检索结果-内蒙古大学图书馆

第43届中国控制会议

作者： Haiming Wang Lijun Sun Wei Wu Peilun Xie Xin Shao Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineer Tianjin University School of Intelligent Manufacturing Tianjin Sino-German University of Applied Sciences

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Based on traditional Proportional-Intergral(PI) vibration amplitude controllers, the Coriosis Mass Flowmeter(CMF)shows slow response and even stopping vibration under gas-liquid two-phase *** solve this problem, WHO-BP(Wild Horse Optimizer-Back propagation) adaptive controller is proposed in this paper. BP neural network is designed to adaptively adjust the parameters of PI controller. WHO is ued to find the optimal solution of the initial weight matrix of BP neural network to prevent vanishing gradient and exploding gradient. The effectiveness of the WHO-BP adaptive controller for improving the drive performance and measurement performance of CMF is verified by experimental and simulations results under gas-liquid two-phase flow conditions. Finally, not only the vibration amplitude stability and robustness of CMF as the flow pattern switching, but also the measurement accuracy under complex flow conditions are improved by proposed algorithm.

关键词： Coriolis Mass Flowmeter gas-liquid two-phase flow Wild Horse Optimizer BP neural network adaptive controller

来源：评论

学校读者我要写书评

暂无评论

The rapidity of phase difference calculation algorithm of Coriolis Mass Flowmeter and its effect on measurement

The rapidity of phase difference calculation algorithm of Co...

引用

第43届中国控制会议

作者： Wei Wu Lijun Sun Haiming Wang Shuai Dong Xin Shao Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineer Tianjin University School of Intelligent Manufacturing Tianjin Sino-German University of Applied Sciences

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Coriolis Mass Flowmeter(CMF) is widely used in industrial and life *** the complexity of working conditions increase,the signal processing algorithm of CMF requires higher *** this paper,the performance of Complex Coefficient Filter(CCF),Quadrature Demodulation(QD) and Hilbert algorithms is compared in terms of the rapidity of the algorithm,taking into account the anti-noise ability and *** pulsating flow signal simulation,the tracking ability of the three algorithms for abrupt signals is *** improved two-phase flow random walk model simulation,the fast solving performance and anti-noise ability of the three algorithms are compared,and the execution time of the algorithms is *** simulation results show that the capabilities of CCF and QD are better than *** of pulsating flow and gas-liquid two-phase flow are designed to verify the performance of CCF and QD *** experimental results show that the measurement accuracy and repeatability of CCF algorithm are better than that of QD in pulsating *** gas-liquid two-phase flow,the measurement error of CCF algorithm is smaller than that of QD,and the repeatability is better than that of QD except for some *** the liquid flow rate is constant,with the increase of gas content,the measurement error of the CCF algorithm is smaller than that of *** the flow pattern changes,the CCF algorithm can track the signal *** the speed of the algorithm increase,the ability of tracking changing signals is stronger,which is benefit for improving the accuracy of measuring gas-liquid two-phase flow and pulsating flow.

关键词： Coriolis mass flowmeter Phase difference algorithm Rapidity Gas-liquid two-phase flow Pulsating flow

来源：评论

学校读者我要写书评

暂无评论

Neural-LAFC: A Neural Learning Adaptive Flight controller for Tailless Flapping-Wing Robots Under Uncertain Wind Disturbance Conditions

引用

IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Guo, Qingcheng Zhang, Yichen Mou, Jiawang Liu, Wu Wu, Xiaosheng Lu, Jun-Guo Shanghai Jiao Tong University Department of Automation China Key Laboratory of System Control and Information Processing Ministry of Education of China China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai200240 China Shanghai Jiao Tong University National Key Laboratory of Advanced Micro and Nano Manufacture Technology China Shanghai Jiao Tong University Department of Micro/Nano Electronics School of Electronic Information and Electrical Engineering Shanghai200240 China Designing Institute of Hubei Space Technology Academy Wuhan China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

Enabling bio-inspired flapping-wing robots (FWRs) to maintain stable flight in windy environments, similar to real flying creatures, is of significant importance. In this work, a neural learning-based adaptive flight controller (Neural-LAFC) is proposed for the attitude and position control of a tailless FWR under uncertain wind conditions. The key approach involves employing a deep neural network (DNN) that incorporates not only attitude information but also instantaneous flapping angles of the wings to learn the aerodynamic torques that cannot be accurately modeled. The training data are obtained from flight experiments conducted with the FWR in a wind tunnel environment. Subsequently, a composite adaptive law is presented to update a set of linear coefficients. These linear coefficients are utilized to blend the pre-trained basis functions to represent the aerodynamic torques. The tracking errors are shown to exponentially converge to a bounded region, as guaranteed by a Lyapunov function. Based on the learning-based attitude controller, we also develop an adaptive controller for position control. Notably, apart from the training phase, the FWR operates without prior knowledge of wind speed. Experimental results demonstrate that the Neural-LAFC successfully achieves the desired attitude stabilization, target point tracking, and path tracking of the FWR in windy conditions. The proposed control scheme also outperforms baseline controllers in wind disturbance suppression, reducing the root mean square position errors by more than 40% when the FWR is subjected to a horizontal wind within the speed of 180 {cm s{-1}}. © 1965-2011 IEEE.

关键词： Wind tunnels

来源：评论

学校读者我要写书评

暂无评论

Investigation on slug flow parameters based on PIV phase discrimination

Investigation on slug flow parameters based on PIV phase dis...

引用

Tianjin University-IET Electrical & information Engineering Doctoral Forum (TJU IET 2023)

作者： H. Wang T. Xue College of Electrical and Information Engineering Tianjin Key Laboratory of Process Measurement and Control Tianjin University Tianjin People's Republic of China

Investigation of synchronously acquiring multiple parameters holds valuable insights into flow characteristics. When employing particle image velocimetry in gas-liquid slug flow, the integration of phase discrimination assumes an unequivocal role. This not only facilitates the separation of gas and liquid phases to distinctly capture velocity field distributions but also enables the extraction of characteristic parameters beyond velocity from gas or liquid phase. In this study, in addition to velocity measurements employing particle image velocimetry, structural parameters measurement methodologies within slug flow, such as liquid film thickness and elongated bubble length, are introduced based on phase discrimination results. By leveraging the inherent relationships among flow rate parameters, the measurement parameters are cross-validated based on experimental findings to assess the feasibility of the method. Ultimately, an exploration and analysis of flow characteristics in slug flow under different flow conditions are undertaken.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on Optimization of Two-Stage Scheduling for Aluminum Extrusion Machine Manufacturing Line

Research on Optimization of Two-Stage Scheduling for Aluminu...

引用

Chinese Automation Congress (CAC)

作者： Aoran Zhou Lipeng Qiu Yali Wu Department of Information and Control Engineering Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co Ltd Xi'an China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In view of the problems of high energy consumption, long inventory time and low production efficiency in the production process of traditional aluminum extrusion machine, this paper establishes an efficient two-stage parallel scheduling optimization model based on the integration of flexible job shop scheduling and assembly sequence planning (IFJSS-ASP). On this basis, an evolutionary algorithm combining strong dominance relationship and simple grouping method (SDREA-SGM) is proposed. The algorithm utilizes a two-stage hybrid chromosome encoding and decoding method to establish a rational mapping from the decision space to the solution space. Furthermore, in order to prevent the model from easily falling into local optima, an adaptive intra-class and inter-class pairing selection strategy has been adopted by the algorithm. This enhances global search and improves local search flexibility. Finally, the feasibility and effectiveness of the algorithm are verified by solving problems of different scales.

关键词： Energy consumption Job shop scheduling Optimization models Aluminum Production Evolutionary computation Encoding Planning Decoding Optimization

来源：评论

学校读者我要写书评

暂无评论

Concurrent Learning-Based Adaptive control for the Wheeled Mobile Robot with Uncertainties and Disturbances

Concurrent Learning-Based Adaptive Control for the Wheeled M...

引用

第43届中国控制会议

作者： Bo Qin Huaicheng Yan Kai Rao Penghui Yang Key Laboratory of Smart Manufacturing in Energy Chemical Process of Ministry of Education East China University of Science and Technology Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper focuses on the tracking problem of a perturbed wheeled mobile robot(WMR). Taking both the kinematic model and dynamic model into account, a transformed model is proposed based on the heading position. By extracting deep-root information from the lumped disturbance, the influence of the lumped disturbance can be estimated and eliminated by a simple adaptive compensation term. concurrent learning(CL) is introduced to the adaptive law to relax the persistent excitation(PE)condition. A Lyapunov-based method is used to ensure globally uniformly ultimately bounded(GUUB) stable tracking. The proposed control strategy is proven effective by a numerical simulation.

关键词： wheeled mobile robot concurrent learning adaptive control disturbances

来源：评论

学校读者我要写书评

暂无评论

Multi-Objective Optimization of Integrated Energy system for Cchp Based on Improved Cuckoo Search Algorithm

SSRN

引用

SSRN 2024年

作者： Zheng, KaiYue Zhao, ChuanZhen School of Control Science and Engineering Key Laboratory of Intelligent Control of Electrical Equipment Tiangong University Tianjin300387 China School of Electronics & Information Engineering Tianjin Key Laboratory of Optoelectronic Detection Technology and System Tiangong University Tianjin300387 China

This paper discusses the optimization and scheduling of an integrated energy system for combined cooling, heating and power (CCHP). It seeks to provide better scheduling of device outputs in the system and to decrease the daily economic and environmental operating costs of the system. We build an integrated energy system with wind turbine, micro gas turbine, electric cooling unit and so on, and establish a multi-objective optimization model with the goal of minimizing economic and environmental costs. In addition, we propose a novel optimal scheduling method. It combines chaotic mapping and cuckoo search algorithm to address issues such as slow convergence speed and high iteration counts in traditional optimization algorithms. Finally, the improved cuckoo search algorithm is used to solve the system optimization problem. The optimization solution is implemented in the case of satisfying the constraints of equipment output and power balance. The simulation results show that the CCHP system can effectively improve the economic efficiency and reduce the pollutant emissions compared with the common micro-grid system. Furthermore, compared with other algorithms, the improved cuckoo algorithm shows much better performance in solving the model and can decrease the whole system's total cost. © 2024, The Authors. All rights reserved.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Quality Prediction of Injection Molding process Using CNN and Parallel-Cascade LSTMs 43

Quality Prediction of Injection Molding Process Using CNN an...

引用

43rd Chinese control Conference, CCC 2024

作者： Zhang, Yibo Li, Dewei Zhou, Yuanqiang Gao, Furong Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai201100 China Tongji University College of Electronic and Information Engineering Shanghai201804 China Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong The Guangzhou Hkust Fok Ying Tung Research Institute Department of Chemical and Biological Engineering Guangzhou511458 China

ISBN: (纸本)9789887581581

Quality prediction of plastic products has always been an important research topic in the injection molding production process. However, existing quality prediction methods struggle to handle both high-frequency data and statistical data generated during the injection molding production process. This paper introduces a novel quality prediction model for injection molding production, utilizing a combination of Convolutional Neural Networks (CNN) and Parallel-Cascade Long Short-Term Memory (PCLSTM) networks. The PCLSTM network is designed to handle the complexities of high-frequency data in injection molding, overcoming the limitations of traditional LSTM methods in processing long sequence data. By segmenting data into stages and utilizing a cascade mechanism, the PCLSTM architecture efficiently captures important temporal dynamics. Additionally, the CNN network is designed to extract statistical data features. The quality prediction results are obtained by fusing two types of data features and then passing them through a fully connected network. Experimental results on real production datasets show that the CNN-PCLSTM model outperforms existing models in prediction accuracy and training convergence speed. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Specificity-preserving RGB-D saliency detection

引用

Computational Visual Media 2023年第2期9卷 297-317页

作者： Tao Zhou Deng-Ping Fan Geng Chen Yi Zhou Huazhu Fu School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Key Laboratory of System Control and Information Processing Ministry of EducationShanghaiChina Computer Vision Lab ETH Z¨urichZ¨urichSwitzerland School of Computer Science and Engineering Northwestern Polytechnical UniversityXi’anChina School of Computer Science and Engineering Southeast UniversityNanjingChina Inception Institute of Artificial Intelligence Abu DhabiUnited Arab Emirates

Salient object detection(SOD)in RGB and depth images has attracted increasing research *** RGB-D SOD models usually adopt fusion strategies to learn a shared representation from RGB and depth modalities,while few methods explicitly consider how to preserve modality-specific *** this study,we propose a novel framework,the specificity-preserving network(SPNet),which improves SOD performance by exploring both the shared information and modality-specific ***,we use two modality-specific networks and a shared learning network to generate individual and shared saliency prediction *** effectively fuse cross-modal features in the shared learning network,we propose a cross-enhanced integration module(CIM)and propagate the fused feature to the next layer to integrate cross-level ***,to capture rich complementary multi-modal information to boost SOD performance,we use a multi-modal feature aggregation(MFA)module to integrate the modalityspecific features from each individual decoder into the shared *** using skip connections between encoder and decoder layers,hierarchical features can be fully *** experiments demonstrate that our SPNet outperforms cutting-edge approaches on six popular RGB-D SOD and three camouflaged object detection *** project is publicly available at https://***/taozh2017/SPNet.

关键词： salient object detection(SOD) RGB-D cross-enhanced integration module(CIM) multi-modal feature aggregation(MFA)

来源：评论

学校读者我要写书评

暂无评论

Distributionally Robust control Synthesis for Stochastic systems with Safety and Reach-Avoid Specifications

arXiv

引用

arXiv 2025年

作者： Chen, Yu Li, Yuda Li, Shaoyuan Yin, Xiang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

We investigate the problem of synthesizing distributionally robust control policies for stochastic systems under safety and reach-avoid specifications. Using a game-theoretical framework, we consider the setting where the probability distribution of the disturbance at each time step is selected from an ambiguity set defined by the Wasserstein distance. The goal is to synthesize a distributionally robust control policy that ensures the satisfaction probability exceeds a specified threshold under any distribution within the ambiguity set. First, for both safety and reach-avoid specifications, we establish the existence of optimal policies by leveraging the dynamic programming principles. Then we demonstrate how the associated optimization problem can be efficiently solved using the dual representation of Wasserstein distributionally robust optimization. Furthermore, for safety specifications in particular, we introduce a novel concept of distributionally robust control barrier certificates and show how these enable the efficient synthesis of controllers through sum-of-squares programming techniques. Finally, our experimental results reveal that incorporating distributional robustness during the synthesis phase significantly improves the satisfaction probability during online execution, even with limited statistical knowledge of the disturbance distribution. Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：