Pub Date : 2025-02-26DOI: 10.1016/j.conengprac.2025.106289
Mladen Čičić , Carlos Vivas , Carlos Canudas-de-Wit , Francisco R. Rubio
We propose an integrated power and transportation system control framework, combining the power grid model with a macroscopic electromobility model including charging stations under V2G operation. In this framework, the electrical vehicles (EVs) act as energy storage, but also as additional virtual power grid links, transporting energy from one point to another. This new holistic approach is used as a basis for optimal control design seeking to provide Active Network Management, in order to minimize curtailment of renewable energy sources and loads at various ports of the network, while accounting for the structural limitation of the grid and other constraints necessary for the optimal operation of the EVs. The proposed control scheme is shown to be able to outperform uncoordinated EV charging in terms of total curtailment in various studied scenarios. Additionally, we study the case when public charging stations are able to incentivize or disincentivise EVs to use them, by dynamically varying their charging price throughout the day, and show that this additional control input can further reduce curtailment in certain scenarios.
{"title":"Active Network Management via grid-friendly electromobility control for curtailment minimization","authors":"Mladen Čičić , Carlos Vivas , Carlos Canudas-de-Wit , Francisco R. Rubio","doi":"10.1016/j.conengprac.2025.106289","DOIUrl":"10.1016/j.conengprac.2025.106289","url":null,"abstract":"<div><div>We propose an integrated power and transportation system control framework, combining the power grid model with a macroscopic electromobility model including charging stations under V2G operation. In this framework, the electrical vehicles (EVs) act as energy storage, but also as additional virtual power grid links, transporting energy from one point to another. This new holistic approach is used as a basis for optimal control design seeking to provide Active Network Management, in order to minimize curtailment of renewable energy sources and loads at various ports of the network, while accounting for the structural limitation of the grid and other constraints necessary for the optimal operation of the EVs. The proposed control scheme is shown to be able to outperform uncoordinated EV charging in terms of total curtailment in various studied scenarios. Additionally, we study the case when public charging stations are able to incentivize or disincentivise EVs to use them, by dynamically varying their charging price throughout the day, and show that this additional control input can further reduce curtailment in certain scenarios.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106289"},"PeriodicalIF":5.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-24DOI: 10.1016/j.conengprac.2025.106297
Xi Zhang , Yaomin Lu , Zhiyang Ju , Jiarui Song , Zheng Zang , Jianyong Qi , Jianwei Gong
Efficiently generating safe and smooth trajectories for autonomous ground vehicles (AGVs) is a crucial and challenging task, particularly in dynamic environments with moving obstacles. This paper proposes an integrated motion planning and trajectory optimization (MPTO) framework that employs an optimization-based spatio-temporal safety corridors (STSC) to ensure trajectory smoothness and safety from a three-dimensional spatio-temporal perspective. The proposed MPTO framework comprises two layers. In the first layer, a multi-objective quadratic programming (MOQP) method was developed with the objective of rapidly generating smoothly varying STSC. The multi-objective cost function provides a comprehensive evaluation of the corridors in terms of their size, direction, and smoothness. Additionally, a convex polygonal feasible area (CPFA) was proposed to provide a linear obstacle-avoidance constraint for the MOQP. The smooth STSC provides within-corridor constraints for trajectory optimization, thereby ensuring collision avoidance of obstacles and reducing the dependence of trajectory optimization on the reference trajectory. In the second layer, an optimal trajectory generation method using polynomials is proposed to generate smooth and efficient trajectories. With smooth STSC constraints, the trajectory optimization model primarily focuses on smoothness, ensuring that the trajectory remains safe and smooth even with sudden changes in the feasible area. Finally, the proposed MPTO framework is validated through simulations and real vehicle experiments.
{"title":"An integrated framework for motion planning and trajectory optimization of AGVs using spatio-temporal safety corridors","authors":"Xi Zhang , Yaomin Lu , Zhiyang Ju , Jiarui Song , Zheng Zang , Jianyong Qi , Jianwei Gong","doi":"10.1016/j.conengprac.2025.106297","DOIUrl":"10.1016/j.conengprac.2025.106297","url":null,"abstract":"<div><div>Efficiently generating safe and smooth trajectories for autonomous ground vehicles (AGVs) is a crucial and challenging task, particularly in dynamic environments with moving obstacles. This paper proposes an integrated motion planning and trajectory optimization (MPTO) framework that employs an optimization-based spatio-temporal safety corridors (STSC) to ensure trajectory smoothness and safety from a three-dimensional spatio-temporal perspective. The proposed MPTO framework comprises two layers. In the first layer, a multi-objective quadratic programming (MOQP) method was developed with the objective of rapidly generating smoothly varying STSC. The multi-objective cost function provides a comprehensive evaluation of the corridors in terms of their size, direction, and smoothness. Additionally, a convex polygonal feasible area (CPFA) was proposed to provide a linear obstacle-avoidance constraint for the MOQP. The smooth STSC provides within-corridor constraints for trajectory optimization, thereby ensuring collision avoidance of obstacles and reducing the dependence of trajectory optimization on the reference trajectory. In the second layer, an optimal trajectory generation method using polynomials is proposed to generate smooth and efficient trajectories. With smooth STSC constraints, the trajectory optimization model primarily focuses on smoothness, ensuring that the trajectory remains safe and smooth even with sudden changes in the feasible area. Finally, the proposed MPTO framework is validated through simulations and real vehicle experiments.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106297"},"PeriodicalIF":5.4,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-24DOI: 10.1016/j.conengprac.2025.106284
Runze Li , Bin Jiang , Yan Zong , Ningyun Lu , Li Guo
Heterogeneous unmanned systems (HUS) consist of multiple types of unmanned sub-systems, and when one or more sub-systems experience failures, it can severely impact the overall system’s operation. Therefore, establishing effective fault diagnosis(FD) methods is crucial for ensuring the safety and reliability of heterogeneous unmanned systems. This paper proposes a federated fault diagnosis method based on data fusion, which combines visual images and multi-sensor information to enhance the fault identification capability of heterogeneous unmanned systems in complex environments. By using an offline broad reinforcement learning strategy, we propose a Federated Broad Reinforcement Learning fault diagnosis method. It achieves high-precision fault diagnosis under various fault conditions by iteratively reconstructing fused data and knowledge. Finally, the proposed method is validated on a hardware-in-the-loop (HIL) simulator in large-scale heterogeneous unmanned systems. Experimental results show that the proposed method improves fault diagnosis accuracy and enhances the safety and reliability of the system.
{"title":"Federated fault diagnosis using data fusion in large-scale heterogeneous unmanned systems","authors":"Runze Li , Bin Jiang , Yan Zong , Ningyun Lu , Li Guo","doi":"10.1016/j.conengprac.2025.106284","DOIUrl":"10.1016/j.conengprac.2025.106284","url":null,"abstract":"<div><div>Heterogeneous unmanned systems (HUS) consist of multiple types of unmanned sub-systems, and when one or more sub-systems experience failures, it can severely impact the overall system’s operation. Therefore, establishing effective fault diagnosis(FD) methods is crucial for ensuring the safety and reliability of heterogeneous unmanned systems. This paper proposes a federated fault diagnosis method based on data fusion, which combines visual images and multi-sensor information to enhance the fault identification capability of heterogeneous unmanned systems in complex environments. By using an offline broad reinforcement learning strategy, we propose a Federated Broad Reinforcement Learning fault diagnosis method. It achieves high-precision fault diagnosis under various fault conditions by iteratively reconstructing fused data and knowledge. Finally, the proposed method is validated on a hardware-in-the-loop (HIL) simulator in large-scale heterogeneous unmanned systems. Experimental results show that the proposed method improves fault diagnosis accuracy and enhances the safety and reliability of the system.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"159 ","pages":"Article 106284"},"PeriodicalIF":5.4,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-22DOI: 10.1016/j.conengprac.2025.106269
Maria Khodaverdian , Yeva Gabrielyan , Aleksandr Hakobyan , Salaman Ijaz , Paolo Castaldi
This work introduces a novel predictor-based integral sliding mode control scheme, designed for spacecraft attitude control. By leveraging Taylor series expansion, we develop predictor dynamics for the sliding surface and its integral, along with the corresponding reaching laws. Subsequently, we formulate a constrained quadratic optimization problem to derive the optimal control input. A notable aspect of the proposed method is the integration of the sliding surface’s integral into the control design, which significantly enhances robustness. Additionally, the proposed approach ensures optimality, fault tolerance capability, fixed-time convergence, computational efficiency, and effective constraint management. In this work, we perform a closed-loop stability analysis to confirm system stability in the presence of external perturbations, and constraints. Comparison results with existing method demonstrate that the proposed approach enhances performance while maintaining satisfactory precision. To validate the practical applicability of our algorithm, we conduct hardware-in-the-loop simulations, demonstrating the proposed method’s seamless integration with real-world hardware.
{"title":"A novel predictor based optimal integral sliding-mode-based attitude tracking control of spacecraft under actuator’s uncertainties and constraints","authors":"Maria Khodaverdian , Yeva Gabrielyan , Aleksandr Hakobyan , Salaman Ijaz , Paolo Castaldi","doi":"10.1016/j.conengprac.2025.106269","DOIUrl":"10.1016/j.conengprac.2025.106269","url":null,"abstract":"<div><div>This work introduces a novel predictor-based integral sliding mode control scheme, designed for spacecraft attitude control. By leveraging Taylor series expansion, we develop predictor dynamics for the sliding surface and its integral, along with the corresponding reaching laws. Subsequently, we formulate a constrained quadratic optimization problem to derive the optimal control input. A notable aspect of the proposed method is the integration of the sliding surface’s integral into the control design, which significantly enhances robustness. Additionally, the proposed approach ensures optimality, fault tolerance capability, fixed-time convergence, computational efficiency, and effective constraint management. In this work, we perform a closed-loop stability analysis to confirm system stability in the presence of external perturbations, and constraints. Comparison results with existing method demonstrate that the proposed approach enhances performance while maintaining satisfactory precision. To validate the practical applicability of our algorithm, we conduct hardware-in-the-loop simulations, demonstrating the proposed method’s seamless integration with real-world hardware.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106269"},"PeriodicalIF":5.4,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-21DOI: 10.1016/j.conengprac.2025.106287
Liang Gao, Bobo Jia, Daiwei Li, Yi Yang, Shanshan Xie
Trajectory planning for tractor–trailer vehicles (TTVs) in a cluttered environment is a highly challenging task owing to complicated kinematic and large-scale collision-avoidance constraints. It has stringent requirements for trajectory feasibility and computational efficiency. Moreover, the varying configurations of TTVs pose challenges to the scalability of the planning method. This article proposes a novel safety-critical trajectory planning method with a general model to address these challenges. Firstly, an algebraic general model is first presented to represent these N-Trailer systems with different hitching types and trailer types uniformly. Secondly, the planning problem is formulated as a nonlinear model predictive control scheme with two key efforts to accelerate calculation speed. One operation is that a novel search-guided optimization-based collision avoidance (SG-OBCA) method is developed to provide a high-quality initial guess. The other operation is that intractable non-convex collision-avoidance constraints are translated into a dual form based on exponential discrete-time control barrier function (DCBF). Finally, both comparative simulations and real-world experiments are conducted to demonstrate the efficiency and applicability of the proposed method in different complicated scenarios and configurations of TTVs.
{"title":"Efficient safety-critical trajectory planning for any N-trailer system with a general model","authors":"Liang Gao, Bobo Jia, Daiwei Li, Yi Yang, Shanshan Xie","doi":"10.1016/j.conengprac.2025.106287","DOIUrl":"10.1016/j.conengprac.2025.106287","url":null,"abstract":"<div><div>Trajectory planning for tractor–trailer vehicles (TTVs) in a cluttered environment is a highly challenging task owing to complicated kinematic and large-scale collision-avoidance constraints. It has stringent requirements for trajectory feasibility and computational efficiency. Moreover, the varying configurations of TTVs pose challenges to the scalability of the planning method. This article proposes a novel safety-critical trajectory planning method with a general model to address these challenges. Firstly, an algebraic general model is first presented to represent these N-Trailer systems with different hitching types and trailer types uniformly. Secondly, the planning problem is formulated as a nonlinear model predictive control scheme with two key efforts to accelerate calculation speed. One operation is that a novel search-guided optimization-based collision avoidance (SG-OBCA) method is developed to provide a high-quality initial guess. The other operation is that intractable non-convex collision-avoidance constraints are translated into a dual form based on exponential discrete-time control barrier function (DCBF). Finally, both comparative simulations and real-world experiments are conducted to demonstrate the efficiency and applicability of the proposed method in different complicated scenarios and configurations of TTVs.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106287"},"PeriodicalIF":5.4,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-21DOI: 10.1016/j.conengprac.2025.106281
Xu Deng , Dapeng Tian
Admittance control is a widely used approach for ensuring compliant robot behavior in physical human–robot interaction (pHRI) tasks. The selection of admittance parameters is crucial, as it directly affects interaction stability. However, this process becomes challenging when the robot’s interaction with objects involves not only the human hand but also the task environment. This is because the task environment is often unknown and hard to predict while the models of the human hand have been extensively studied in previous work. To address this issue, this paper proposes an admittance adaptive algorithm that ensures stability in human–robot-environment interaction tasks. This algorithm can adjust damping online without prior information about environments. Specifically, we consider the coupling between the robot, human hand, and task environment, treating them as a whole to analyze interaction stability and construct an energy function. Then, based on the energy function, a passive observer is designed to monitor unstable behaviors during the interaction process. Finally, the algorithm adjusts the damping online based on the observed values. The algorithm was experimentally validated using a custom admittance force feedback device. Experimental results indicate that the algorithm can ensure interaction stability without prior information about environments. In the experiment of writing letters, compared to a constant-parameter admittance controller, the algorithm reduces operator effort while maintaining stability.
{"title":"An admittance adaptive force feedback device and its interaction stability involving coupling with humans and uncertain environments","authors":"Xu Deng , Dapeng Tian","doi":"10.1016/j.conengprac.2025.106281","DOIUrl":"10.1016/j.conengprac.2025.106281","url":null,"abstract":"<div><div>Admittance control is a widely used approach for ensuring compliant robot behavior in physical human–robot interaction (pHRI) tasks. The selection of admittance parameters is crucial, as it directly affects interaction stability. However, this process becomes challenging when the robot’s interaction with objects involves not only the human hand but also the task environment. This is because the task environment is often unknown and hard to predict while the models of the human hand have been extensively studied in previous work. To address this issue, this paper proposes an admittance adaptive algorithm that ensures stability in human–robot-environment interaction tasks. This algorithm can adjust damping online without prior information about environments. Specifically, we consider the coupling between the robot, human hand, and task environment, treating them as a whole to analyze interaction stability and construct an energy function. Then, based on the energy function, a passive observer is designed to monitor unstable behaviors during the interaction process. Finally, the algorithm adjusts the damping online based on the observed values. The algorithm was experimentally validated using a custom admittance force feedback device. Experimental results indicate that the algorithm can ensure interaction stability without prior information about environments. In the experiment of writing letters, compared to a constant-parameter admittance controller, the algorithm reduces operator effort while maintaining stability.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106281"},"PeriodicalIF":5.4,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-20DOI: 10.1016/j.conengprac.2025.106285
Yong Ruan , Tao Tang
This paper addresses the control problem of a time-delay compensation method with multirate control in Youla–Kucera parametrization to reject disturbance. Such design methodologies not only enhance the disturbance rejection performance within the control bandwidth, but can also even break through the bandwidth to reject disturbance up to the Nyquist frequency. First, the time-delay function can be simplified to the real number at the disturbance characteristic frequency by tuning the additional time-delay factor for compensation, resulting in alleviating the detrimental effects of time delays. Next, a multirate control mode is proposed to implement the fractional compensation condition for solving the time-delay alignment problem. Moreover, this paper presents a parallel design approach for Q filters, significantly attenuating beam jitter resulting from complex multi-frequency disturbances. Finally, to assess the proposed method for beam jitter attenuation, experiments were conducted on a line-of-sight stabilization testbed. The results demonstrate that the proposed method can effectively enhance the disturbance rejection performance in time-delay control systems.
{"title":"An optimized Youla–Kucera parametrization with time-delay compensation in multirate parallel control for disturbance rejection up to Nyquist frequency","authors":"Yong Ruan , Tao Tang","doi":"10.1016/j.conengprac.2025.106285","DOIUrl":"10.1016/j.conengprac.2025.106285","url":null,"abstract":"<div><div>This paper addresses the control problem of a time-delay compensation method with multirate control in Youla–Kucera parametrization to reject disturbance. Such design methodologies not only enhance the disturbance rejection performance within the control bandwidth, but can also even break through the bandwidth to reject disturbance up to the Nyquist frequency. First, the time-delay function can be simplified to the real number <span><math><mrow><mo>±</mo><mn>1</mn></mrow></math></span> at the disturbance characteristic frequency by tuning the additional time-delay factor for compensation, resulting in alleviating the detrimental effects of time delays. Next, a multirate control mode is proposed to implement the fractional compensation condition for solving the time-delay alignment problem. Moreover, this paper presents a parallel design approach for Q filters, significantly attenuating beam jitter resulting from complex multi-frequency disturbances. Finally, to assess the proposed method for beam jitter attenuation, experiments were conducted on a line-of-sight stabilization testbed. The results demonstrate that the proposed method can effectively enhance the disturbance rejection performance in time-delay control systems.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106285"},"PeriodicalIF":5.4,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-19DOI: 10.1016/j.conengprac.2025.106286
Lin Qi, Jin Zhang, Xiaohong Jiao
This paper investigates the connected cruise control issue for the connected autonomous vehicle (CAV) in a mixed platoon consisting of a CAV, consecutive human-driven vehicles (HDVs), and a connected HDV considering mixed traffic of human-autonomous vehicles from the low penetration of autonomous vehicles. To deal with the uncertainty of traffic flow and vehicle platooning when the uncertain number of HDVs enter or leave the mixed platoon, a CAV predictive cruise control strategy based on the prediction of the preceding vehicle’s speed is designed for the CAV with the help of the information of connected vehicles ahead and Signal Phase and Timing (SPaT) information through vehicle-to-everything (V2X) communication. A stochastic speed prediction method combining a conditional linear Gaussian speed prediction model and a backpropagation neural network is proposed, which improves the prediction accuracy of the future speed of the predecessor vehicle. The CAV’s target speed is planned based on the network information so that the CAV can pass the intersection without stopping. The fuel efficiency driving problem is transformed into the target speed tracking problem, and the optimal solution is carried out in the model predictive control (MPC) framework, which improves fuel economy while ensuring safety. Compared with existing other schemes verify the effectiveness and advantage of the designed strategy.
{"title":"Predecessor speed prediction-based predictive cruise control of connected autonomous vehicle in platoon with multiple-human-driven-vehicles","authors":"Lin Qi, Jin Zhang, Xiaohong Jiao","doi":"10.1016/j.conengprac.2025.106286","DOIUrl":"10.1016/j.conengprac.2025.106286","url":null,"abstract":"<div><div>This paper investigates the connected cruise control issue for the connected autonomous vehicle (CAV) in a mixed platoon consisting of a CAV, consecutive human-driven vehicles (HDVs), and a connected HDV considering mixed traffic of human-autonomous vehicles from the low penetration of autonomous vehicles. To deal with the uncertainty of traffic flow and vehicle platooning when the uncertain number of HDVs enter or leave the mixed platoon, a CAV predictive cruise control strategy based on the prediction of the preceding vehicle’s speed is designed for the CAV with the help of the information of connected vehicles ahead and Signal Phase and Timing (SPaT) information through vehicle-to-everything (V2X) communication. A stochastic speed prediction method combining a conditional linear Gaussian speed prediction model and a backpropagation neural network is proposed, which improves the prediction accuracy of the future speed of the predecessor vehicle. The CAV’s target speed is planned based on the network information so that the CAV can pass the intersection without stopping. The fuel efficiency driving problem is transformed into the target speed tracking problem, and the optimal solution is carried out in the model predictive control (MPC) framework, which improves fuel economy while ensuring safety. Compared with existing other schemes verify the effectiveness and advantage of the designed strategy.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106286"},"PeriodicalIF":5.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-19DOI: 10.1016/j.conengprac.2025.106280
Ze Wang, Zhongyang Han, Jun Zhao, Wei Wang
The state prediction of by-product gas system in steel industry plays a pivotal role in its safety assessment, so as to maintain stable operation and production. The fluctuation caused by some units in a time window will then affect others by spatially distributed pipeline network, which may lead to potential safety threats, such as shortage supply, unstable transmission, etc. As such, a multi-node state prediction model considering spatial and temporal characteristics for by-product gas system is proposed in this paper. Considering that the distribution of the key nodes including generation, transmission, storage and consumption presents a non-Euclidean spatial structure, the byproduct gas network is intuitively addressed as a graph model according to the state features in this study, which not only innovatively defines both nodes and edges with regard to their practical consideration, but also establishes physics-related constraints to efficiently and accurately capture the correlation. Then, an interactive extraction mechanism of the node–edge features is designed to achieve dynamic updating of the graph neural network, so that the transient characteristic of gas transportation process can be fully reflected. Finally, the Gated Recurrent Unit (GRU) is introduced to capture the temporal-dependent relationship. Based on the actual data of an iron and steel enterprise in China, the experimental results verified that the proposed method exhibits an advanced accuracy for multi-node prediction. In addition, the prediction interval is constructed to quantify reliability based on the numeric prediction results, which is then verified to be effective for supporting the safety assessment.
{"title":"A spatiotemporal characteristics based multi-nodes state prediction method for byproduct gas system and its application on safety assessment","authors":"Ze Wang, Zhongyang Han, Jun Zhao, Wei Wang","doi":"10.1016/j.conengprac.2025.106280","DOIUrl":"10.1016/j.conengprac.2025.106280","url":null,"abstract":"<div><div>The state prediction of by-product gas system in steel industry plays a pivotal role in its safety assessment, so as to maintain stable operation and production. The fluctuation caused by some units in a time window will then affect others by spatially distributed pipeline network, which may lead to potential safety threats, such as shortage supply, unstable transmission, etc. As such, a multi-node state prediction model considering spatial and temporal characteristics for by-product gas system is proposed in this paper. Considering that the distribution of the key nodes including generation, transmission, storage and consumption presents a non-Euclidean spatial structure, the byproduct gas network is intuitively addressed as a graph model according to the state features in this study, which not only innovatively defines both nodes and edges with regard to their practical consideration, but also establishes physics-related constraints to efficiently and accurately capture the correlation. Then, an interactive extraction mechanism of the node–edge features is designed to achieve dynamic updating of the graph neural network, so that the transient characteristic of gas transportation process can be fully reflected. Finally, the Gated Recurrent Unit (GRU) is introduced to capture the temporal-dependent relationship. Based on the actual data of an iron and steel enterprise in China, the experimental results verified that the proposed method exhibits an advanced accuracy for multi-node prediction. In addition, the prediction interval is constructed to quantify reliability based on the numeric prediction results, which is then verified to be effective for supporting the safety assessment.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106280"},"PeriodicalIF":5.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.conengprac.2025.106282
Kaixin Cui , Wenjing Wu , Jun Shang , Dawei Shi
Alarm systems are essential for the safety maintenance and health management of industrial systems. In this work, a dynamic alarm monitoring approach with data-driven ellipsoidal threshold learning is proposed, and an unknown system is directly learned using noisy data without model identification. An ellipsoid-based normal operating zone of the system variable is iteratively predicted based on system dynamics, and is updated as an external approximation of the intersection of a predicted ellipsoid and a measurement-based ellipsoid with an event-triggering condition. Then, the dynamic alarm limits are calculated for each dimension of the output by an ellipsoid-based quadratic equation, and a projection strategy from output points to the predicted ellipsoids is designed to have two different solutions to the equation. The effectiveness of the proposed dynamic alarm monitoring approach is illustrated by experimental results on the sensor fault and actuator fault detection of an ultrasonic motor with and without an event-triggering condition, respectively.
{"title":"Dynamic alarm monitoring with data-driven ellipsoidal threshold learning","authors":"Kaixin Cui , Wenjing Wu , Jun Shang , Dawei Shi","doi":"10.1016/j.conengprac.2025.106282","DOIUrl":"10.1016/j.conengprac.2025.106282","url":null,"abstract":"<div><div>Alarm systems are essential for the safety maintenance and health management of industrial systems. In this work, a dynamic alarm monitoring approach with data-driven ellipsoidal threshold learning is proposed, and an unknown system is directly learned using noisy data without model identification. An ellipsoid-based normal operating zone of the system variable is iteratively predicted based on system dynamics, and is updated as an external approximation of the intersection of a predicted ellipsoid and a measurement-based ellipsoid with an event-triggering condition. Then, the dynamic alarm limits are calculated for each dimension of the output by an ellipsoid-based quadratic equation, and a projection strategy from output points to the predicted ellipsoids is designed to have two different solutions to the equation. The effectiveness of the proposed dynamic alarm monitoring approach is illustrated by experimental results on the sensor fault and actuator fault detection of an ultrasonic motor with and without an event-triggering condition, respectively.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106282"},"PeriodicalIF":5.4,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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