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Edge computing aileron mechatronics using antiphase hysteresis Schmitt trigger for fast flutter suppression

control Theory and Technology 2025年第1期23卷 153-160页

作者： Tangwen Yin Dan Huang Xiaochun Zhang Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai200240China School of Aeronautics and Astronautics Shanghai Jiao Tong UniversityShanghai200240China Control Division Shanghai Aircraft Design and Research InstituteShanghai200210China

An aileron is a crucial control surface for *** jitter or shaking caused by the aileron mechatronics could have catastrophic consequences for the aircraft’s stability,maneuverability,safety,and *** paper presents a robust solution in the form of a fast flutter suppression digital control logic of edge computing aileron mechatronics(ECAM).We have effectively eliminated passive and active oscillating response biases by integrating nonlinear functional parameters and an antiphase hysteresis Schmitt *** findings demonstrate that self-tuning nonlinear parameters can optimize stability,robustness,and *** the same time,the antiphase hysteresis Schmitt trigger effectively rejects flutters without the need for collaborative navigation and *** hardware-in-the-loop simulation results confirm that this approach can eliminate aircraft jitter and shaking while ensuring expected stability and *** conclusion,this nonlinear aileron mechatronics with a Schmitt positive feedback mechanism is a highly effective solution for distributed flight control and active flutter rejection.

关键词： Aileron Edge computing Flutter suppression Mechatronics Nonlinear hysteresis control Positive feedback

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Preserving Topology of Network systems: Metric, Analysis, and Optimal Design

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IEEE Transactions on Automatic control 2024年第6期70卷 3540-3555页

作者： Li, Yushan Wang, Zitong He, Jianping Chen, Cailian Guan, Xinping Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

Preserving the topology from being inferred by external adversaries has become a paramount security issue for network systems (NSs), and adding random noises to the nodal states provides a promising way. Nevertheless, recent works have revealed that the topology cannot be preserved under i.i.d. noises in the asymptotic sense. How to effectively characterize the non-asymptotic preservation performance still remains an open issue. Inspired by the deviation quantification of concentration inequalities, this paper proposes a novel metric named trace-based variance-expectation ratio. This metric effectively captures the decaying rate of the topology inference error, where a slower rate indicates better non-asymptotic preservation performance. We prove that the inference error will always decay to zero asymptotically, as long as the added noises are non-increasing and independent (milder than the i.i.d. condition). Then, the optimal noise design that produces the slowest decaying rate for the error is obtained. More importantly, we amend the noise design by introducing one-lag time dependence, achieving the zero state deviation and the non-zero topology inference error in the asymptotic sense simultaneously. Extensions to a general class of noises with multi-lag time dependence are provided. Comprehensive simulations verify the theoretical findings. © 1963-2012 IEEE.

关键词： Network topology

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Resilient control of flexible hypersonic vehicles against unmatched distributed faults

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Chinese Journal of Aeronautics 2024年第5期37卷 60-70页

作者： Dong ZHAO Wenjing REN School of Artificial Intelligence Anhui UniversityHefei 230601China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China School of Electrical Engineering and Automation Hefei University of TechnologyHefei 230009China

This paper studies a robust fault compensation and vibration suppression problem of flexible hypersonic *** controlled plant is represented by a cascade system composed of a nonlinear Ordinary Differential Equation(ODE)and an Euler-Bernoulli Beam Equation(EBBE),in which the vibration dynamics is coupled with the rigid dynamics and suffers from distributed faults.A state differential transformation is introduced to transfer distributed faults to an EBBE boundary and a longitudinal dynamics is refined by utilizing T-S fuzzy IF-THEN rules.A novel T-S fuzzy based fault-tolerant control algorithm is developed and related stability conditions are *** robust exponential stability and well-posedness are proved by using the modified l_(0)-semigroup based Lyapunov direct approach.A simulation study on the longitudinal dynamics of flexible hypersonic vehicles effectively verifies the validity of the developed theoretical results.

关键词： Flexible hypersonic vehicles ODE-EBBE cascade Robust exponential stability Unmatched distributed fault compensation Vibration suppression

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controllability of heterogeneous networked sampled-data systems

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Science China(Information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Multi-Time-Scale Variational Mode Decomposition-Based Robust Fault Diagnosis of Railway Point Machines Under Multiple Noises

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Chinese Journal of Electronics 2024年第3期33卷 814-822页

作者： Junqi LIU Tao WEN Guo XIE Yuan CAO Clive Roberts Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology The School of Electronic and Information Engineering Beijing Jiaotong University Birmingham Centre for Railway Research and Education University of Birmingham

The fault diagnosis of railway point machines(RPMs) has attracted the attention of engineers and *** have studies considered diverse noises along the *** fulfill this aspect,a multi-time-scale variational mode decomposition(MTSVMD) is proposed in this paper to realize the accurate and robust fault diagnosis of RPMs under multiple *** decomposes condition monitoring signals after coarse-grained processing in varying *** this manner,the information contained in the signal components at multiple time scales can construct a more abundant feature space than at a single *** the experimental validation,a random position,random type,random number,and random length(4R) noise-adding algorithm helps to verify the robustness of the *** adequate experimental results demoristrate the superiority of the proposed MTSVMD-based fault diagnosis.

关键词： Railway point machines Fault diagnosis Multi-time-scale Variational mode decomposition

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Research on High-Precision Contouring control of Gantry Dual-Drive H-Type Planar Motion Platform

Research on High-Precision Contouring Control of Gantry Dual...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Chen, Chao Li, Haoyu Gu, Chaochen Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai China

ISBN: (纸本)9798350372601

The H-type two-axis linear plane motion platform with dual gantry drive is one of the most crucial components in contour processing equipment. The dual gantry structure employs independently controlled dual-side motors to collectively drive the motion of the gantry crossbeam axis. While the introduction of dual gantry drive brings higher single-axis positioning accuracy and greater operational speed to contour processing *** these issues, this paper starts with the dynamic modeling of the dual gantry H-type plane motion platform. It modifies and extends the task coordinates within the framework of the Global Task Coordinate Frame (GTCF). Subsequently, it effectively addresses the coordination between axes and the synchronization of dual drive in the task space, obtaining both motion coordination and dual-axis synchronization capabilities, leading to more accurate contour error calculation and evaluation. The paper includes a comprehensive design of experiments to assess the dual gantry synchronization performance in contour control. The proposed control method is compared with the traditional GTCF-based contour control method, demonstrating the effectiveness and superiority of the integrated coordination and synchronization contour control method. © 2024 IEEE.

关键词： Contour followers

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Online-Learning-Enabled Distributionally Robust Motion control via Uncertainty Propagation and Ambiguity Set Compression 63

Online-Learning-Enabled Distributionally Robust Motion Contr...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Wang, Han Ning, Chao Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai China

ISBN: (纸本)9798350316339

We develop a safe, efficient, and flexible motion control framework for collision-free navigation of robots in uncertain and dynamic environments. With the gathered real-time data at each control time, the motion distribution of obstacles is estimated from data streams by leveraging the Dirichlet process mixture model. We propose a novel uncertainty propagation method, which theoretically admits the derivation of obstacle position distributions over the entire prediction horizon only based on the current position and motion distribution of obstacles. To enhance the robustness against estimated distribution errors, an ambiguity set utilizing local-moment information of position distributions is constructed. Additionally, we introduce a compression scheme to automatically adjust the complexity (granularity) of the ambiguity set by aggregating distributions that are close in Wasserstein space, thereby flexibly striking a trade-off between control performance and computation time. The distributionally robust collision avoidance constraint based on the compressed ambiguity set is reformulated into separating hyperplanes, which are applied in the model predictive controller to obtain the optimal collision-free trajectory. To resolve the infinite-dimensionality issue inherent in the computation of the separating hyperplanes, we equivalently derive a tractable semi-definite programming formulation exploiting distributionally robust optimization techniques. The efficacy of the proposed framework is demonstrated through simulation. © 2024 IEEE.

关键词： Predictive control systems

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Multi-camera Registration with Small FOV Based on Pose Graph Optimization 1

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13th International Conference on Green Intelligent Transportation systems and Safety, GITSS 2022

作者： Chen, Long He, Xing He, Yuesheng Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9789819730520

ISBN: (纸本)9789819730513

Multiple roadside cameras sense and localize autonomous vehicles for Automated Valet Parking. The accurate multi-camera registration into a shared coordinate system is of great importance. Owing to the sparse and distributed placement of multiple cameras, there is a very small field of view (FOV) between the cameras. The multi-camera registration is complex and dependent on human expertise. Therefore, a multi-camera registration method with small FOV based on pose graph optimization is proposed in this paper to automatically generate the extrinsic. The moving checkerboard in the public FOV is utilized as a reference for calibration. The optimization method constructs a pose graph to store camera and checkerboard pose and solves the pose graph by calculating checkerboard reprojection errors. To increase the overall flatness of the ground, ground plane assumptions can be utilized to further optimize the parameters. The experimental results show that the proposed method has greater calibration accuracy on the constructed multiple RGB-D camera system, as well as being simple and efficient in the real calibration procedure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Automated valet parking Automatic calibration Multi-camera registration Pose graph optimization Small FOV

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Event-Triggered Optimal Nonlinear systems control Based on State Observer and Neural Network

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Journal of systems Science & Complexity 2023年第1期36卷 222-238页

作者： CHENG Songsong LI Haoyun GUO Yuchao PAN Tianhong FAN Yuan Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China

This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time ***,the authors propose an online algorithm with critic and actor NNs to solve the optimal control problem and provide an event-triggered method to reduce communication and computation ***,the authors design weight estimation for critic and actor NNs based on gradient descent method and achieve uniformly ultimate boundednesss(UUB)estimation ***,by using bounded NN weight estimation and dead-zone operator,the authors propose a triggering condition,prove the asymptotic stability of closed-loop system from Lyapunov stability perspective,and exclude the Zeno ***,the authors provide a numerical example to illustrate the effectiveness of the proposed method.

关键词： Event-triggered control neural network optimal control state observer

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Fast Super-Resolution DOA Estimation for Unknown Number of Radiation Sources Based on Complex Convolutional Neural Networks 2

Fast Super-Resolution DOA Estimation for Unknown Number of R...

引用

2nd IEEE International Conference on signal, Information and Data processing, ICSIDP 2024

作者： Ma, Hui Liu, Xianpeng Liu, Hongwei Yang, Junxiang Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Xian Institute of Electromechanical Information Technology Electromechanical Dynamic Control Laboratory Xi'an China

ISBN: (纸本)9798331515669

To address the high computational complexity of traditional Direction of Arrival (DOA) estimation techniques and the limitations of previous neural networks in handling fixed signal sources, a new signal processing model was developed. This model employs sparse representation methods and deep learning through complex convolutional neural networks(CCNN). Focused research on the array's performance under unknown radiation sources using the complex convolutional neural network algorithm for super-resolution DOA estimation was conducted in a PyTorch environment. The results indicate that the complex convolutional model has a lower DOA computation complexity and higher precision in handling unknown radiation sources. After incorporating sparse representation with sampled data through the CCNN model for DOA estimation, an improvement in estimation accuracy and a reduction in computational complexity were observed compared to methods relying solely on sparse representation. Additionally, this model can effectively detect incoming waves from unknown radiation sources, unlike previous neural networks. © 2024 IEEE.

关键词： Convolutional neural networks

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