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42nd Chinese control Conference, CCC 2023

作者： Li, Wen Su, Jinya Li, Shihua School of Automation Southeast University Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing210096 China

ISBN: (纸本)9789887581543

In this study, we investigate the control problem of electronic throttle systems in the presence of practical challenges such as disturbances and measurement noises. To address these challenges, we propose an adaptive augmented Kalman filter (AAKF) based control approach that combines the strengths of extended state observer in disturbance estimation and adaptive Kalman fil-ter in adaptive noise filtering. The outputs of AAKF are integrated into the Backstepping control design, resulting in a composite control that concurrently achieves fast disturbance rejection and noise suppression. We conduct a comparative simulation study against conventional methods without adaptive filtering to validate the effectiveness of the proposed AAKF-based control strat-egy, which exhibits superior position control accuracy and disturbance attenuation performance. We envision that our proposed control strategy will contribute to improving vehicle power, fuel economy, and emission performance. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Adaptive filtering

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Fixed-Time Adaptive Tracking Event-Based control for Uncertain Stochastic Nonlinear systems With Output Constraints

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International Journal of Robust and Nonlinear control 2025年

作者： Wang, Kun Xie, Liping Yuan, Yixuan Zhang, Kanjian Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China

This paper focuses on an adaptive fixed-time tracking control problem for nonstrict-feedback stochastic nonlinear systems with unknown control coefficients and output constraints. To overcome this problem, this article introduces a unified system transformation function to facilitate the transition of the system from constrained to unconstrained states. Subsequently, a fuzzy approximation principle is utilized for handling unknown terms in the transformed system, while Nussbaum functions are employed to manage unknown control directions. Then, combined with the backstepping technique, an adaptive fixed-time tracking controller is designed with an event-triggered mechanism, which not only achieves the convergence of tracking errors within a limited time independent of initial states, but also conserves resources. Under the proposed tracking controller, practical fixed-time stability can be ensured for the closed-loop system. Finally, two simulation examples demonstrate the efficacy of the proposed scheme. © 2025 John Wiley & Sons Ltd.

关键词： Stochastic systems

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Study of multilevel feature weighted fusion based image classification method for silicon single crystal growth process

Study of multilevel feature weighted fusion based image clas...

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2024 International Conference on Image Processing and Artificial Intelligence, ICIPAl 2024

作者： Xie, Ruidong Zhang, Zheqi Zhu, Pei Ma, Wenle Yi, Yingmin Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

ISBN: (纸本)9781510681514

A multi-level feature weighted fusion based image classification method for silicon single crystal growth process has been proposed to address the issue of the long silicon single crystal pulling times at industrial sites, which prevents timely understanding of the crystal growth process. A multi-level feature weighted fusion method was employed to identify and classify the growth process of silicon single crystals. A Czochralski single crystal silicon growth process recognition system was then designed. A comparison of the experimental results obtained from this design with the traditional single image classification method clearly showed that using different levels of silicon single crystal image information simultaneously effectively improved the accuracy of silicon single crystal growth image classification. © 2024 SPIE.

关键词： Image classification

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Improved Kalman Filtering Algorithm Based Multi-Sensor Integration for Silicon Single Crystal Growth Process 7

Improved Kalman Filtering Algorithm Based Multi-Sensor Integ...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Xie, Ruidong Zhu, Pei Ma, Wenle Zhang, Zheqi Yi, Yingmin Guo, Zheng Xi'an University of Technology Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an710048 China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China

ISBN: (纸本)9798350363173

The study primarily delves into addressing the data filtering challenge inherent in the silicon single crystal growth process by proposing a multi-sensor integrated detection approach. This approach is designed to alleviate the diminished filtering accuracy resulting from the reliance on a single sensor and the conventional Kalman filtering algorithm. By utilizing an enhanced adaptive Kalman filtering algorithm and the maximum likelihood estimation criterion to incorporate the innovation variance directly into the gain calculation of the Kalman filter, dynamic adjustment of the estimation model is achieved while interference from system noise and measurement noise is reduced. Finally, simulation-based comparative experiments between the adaptive and conventional Kalman filtering algorithms are performed. The results show that the performance of the adaptive Kalman filtering algorithm is superior to that of the conventional Kalman filtering algorithm in terms of accuracy and stability when detecting signals from multiple sensors. The research findings furnish dependable data support for refining the decision-making process in crystal growth technology, augmenting the precision and scientific integrity of crystal safety production scheduling and decision-making endeavors. © 2024 IEEE.

关键词： Kalman filters

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Ensuring Port Safety: Improved YOLOX and DeepSORT for Accurate Detection and Tracking of Trucks and Truck Drivers 42

Ensuring Port Safety: Improved YOLOX and DeepSORT for Accura...

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42nd Chinese control Conference, CCC 2023

作者： Zheng, Xueqin Su, Jinya Yang, Jun School of Automation Southeast University Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Nanjing210096 China

ISBN: (纸本)9789887581543

An optimized YOLOX+DeepSORT method is proposed to accurately detect and track container trucks and truck drivers at the working position of automated rubber tire gantries in ports, while ensuring their safety during the whole working process. In the proposed method, the improved YOLOX performs object detection and its output is used as the input for multi -object tracking using DeepSORT. The improved YOLOX model is developed through replacing standard convolution with depthwise separable convolution, adding the convolutional block attention module to enhance feature extraction, and using Focal Loss in the loss function to address sample imbalances. Comparative experiments were carried out on a self-built dataset, showing a 4.32% increase in mAP and improved reasoning speed for improved YOLOX compared to the original YOLOX. Furthermore, the optimized method shows a 3.57% increase in Multi-Object Tracking Accuracy and a 1.73% increase in Multi-Object Tracking Precision compared to the benchmark YOLOX+DeepSORT. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Object detection

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Robust Speed Regulation of PMSM Under Disturbances and Noises Using Composite Model Predictive control 42

Robust Speed Regulation of PMSM Under Disturbances and Noise...

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42nd Chinese control Conference, CCC 2023

作者： Mao, Linxuan Su, Jinya Li, Shihua School of Automation Southeast University Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9789887581543

This paper presents a single-loop Model Predictive control strategy that incorporates a reduced-order Generalized Proportional Integral Observe and a Kalman filter to enhance the speed regulation of Permanent Magnet Synchronous Motor systems in the presence of complex disturbances and measurement noises. The proposed controller design seamlessly integrates the predictive control, disturbance observer, and state filter components, and it was evaluated through simulation comparisons. The performance of the proposed method is evaluated using various metrics, including maximum velocity drop, recovery time, and variance of steady-state error, which demonstrate its superior response performance and anti-disturbance ability when compared to other existing methods without state filtering. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Model predictive control

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A Dynamic control Strategy for Enhancing the Energy Extracting Capability of Magnetic Field Energy Harvesters in Sensor Nodes of Power Equipment 14

A Dynamic Control Strategy for Enhancing the Energy Extracti...

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14th International Conference on Power and Energy systems, ICPES 2024

作者： Gao, Yuan Fan, Libo Huang, Jiabin Han, Rongjie Sun, Min University of Electronic Science and Technology of China Power system wide area measurement and control of the Key Laboratory of Sichuan Province Chengdu China The State Grid Zhejiang Electric Power Company Hangzhou China

ISBN: (纸本)9798350391329

With the widespread application of sensors nodes in power equipment, providing a stable energy supply for these sensors has become a significant challenge. Traditional batterypowered solutions are costly and difficult to install. The development of energy harvesting technology offers a new technical approach to address this challenge. This paper mainly investigates how to enhance the energy harvesting power of Magnetic Field Energy Harvesters (MEH) under conditions where the magnetic field around power equipment is limited. A dynamic control method is proposed to improve the energy harvesting power of MEH. The fundamental idea of dynamic control is to precisely control the MOSFETs in the rectifier, dynamically adjusting the switching times of the energy harvesting interval to be symmetric around the peak current of the primary side, thereby significantly enhancing harvesting efficiency. This method is particularly applicable when the magnetic core enters the soft saturation region, causing the energy harvesting interval to be less than T/2. Experimental results show that under constant voltage load, dynamic control effectively adjusts the energy harvesting interval, maximizing the current extracted during this interval, thereby effectively increasing energy harvesting power. Compared to passive rectification, active rectification under dynamic control increases the energy harvesting power by 76%, and the power factor of active rectification is 1.7 times that of passive rectification. The research findings provide important theoretical support and practical significance for the application of magnetic field energy harvesting technology in sensor nodes. © 2024 IEEE.

关键词： Sensor nodes

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Consensus-based Distributed Augmented Lagrangian Method for Nonconvex Optimization with Coupled Constraints

Consensus-based Distributed Augmented Lagrangian Method for ...

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2022 Chinese Automation Congress, CAC 2022

作者： Su, Yanxu Anhui University School of Artificial Intelligence Hefei230601 China Ministry of Education Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Nanjing210096 China

ISBN: (纸本)9781665465335

In this paper, we study the nonconvex optimization problems with consideration of globally coupled constraints. The constrained optimization problem is converted into an augmented Lagrangian function, and a distributed primal-dual algorithm is exploited in the context of finite-time consensus for solving such a problem. Particularly, we do not require the globally coupled constraints to be separable. Instead, we introduce some local variables for estimating the constraint violations. Under some mild assumptions in the research of nonconvex optimization, we prove the convergence of the presented algorithm to a KKT point of the problem. The numerical experiment verifies the correctness and the effectiveness of the theoretical results. © 2022 IEEE.

关键词： Constrained optimization

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The Optimal Duty Cycle Model-Predictive control of PMSM Used for Satellite Payload 1

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17th Annual Conference of China Electrotechnical Society, CES 2022

作者： Li, Jialin Chen, Zhen Hu, Hengzai Liu, Xiangdong Bao, Liang School of Automatic Beijing Institute of Technology Beijing100081 China Key Laboratory of Drive and Control of Servo Motion System Ministry of Industry and Information Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision for Complex System Beijing100081 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (数字)9789819904082

ISBN: (纸本)9789819904075

Model-predictive control is emerging as an advanced control strategy for its feature that the state variables can be predicted according to the math model of the control system. In the PMSM drive application, conventional model-predictive control strategy induces current ripple due to the fact that the optimal voltage vector always acts on the system for the whole control period. In order to restrain the current ripple, the idea of duty cycle control is taken into MPC by inserting a zero vector into the optimal non-zero vector and regulating the duty cycle of non-zero vector. In this paper, the optimal duty cycle FSC-MPC strategy based on two different principles is investigated. Principle A is that the estimation is equal to the reference at the end of control cycle, and principle B is that the area under trace of the estimation is equal to that of reference. The calculation of duty based on the two different principles and the flow chart of the strategy are introduced in detail. Finally, the effectiveness of the optimal duty cycle FSC-MPC is firstly verified by the simulation, and then verified by the experimental results, which is implemented on the PMSM driver of the DQ-1 satellite payload. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Model predictive control

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Stabilization of Perturbed Continuous-Time systems Using Event-Triggered Model Predictive control

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IEEE Transactions on Cybernetics 2022年第5期52卷 4039-4051页

作者： Wang, Mengzhi Sun, Jian Chen, Jie Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex System Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

In this article, event-triggered model predictive control (EMPC) of continuous-time nonlinear systems with bounded disturbances is studied. Two novel event-triggered control schemes are proposed. In the first strategy, an event-triggering condition, designed based on the state error between the actual system state and the optimal one, with an absolute threshold is considered. In the second strategy, an event-triggering condition with a mixed threshold is designed to further save the computational resources. The minimal interevent times of both event-triggered control schemes are obtained to avoid the Zeno behavior. Sufficient conditions of recursive feasibility for these two triggering strategies, which refer to the prediction horizon, the triggering level, and the disturbance bound, are obtained, respectively. Input-to-state practical stability (ISpS) of both event-triggered control systems is established without requiring the system state entering the terminal set in finite time, respectively. Finally, the numerical simulation shows the effectiveness of the proposed methods. © 2013 IEEE.

关键词： Model predictive control

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