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Observer-based Fixed-time Attitude Tracking Control of Rigid Spacecraft with Output Constraints

IEEE Transactions on automation Science and Engineering 2025年 22卷 15878-15888页

作者： Shen, Ganghui Cui, Bing Felicetti, Leonard Xia, Yuanqing Huang, Panfeng Northwestern Polytechnical University Research Center for Intelligent Robotics School of Astronautics Xi’an 710072 China Beijing Institute of Technology School of Automation Beijing 100081 China Cranfield University School of Aerospace Transport and Manufacturing Bedford Cranfield MK43 0AL United Kingdom

This paper investigates the fixed-time attitude tracking control problem for rigid spacecraft subject to external disturbance and output constraints. First, the state transformed function (STF) technique is employed to convert the constrained spacecraft error dynamics into an unconstrained one. Subsequently, a fixed-time disturbance observer (FXTDO) is designed to estimate and reconstruct the lumped disturbance of unconstrained system. Combined with the developed STF, FXTDO and fixed-time integral terminal sliding mode (FITSM) surface techniques, the proposed fixed-time control law provides zero-error attitude tracking with high control precision and chattering avoidance, while the output constraints are never transgressed. The fixed-time stability of the closed-loop system is conducted via the Lyapunov technique and bi-limit homogeneity theory, and the expression of convergence time is also presented. Simulations illustrate the efficiency of the investigated controller. © 2004-2012 IEEE.

关键词： Fixed-time disturbance observer Fixed-time integral terminal sliding mode Output constraints Rigid spacecraft Zero-error attitude tracking

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive Control

A Real-time Local Planner Design for Smart Wheelchairs Based...

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

作者： Guanfeng Yu Han Zhang Zehao Wang Jingchuan Wang Department of Automation Institute of Medical Robotics 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

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities.

关键词： Pedestrians Accuracy Systematics Wheelchairs Estimation Predictive models Real-time systems

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K-BMPC: Derivative-based Koopman Bilinear Model Predictive Control For Tractor-trailer Trajectory Tracking With Unknown Parameters

K-BMPC: Derivative-based Koopman Bilinear Model Predictive C...

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IEEE International Conference on robotics and automation (ICRA)

作者： Zehao Wang Han Zhang Jingchuan Wang Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the corresponding infinite dimensional Koopman bilinear model over the lifting function is equivalent to the original control-affine system. Further, we analyze the propagation and bounds of state prediction errors caused by the truncation in derivative order. The identified finite dimensional Koopman bilinear model would serve as predictive model in the next step. Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem. We linearize the bilinear model around the estimation of the lifted state and control input. Then the bilinear Model Predictive Control problem is approximated by a quadratic programming problem. Further, the estimation is updated at each iteration until the convergence is reached. Moreover, we implement our algorithm on a tractor-trailer system, taking into account the longitudinal and side slip effects. The open-loop simulation shows the proposed Koopman bilinear model captures the dynamics with unknown parameters and has good prediction performance. Closed-loop tracking results show the proposed K-BMPC exhibits elevated tracking precision with the commendable computational efficiency. The experimental results demonstrate the feasibility of K-BMPC.

关键词： Trajectory tracking Computational modeling Estimation Predictive models Control systems Data models Nonlinear dynamical systems

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Multi-Feature-Based Online Remaining Useful Life Prediction of Lithium-Ion Batteries in Stages Using Cascaded Data-Driven Algorithm

SSRN

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SSRN 2023年

作者： Tao, Liujun Wu, Huaiyu Zheng, Xiujuan Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology China

Accurate prediction of remaining useful life (RUL) is very important for the safe and stable operation of battery systems. Considering that it is difficult to directly measure the capacity of lithium-ion batteries during operation, this paper proposes an online hybrid cascaded data-driven prediction algorithm for RUL. Firstly, health indicators (HIs) are extracted from the charge-discharge voltage and incremental capacity curves. Then, the correlation between HIs and battery capacity degradation is quantified by grey relational analysis. And kernel principal component analysis is used to eliminate redundant information of HIs. Secondly, the kernel extreme learning machine based on sparrow search algorithm (SSA-KELM) is selected as the first-level capacity prediction model to establish the relationship between HIs and capacity. The bidirectional long short-term memory network is selected as the secondary-level capacity prediction model, which fuses the preliminary capacity predictions of SSA-KELM. Finally, the battery dataset from NASA and Oxford are used to verify the proposed method. The results demonstrate that the proposed method has strong generalization ability and high prediction accuracy. Quantitatively, the RMSE and MAPE of NASA batteries are within 0.03, while the errors of Oxford batteries are within 0.003. The RUL prediction errors of all lithium-ion batteries are within two cycles. © 2023, The Authors. All rights reserved.

关键词： Lithium-ion batteries

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FDNet: Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Fourier Series and DenseNet

FDNet: Remaining Useful Life Prediction for Lithium-Ion Batt...

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Machine Learning and Computer Application (ICMLCA), International Conference on

作者： Siwen Chen Xiujuan Zheng Shanghai United Imaging Healthcare Co. Ltd Shanghai China Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

To enhance the prediction accuracy of the remaining useful life (RUL) of lithium-ion batteries, this study proposes a novel RUL prediction model, termed FDNet, which integrates Discrete Fourier Series (DFS) and Densely Connected Convolutional Networks (DenseNet). In contrast to traditional methods that rely on one-dimensional (1D) numerical representations of time-series data, this model utilizes a two-dimensional (2D) visual representation for direct RUL prediction. First, the DFS is employed to convert 1D time-series signals into a 2D time-frequency domain, enabling the extraction of high-dimensional features from the original data. Then, these 2D images are subsequently input into DenseNet, which learns the mapping between the image features and the RUL targets. Finally, the proposed model is validated using the NASA lithium-ion battery aging dataset, and the results indicate that FDNet achieves superior prediction accuracy and exhibits notable robustness.

关键词： Lithium-ion batteries Time-frequency analysis Accuracy NASA Predictive models Feature extraction Robustness Numerical models Fourier series Convolutional neural networks

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Human-like Walking of Biped Robot with Foot Rotation Using Passive Metatarsophalangeal Joint 12

Human-like Walking of Biped Robot with Foot Rotation Using P...

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12th International Conference on CYBER Technology in automation, Control, and intelligent Systems, CYBER 2022

作者： Dai, Xiaolin Liu, Yixiang Liu, Xinyu Zang, Xizhe Song, Rui Li, Yibin School of Control Science and Engineering Shandong University Jinan250061 China Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan250061 China Jiangsu Automation Research Institute Lianyungang222000 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In the process of walking, humans are accompanied by the important action of foot rotation. The foot rotates taking the heel and toe as the axis of rotation when landing on and leaving the ground, respectively. Although having high similarity to humans, many biped robots do not reproduce this important feature. This paper describes a method for adding foot rotation into biped robots using the passive metatarsophalangeal joint. Firstly, the biomechanics of human metatarsophalangeal joint during walking is analyzed. Then, the control strategy based on finite state machine for human-like biped walking with foot rotation is proposed for a simplified biped robot model that is composed of eight joints. Finally, the simulation results of the walking gait of the biped robot in MATLAB demonstrate the effectiveness of the control strategy. © 2022 IEEE.

关键词： Rotation

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The generalized synchronization for double-layer delayed coupling complex networks by dynamic soft variable structure control method

The generalized synchronization for double-layer delayed cou...

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2022 Chinese automation Congress, CAC 2022

作者： Qian, Kang Chen, Zhihuan Sun, Yanqin Engineering Research Center for Metallurgical Automation and Measurement Technology Ministry of Education Wuhan University of Science and Technology Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781665465335

This study focuses on the synchronization problem of double-layer complex networks with time delayed coupling. Distinguish from most of previous works, a more general network model is introduced, where the number and the dimension of the nodes can be different between the drive network and the response network. This network model is more close to the practice. In order to obtain the synchronization of double-layer complex networks, an ingenious dynamic soft variable structure controller is proposed, where three sub-controllers and one adaptive observers are designed, and the stability of the controller is demonstrated by a strict mathematical proof. Numerical simulations verify the effectiveness of proposed strategy. © 2022 IEEE.

关键词： Complex networks

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UAV Path Planning Based on Simultaneous Optimization of Monitoring Frequency and Security

UAV Path Planning Based on Simultaneous Optimization of Moni...

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第34届中国控制与决策会议

作者： Yifei Shu Yang Chen Mian Hu Huaiyu Wu Xingang Zhao Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences

UAVs have great potential when applied to persistent monitoring,but there are still problems such as difficulty in ensuring the monitoring frequency and easy leakage of monitoring path ***,it is necessary to increase the UAV monitoring frequency of targets and the randomness of monitoring paths as much as possible on the premise of covering all monitoring *** response to the above problems,this paper studies the UAV path planning problem of simultaneous optimization of monitoring frequency and path *** the evaluation of monitoring frequency and path security based on monitoring overdue time and path entropy,a mathematical model for UAV path planning is *** improved ant colony algorithm based on the monitoring overdue time(Overdue-aware Ant Colony Optimization,OACO) is designed,and finally the UAV flight trajectory with high monitoring frequency and the high monitoring path security is *** simulation results show that the method proposed in this paper can effectively improve the monitoring frequency of each monitoring node to be accessed,improve the security of the UAV monitoring path,which is of great significance for enhancing monitoring security and preventing intrusion.

关键词： UAV persistent monitoring path planning monitoring frequency overdue time security

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Parameter Identification of Chaotic Systems Based on Least Squares Method and Pauta Criterion

Parameter Identification of Chaotic Systems Based on Least S...

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Chinese automation Congress (CAC)

作者： Yu Liu Zhihuan Chen Yaru Qiao Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

In this study, an offline parameter identification approach based on the measured time series of chaotic system is proposed. In this approach, least squares method is firstly introduced to minimize the time series error and Pauta criterion is then employed to pick out the wrong extreme value point. Two representative cases are conducted to verify the effectiveness of our proposed approach. Numerical results are in agreement with theoretical analysis. Comparing to other existing methods, our proposed approach just needs to obtain the measured time series to estimate the parameters, which is simple in theorem and easy to be implemented.

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Logarithmic Sliding-Mode Control for High-Precision Rigid-Body Attitude Tracking

Logarithmic Sliding-Mode Control for High-Precision Rigid-Bo...

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Annual Conference of Industrial Electronics Society

作者： Hanlin Dong Xuebo Yang Zhongbo Chen Xiyao Liu School of Automation Northwestern Polytechnical University Xi'an China Research Institute of Intelligent Control Systems Harbin Institute of Technology Harbin China College of Control Science and Engineering Bohai University Jinzhou China Research Center for Intelligent Robotics Northwestern Polytechnical University Xi'an China

The problem of high-precision attitude tracking is studied in this paper under model uncertainty and external disturbance risk. First of all, the kinematics and dynamics model of rigid body is derived based on the quaternion theory. Then, a standard logarithmic sliding-mode function is constructed using the attitude quaternion and its derivatives of the rigid spacecraft, and the corresponding logarithmic sliding-mode controller is also derived. Finally, the stability of the controlled closed-loop system is demonstrated. Consistenting with theoretical proof, the numerical simulation results showed that the controlled rigid body can quickly track its desired attitude command, even if there are model uncertainty and external disturbance risks.

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