Compared to other techniques, mechanical weeding has many benefits that support more accurate weeding operations without polluting the environment. The primary challenge is precisely locating target crops in complex surroundings, and deep learning methods are suitable for this kind of work. In this paper, in order to apply object detection approaches to agricultural weeding, we build two object detection models, YOLOv5 and YOLOv8, which are based on a total of 838 labeled images of corn seedlings in farmland. The two models were then implemented on different embedded systems, and their performance was compared. Model compression is also used to optimize network performance and enhance model deployment on embedded devices. Finally, we applied it to the actual project, and the results demonstrated that the object detection model could accurately identify target corn seedlings while significantly reducing computation and parameters.

关键词： YOLO Performance evaluation Deep learning Accuracy Embedded systems Image coding Computational modeling

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Anti-Unwinding Robust Adaptive Sliding Mode Attitude control for Rigid Spacecraft

Anti-Unwinding Robust Adaptive Sliding Mode Attitude Control...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Faian Shahid Hao Luo Shafqat Ali Muhammad Zubair Ashraf Jahan Zaib Bhatti Control and Simulation Center Harbin Institute of Technology Harbin China Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

Reliable spacecraft attitude control during maneuvers is essential for the success of space missions. This paper introduces a robust adaptive control strategy for rigid spacecraft attitude tracking capable of dynamically adjusting control system parameters to respond to inherent parametric uncertainties and external disturbances. The primary objective is to ensure the convergence of unit quaternion-based spacecraft system states in the presence of inertial uncertainties and disturbances while avoiding unwinding phenomena. The proposed method uses a switching function designed to drive the error trajectories of rigid spacecraft onto a sliding manifold containing two equilibria. Subsequently, a robust adaptive attitude tracking control is developed to handle uncertainties and disturbances while driving the system error states toward the origin along the sliding surface. In consideration of safe actuator operation, the chattering phenomenon is minimized by utilizing a boundary layer function. Constraint is employed on the designed parameters of the adaptive function in such a way that the system states converge within this boundary layer. The Lyapunov stability theory demonstrates the stability analysis of the attitude control system for rigid spacecraft. Numerical simulations validate the effectiveness, reliability, and anti-unwinding capabilities of the proposed approach.

关键词： Space vehicles Actuators Uncertainty Attitude control Switches Reliability theory Numerical simulation

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Subspace-Aided SIR Approach with Application to Indicator Diagram Estimation of BPUs

Subspace-Aided SIR Approach with Application to Indicator Di...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Xinyu Qiao Jilun Tian Xiaoyi Xu Jiusi Zhang Hao Luo Department of Control Science and Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875

Aiming at the difficulty in the estimation of indicator diagrams for electrical parameters of beam pumping units (BPUs), a subspace-aided stable image representation (SIR) approach is proposed for the search of the mapping relationship among electrical and force parameters and the implementation of accurate estimation of indicator diagrams. The advantage of the proposed method is a data-driven implementation, which does not require analyzing the dynamic relationship and model knowledge of the BPUs. Further, through collecting data from the BPUs, the Hankle matrix is constructed to form signal spaces. Then, the SIR can be calculated by performing LQ decomposition, namely, finding the mapping relationship among electrical and force parameters, which is helpful for using the electrical parameter estimation indicator diagram. Eventually, the effectiveness and applicability of the proposed method are verified through the actual data of BPUs.

关键词： Industrial electronics Analytical models Parameter estimation Accuracy Force Dynamics Estimation

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