Pub Date : 2024-08-08DOI: 10.1177/00202940241259334
Yuqiang Wang
Considering the real scenario in China, in order to decrease passenger transfer, cross-line trains are scheduled extensively for the large number of cross-line passenger flow. Therefore, in this paper, we propose a more practical approach aiming to schedule more trains within a limit time horizon by both main-line train and cross-line train scheduling optimization (train timetable and stopping plan optimization). We find that the train scheduling and passenger assignment problems are multi-commodity flow problems. The trains (as the users) share the railway capacities (as the resource) in a high-speed railway network, and the passengers (as the users) share the train carrying capacities (as the resource). Thus, based on this, we formulate two space–time networks—train and passenger space–time networks—to present the train operation and the passenger flow, respectively. In addition, we regard train disturbances in different directions as different train headways at cross-line stations to optimize train scheduling practically. Sequentially, a mixed-integer linear programing model with headway and coupling constraints is formulated. To solve the model efficiently for a large-scale application, we decompose the problem into two space–time path-searching sub-problems based on the passenger and train space–time networks by the Lagrangian relaxation and alternating direction method of multipliers decomposition methods. Finally, we adopt the Taiyuan–Dezhou and Zhengzhou–Beijing high-speed railway networks in a practical experiment, and an experiment without cross-line operation is designed to test the effect of cross-line operation. The results show the proposed approach can obtain a no-conflict timetable and all the passenger demand can be satisfied, meanwhile, the capacity can improve 20.7% when the cross-line operation is not considered.
{"title":"Train timetable and stopping plan generation based on cross-line passenger flow in high-speed railway network","authors":"Yuqiang Wang","doi":"10.1177/00202940241259334","DOIUrl":"https://doi.org/10.1177/00202940241259334","url":null,"abstract":"Considering the real scenario in China, in order to decrease passenger transfer, cross-line trains are scheduled extensively for the large number of cross-line passenger flow. Therefore, in this paper, we propose a more practical approach aiming to schedule more trains within a limit time horizon by both main-line train and cross-line train scheduling optimization (train timetable and stopping plan optimization). We find that the train scheduling and passenger assignment problems are multi-commodity flow problems. The trains (as the users) share the railway capacities (as the resource) in a high-speed railway network, and the passengers (as the users) share the train carrying capacities (as the resource). Thus, based on this, we formulate two space–time networks—train and passenger space–time networks—to present the train operation and the passenger flow, respectively. In addition, we regard train disturbances in different directions as different train headways at cross-line stations to optimize train scheduling practically. Sequentially, a mixed-integer linear programing model with headway and coupling constraints is formulated. To solve the model efficiently for a large-scale application, we decompose the problem into two space–time path-searching sub-problems based on the passenger and train space–time networks by the Lagrangian relaxation and alternating direction method of multipliers decomposition methods. Finally, we adopt the Taiyuan–Dezhou and Zhengzhou–Beijing high-speed railway networks in a practical experiment, and an experiment without cross-line operation is designed to test the effect of cross-line operation. The results show the proposed approach can obtain a no-conflict timetable and all the passenger demand can be satisfied, meanwhile, the capacity can improve 20.7% when the cross-line operation is not considered.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"43 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141929663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1177/00202940241256802
Thanh Q Nguyen, Vu Ba Tu, Duong N Nguyen
The manuscript introduces a novel approach to design and construct a pore water pressure sensor utilizing strain gage technology integrated with deep learning principles. This sensor type is specifically tailored for measuring pressure at the vertex of pile bases in structures with substantial load-bearing capacity. While existing pressure sensors employing strain gage technology are available, this research addresses a unique measurement model suited for deep-water environments characterized by high corrosiveness and heavy loads. Consequently, the manuscript proposes design innovations aimed at optimizing the sensor’s form and dimensions to accommodate these demanding conditions. Computational simulations are conducted to perform relevant calculations, with results validated through rigorous analysis and experimentation against real-world datasets. Moreover, the study incorporates a pioneering deep learning-based data acquisition model to enhance output values, a feature currently underutilized in sensor technology. The findings demonstrate the viability of the proposed water pressure sensor model in various challenging working environments. This research underscores the potential for proactive manufacturing of sensors in diverse configurations, emphasizing adaptability and efficiency.
{"title":"Enhancing water pressure sensing in challenging environments: A strain gage technology integrated with deep learning approach","authors":"Thanh Q Nguyen, Vu Ba Tu, Duong N Nguyen","doi":"10.1177/00202940241256802","DOIUrl":"https://doi.org/10.1177/00202940241256802","url":null,"abstract":"The manuscript introduces a novel approach to design and construct a pore water pressure sensor utilizing strain gage technology integrated with deep learning principles. This sensor type is specifically tailored for measuring pressure at the vertex of pile bases in structures with substantial load-bearing capacity. While existing pressure sensors employing strain gage technology are available, this research addresses a unique measurement model suited for deep-water environments characterized by high corrosiveness and heavy loads. Consequently, the manuscript proposes design innovations aimed at optimizing the sensor’s form and dimensions to accommodate these demanding conditions. Computational simulations are conducted to perform relevant calculations, with results validated through rigorous analysis and experimentation against real-world datasets. Moreover, the study incorporates a pioneering deep learning-based data acquisition model to enhance output values, a feature currently underutilized in sensor technology. The findings demonstrate the viability of the proposed water pressure sensor model in various challenging working environments. This research underscores the potential for proactive manufacturing of sensors in diverse configurations, emphasizing adaptability and efficiency.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"73 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141342353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-14DOI: 10.1177/00202940241258821
Leijia Liu
Given the importance of promoting a greener and more sustainable future, it is crucial to promptly tackle and improve the issues surrounding carbon emissions and inefficiency linked to traditional energy sources. This study presents a new optimization method for PV systems. It combines an IGWO Algorithm with PID-type SMC to enhance the effectiveness of MPPT. Using IGWO, the optimal MPP voltage is determined even in the face of changing environmental conditions. Afterwards, the PID-type SMC adjusts the actual output voltage of the Boost based on the expected voltage to generate the required duty cycle. The integrated approach considers the natural fluctuations in PV systems, where changes in the environment can greatly affect the maximum power point. An in-depth evaluation was conducted using simulation software based on MATLAB, and a practical testing platform was built accordingly. The simulation and experimental results in real-world scenarios show that the new MPPT strategy has excellent overall performance and can quickly determine and track the voltage value for MPP compared to established algorithms. This study lays the groundwork for applying IGWO and new SMC control theories in the field of renewable energy generation. It also contributes to the development of MPPT technology, considering the challenges posed by the controlled environment.
{"title":"Photovoltaic MPPT control and improvement strategies considering environmental factors: based on PID-type sliding mode control and improved grey wolf optimization","authors":"Leijia Liu","doi":"10.1177/00202940241258821","DOIUrl":"https://doi.org/10.1177/00202940241258821","url":null,"abstract":"Given the importance of promoting a greener and more sustainable future, it is crucial to promptly tackle and improve the issues surrounding carbon emissions and inefficiency linked to traditional energy sources. This study presents a new optimization method for PV systems. It combines an IGWO Algorithm with PID-type SMC to enhance the effectiveness of MPPT. Using IGWO, the optimal MPP voltage is determined even in the face of changing environmental conditions. Afterwards, the PID-type SMC adjusts the actual output voltage of the Boost based on the expected voltage to generate the required duty cycle. The integrated approach considers the natural fluctuations in PV systems, where changes in the environment can greatly affect the maximum power point. An in-depth evaluation was conducted using simulation software based on MATLAB, and a practical testing platform was built accordingly. The simulation and experimental results in real-world scenarios show that the new MPPT strategy has excellent overall performance and can quickly determine and track the voltage value for MPP compared to established algorithms. This study lays the groundwork for applying IGWO and new SMC control theories in the field of renewable energy generation. It also contributes to the development of MPPT technology, considering the challenges posed by the controlled environment.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"55 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141344518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-18DOI: 10.1177/00202940241252724
Zheng Sun, Min Xiao, Di Li, Jia Chu
Quadrotor unmanned aerial vehicles (UAVs) operating in agricultural fields for aerial photography are susceptible to external disturbances. The disturbances result in trajectory deviation and irregular image overlapping that considerably degrade image quality. Disturbance observers (DOs) are commonly researched for counteracting these effects but may have delays and limitations in handling diverse and high-frequency disturbances. To this end, this work proposes a continuous high-order sliding mode-assisted DO (HSMDO) with limited time convergence characteristics for the estimation of disturbances in systems. The observer consists of a classical nonlinear DO (NDO) and a sliding mode-assisted system (SMAS). The NDO is used to estimate disturbances preliminarily. The SMAS is utilised to assist the NDO in estimating the high-frequency component of disturbances and ensure that the entire DO is finite-time convergent. Finally, the tracking controller is designed on the basis of the HSMDO, which enables UAVs to track the prescribed trajectories under disturbances stably. Simulation results show that the proposed HSMDO can accurately estimate various types of disturbances. Moreover, the tracking controller based on the HSMDO can improve the antidisturbance performance of systems and ensure the trajectory tracking accuracy of UAVs.
{"title":"Tracking controller design for quadrotor UAVs under external disturbances using a high-order sliding mode-assisted disturbance observer","authors":"Zheng Sun, Min Xiao, Di Li, Jia Chu","doi":"10.1177/00202940241252724","DOIUrl":"https://doi.org/10.1177/00202940241252724","url":null,"abstract":"Quadrotor unmanned aerial vehicles (UAVs) operating in agricultural fields for aerial photography are susceptible to external disturbances. The disturbances result in trajectory deviation and irregular image overlapping that considerably degrade image quality. Disturbance observers (DOs) are commonly researched for counteracting these effects but may have delays and limitations in handling diverse and high-frequency disturbances. To this end, this work proposes a continuous high-order sliding mode-assisted DO (HSMDO) with limited time convergence characteristics for the estimation of disturbances in systems. The observer consists of a classical nonlinear DO (NDO) and a sliding mode-assisted system (SMAS). The NDO is used to estimate disturbances preliminarily. The SMAS is utilised to assist the NDO in estimating the high-frequency component of disturbances and ensure that the entire DO is finite-time convergent. Finally, the tracking controller is designed on the basis of the HSMDO, which enables UAVs to track the prescribed trajectories under disturbances stably. Simulation results show that the proposed HSMDO can accurately estimate various types of disturbances. Moreover, the tracking controller based on the HSMDO can improve the antidisturbance performance of systems and ensure the trajectory tracking accuracy of UAVs.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"123 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141125483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.1177/00202940231212949
Mingming Liu, Longlong Chen, Yanxi Ren
In the areas of aerospace and military industry, wheeled vehicles are expected to have the ability of passing various ground surfaces, including lunar soil, sand, marsh, mud flat, etc. This makes vehicle trafficability on soft ground become a very hot research topic. There are very a few difficulties in the present research of vehicle trafficability on soft ground, such as obtaining wheel-ground interaction information, inaccurate identification of soil mechanical characteristics parameters, and single evaluation index. In this paper, a novel approach of evaluating the vehicle trafficability on soft ground using wheel force information is proposed. As parts of the proposed approach, the methods of obtaining wheel force information, identification of soil mechanical characteristics parameters and integated method of trafficability evaluation, are discussed in detail. The proposed approach was validated through a practical test.
{"title":"Evaluating vehicle trafficability on soft ground using wheel force information","authors":"Mingming Liu, Longlong Chen, Yanxi Ren","doi":"10.1177/00202940231212949","DOIUrl":"https://doi.org/10.1177/00202940231212949","url":null,"abstract":"In the areas of aerospace and military industry, wheeled vehicles are expected to have the ability of passing various ground surfaces, including lunar soil, sand, marsh, mud flat, etc. This makes vehicle trafficability on soft ground become a very hot research topic. There are very a few difficulties in the present research of vehicle trafficability on soft ground, such as obtaining wheel-ground interaction information, inaccurate identification of soil mechanical characteristics parameters, and single evaluation index. In this paper, a novel approach of evaluating the vehicle trafficability on soft ground using wheel force information is proposed. As parts of the proposed approach, the methods of obtaining wheel force information, identification of soil mechanical characteristics parameters and integated method of trafficability evaluation, are discussed in detail. The proposed approach was validated through a practical test.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"8 45","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140964188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.1177/00202940221092037
Yongqiang Han, Ruirui Liang
Aiming at the obvious trend of the contours on the high-altitude geomagnetic map, this paper presents a method of high-altitude geomagnetic matching area selection combining geomagnetic information entropy and geomagnetic direction entropy based on the study of geomagnetic information entropy and geomagnetic direction entropy. The method first uses geomagnetic information entropy to select the region with rich geomagnetic information, and then determines the direction of the flight trajectory according to geomagnetic direction entropy to obtain the optimal matching trajectory. Finally, the method compares and analyzes the matching localization results of three flight trajectories in different directions on the geomagnetic map at an altitude of 30,000 m by using semi-physical simulation. The experimental results show that the flight navigation error along the trajectory with small information entropy is small, and its positioning error is 12.7% of the trajectory positioning error along the maximum information entropy direction. Selecting the flight trajectory according to the value of the geomagnetic direction entropy can greatly improve the precision and reliability of the geomagnetic matching localization. The method in this paper can provide a basis for path planning of the geomagnetic matching navigation.
{"title":"A high-altitude geomagnetic matching area selection approach based on geomagnetic information entropy and geomagnetic direction entropy","authors":"Yongqiang Han, Ruirui Liang","doi":"10.1177/00202940221092037","DOIUrl":"https://doi.org/10.1177/00202940221092037","url":null,"abstract":"Aiming at the obvious trend of the contours on the high-altitude geomagnetic map, this paper presents a method of high-altitude geomagnetic matching area selection combining geomagnetic information entropy and geomagnetic direction entropy based on the study of geomagnetic information entropy and geomagnetic direction entropy. The method first uses geomagnetic information entropy to select the region with rich geomagnetic information, and then determines the direction of the flight trajectory according to geomagnetic direction entropy to obtain the optimal matching trajectory. Finally, the method compares and analyzes the matching localization results of three flight trajectories in different directions on the geomagnetic map at an altitude of 30,000 m by using semi-physical simulation. The experimental results show that the flight navigation error along the trajectory with small information entropy is small, and its positioning error is 12.7% of the trajectory positioning error along the maximum information entropy direction. Selecting the flight trajectory according to the value of the geomagnetic direction entropy can greatly improve the precision and reliability of the geomagnetic matching localization. The method in this paper can provide a basis for path planning of the geomagnetic matching navigation.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"45 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140966045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.1177/00202940241248252
Qunpo Liu, Zhuoran Zhang, Jiakun Li, Xuhui Bu, Naohiko Hanajima
Research on initial errors and constraint restrictions is one of the main research directions in the field of control of uncertain robotic systems. An adaptive iterative learning control (AILC) method based on radial basis function (RBF) neural network is proposed to address the trajectory tracking problem of the long-stroke hybrid robot system with random initial errors and full state constraints. The RBF neural network is used to approximate the unknown nonlinear terms, and the network weights are updated using an iterative learning law that incorporates a projection mechanism. Additionally, a robust learning strategy is used to compensate for both the approximation error of the neural network and the external disturbances that vary with each iteration. To relax the requirement of traditional iterative learning control (ILC) for identical initial condition, an equivalent error function is constructed based on the time-varying boundary layer. The tangent-type barrier Lyapunov function (BLF) is designed to ensure that the joint position and speed of the robot system are bounded within a predetermined range. Through stability analysis based on barrier composite energy function (BCEF), it can be proved that the boundedness of all signals in the closed-loop system and the tracking error of the robot system will converge to an adjustable residual set asymptotically. Finally, through simulation experiments conducted on the MATLAB platform, the results demonstrate that the method overcomes the random initial errors of the system effectively, ensures that the system satisfies the full-state constraints, and realizes high-precision trajectory tracking.
{"title":"Adaptive neural network iterative learning control of long-stroke hybrid robots with initial errors and full state constraints","authors":"Qunpo Liu, Zhuoran Zhang, Jiakun Li, Xuhui Bu, Naohiko Hanajima","doi":"10.1177/00202940241248252","DOIUrl":"https://doi.org/10.1177/00202940241248252","url":null,"abstract":"Research on initial errors and constraint restrictions is one of the main research directions in the field of control of uncertain robotic systems. An adaptive iterative learning control (AILC) method based on radial basis function (RBF) neural network is proposed to address the trajectory tracking problem of the long-stroke hybrid robot system with random initial errors and full state constraints. The RBF neural network is used to approximate the unknown nonlinear terms, and the network weights are updated using an iterative learning law that incorporates a projection mechanism. Additionally, a robust learning strategy is used to compensate for both the approximation error of the neural network and the external disturbances that vary with each iteration. To relax the requirement of traditional iterative learning control (ILC) for identical initial condition, an equivalent error function is constructed based on the time-varying boundary layer. The tangent-type barrier Lyapunov function (BLF) is designed to ensure that the joint position and speed of the robot system are bounded within a predetermined range. Through stability analysis based on barrier composite energy function (BCEF), it can be proved that the boundedness of all signals in the closed-loop system and the tracking error of the robot system will converge to an adjustable residual set asymptotically. Finally, through simulation experiments conducted on the MATLAB platform, the results demonstrate that the method overcomes the random initial errors of the system effectively, ensures that the system satisfies the full-state constraints, and realizes high-precision trajectory tracking.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"46 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140965886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-10DOI: 10.1177/00202940241236649
Hui Ali, Yu Jie, Weiqiang Lu
Aiming at the problem of mode aliasing in the adaptive decomposition of nonlinear and non-stationary current signals generated by three-phase asynchronous motor faults, and the fault features contained in signals collected by a single sensor can not be accurately and comprehensively extracted and characterized when early rotor bar breakage and air gap eccentricity faults occur, A fault diagnosis method for three-phase asynchronous motor based on noise assisted multivariate empirical mode decomposition (NA-MEMD) and mutual information is proposed. Firstly, the NA-MEMD algorithm is used to decompose the three-phase stator current signal of the asynchronous motor to obtain multi-scale intrinsic mode functions (IMFs). Then, the correlation algorithm is used to screen the IMFs containing useful information. Then, the filtered IMF components are reconstructed into new signals and their features are extracted, Finally, support vector machines (SVM) are used to identify the rotor broken bars and air gap eccentric faults of the three-phase asynchronous motor. The experimental results show that the NA-MEMD method has a higher recognition rate than the traditional empirical mode decomposition (EMD) and the ensemble empirical mode decomposition (EEMD) methods.
{"title":"Research on rotor fault diagnosis technology of three-phase asynchronous motor based on NA-MEMD mutual information and SVM","authors":"Hui Ali, Yu Jie, Weiqiang Lu","doi":"10.1177/00202940241236649","DOIUrl":"https://doi.org/10.1177/00202940241236649","url":null,"abstract":"Aiming at the problem of mode aliasing in the adaptive decomposition of nonlinear and non-stationary current signals generated by three-phase asynchronous motor faults, and the fault features contained in signals collected by a single sensor can not be accurately and comprehensively extracted and characterized when early rotor bar breakage and air gap eccentricity faults occur, A fault diagnosis method for three-phase asynchronous motor based on noise assisted multivariate empirical mode decomposition (NA-MEMD) and mutual information is proposed. Firstly, the NA-MEMD algorithm is used to decompose the three-phase stator current signal of the asynchronous motor to obtain multi-scale intrinsic mode functions (IMFs). Then, the correlation algorithm is used to screen the IMFs containing useful information. Then, the filtered IMF components are reconstructed into new signals and their features are extracted, Finally, support vector machines (SVM) are used to identify the rotor broken bars and air gap eccentric faults of the three-phase asynchronous motor. The experimental results show that the NA-MEMD method has a higher recognition rate than the traditional empirical mode decomposition (EMD) and the ensemble empirical mode decomposition (EEMD) methods.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":" 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140993452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-08DOI: 10.1177/00202940241241931
Ya Deng, Wei Zhu, Huannan Zheng
Compared with bounded delays, distributed infinite delays are more general in practical systems. Event-triggered control can effectively reduce energy consumption and communication costs. This paper addresses time-varying formation control of general linear multi-agent systems with distributed infinite delays in both of their inputs and outputs. An observer-based event-triggered formation control protocol considering distributed infinite delays is proposed, which is related to the combined observed information and some formation compensation signals at triggering time instants. By utilizing inequality techniques, the desired time-varying formation can be implemented while Zeno-behavior is excluded. Some numerical simulations are carried out for demonstrating the validity of theoretical results.
{"title":"Observer-based event-triggered time-varying formation control of linear multi-agent systems with distributed infinite delays","authors":"Ya Deng, Wei Zhu, Huannan Zheng","doi":"10.1177/00202940241241931","DOIUrl":"https://doi.org/10.1177/00202940241241931","url":null,"abstract":"Compared with bounded delays, distributed infinite delays are more general in practical systems. Event-triggered control can effectively reduce energy consumption and communication costs. This paper addresses time-varying formation control of general linear multi-agent systems with distributed infinite delays in both of their inputs and outputs. An observer-based event-triggered formation control protocol considering distributed infinite delays is proposed, which is related to the combined observed information and some formation compensation signals at triggering time instants. By utilizing inequality techniques, the desired time-varying formation can be implemented while Zeno-behavior is excluded. Some numerical simulations are carried out for demonstrating the validity of theoretical results.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":" 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140997654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-05DOI: 10.1177/00202940241245241
Yu Zheng, Ningtao Peng, Hao Qi, Guiliang Gong, Dan Huang, Kaikai Zhu, Jingsheng Liu, Gonggang Liu
The classical distributed hybrid flow shop scheduling problem (DHFSP) only considers static production settings while ignores operation inspection and reprocessing. However, in the actual production, the manufacturing environment is usually dynamic; and the operation inspection and reprocessing are very necessary to avoid unqualified jobs from being transported to other production units and to make reasonable arrangements for unqualified and unprocessed jobs. In this paper, we propose a DHFSP with operation inspection and reprocessing (DHFSPR) for the first time, in which the operation inspection and reprocessing as well as the processing time and energy consumption are considered simultaneously. An improved memetic algorithm (IMA) is then designed to solve the DHFSPR, where some effective crossover and mutation operators, a new dynamic rescheduling method (DRM) and local search operator (LSO) are integrated. A total 60 DHFSPR benchmark instances are constructed to verify the performance of our IMA. Extensive experiments carried out demonstrate that the DRM and LSO can effectively improve the performance of IMA, and the IMA has obvious superiority to solve the DHFSPR problem compared with other three well-known algorithms. Our proposed model and algorithm here will be beneficial for the production managers who work with distributed hybrid shop systems in scheduling their production activities by considering operation inspection and reprocessing.
经典的分布式混合流程车间调度问题（DHFSP）只考虑了静态的生产环境，而忽略了作业检查和再处理。然而，在实际生产中，生产环境通常是动态的，为了避免不合格的作业被传送到其他生产单元，合理安排不合格和未处理的作业，作业检查和再处理是非常必要的。本文首次提出了一种带操作检查和再处理的 DHFSP（DHFSPR），它同时考虑了操作检查和再处理以及处理时间和能耗。然后设计了一种改进的记忆算法（IMA）来求解 DHFSPR，其中集成了一些有效的交叉和变异算子、一种新的动态重调度方法（DRM）和局部搜索算子（LSO）。为了验证 IMA 的性能，我们构建了 60 个 DHFSPR 基准实例。广泛的实验证明，DRM 和 LSO 能有效提高 IMA 的性能，与其他三种著名算法相比，IMA 在解决 DHFSPR 问题上具有明显的优势。我们在此提出的模型和算法将有益于使用分布式混合车间系统的生产管理人员通过考虑操作检查和再加工来安排生产活动。
{"title":"An improved memetic algorithm for distributed hybrid flow shop scheduling problem with operation inspection and reprocessing","authors":"Yu Zheng, Ningtao Peng, Hao Qi, Guiliang Gong, Dan Huang, Kaikai Zhu, Jingsheng Liu, Gonggang Liu","doi":"10.1177/00202940241245241","DOIUrl":"https://doi.org/10.1177/00202940241245241","url":null,"abstract":"The classical distributed hybrid flow shop scheduling problem (DHFSP) only considers static production settings while ignores operation inspection and reprocessing. However, in the actual production, the manufacturing environment is usually dynamic; and the operation inspection and reprocessing are very necessary to avoid unqualified jobs from being transported to other production units and to make reasonable arrangements for unqualified and unprocessed jobs. In this paper, we propose a DHFSP with operation inspection and reprocessing (DHFSPR) for the first time, in which the operation inspection and reprocessing as well as the processing time and energy consumption are considered simultaneously. An improved memetic algorithm (IMA) is then designed to solve the DHFSPR, where some effective crossover and mutation operators, a new dynamic rescheduling method (DRM) and local search operator (LSO) are integrated. A total 60 DHFSPR benchmark instances are constructed to verify the performance of our IMA. Extensive experiments carried out demonstrate that the DRM and LSO can effectively improve the performance of IMA, and the IMA has obvious superiority to solve the DHFSPR problem compared with other three well-known algorithms. Our proposed model and algorithm here will be beneficial for the production managers who work with distributed hybrid shop systems in scheduling their production activities by considering operation inspection and reprocessing.","PeriodicalId":18375,"journal":{"name":"Measurement and Control","volume":"300 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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