Pub Date : 2024-05-15DOI: 10.3389/fcteg.2024.1394668
Ahmad Al Ali, Zheng H. Zhu
This study introduces a novel approach for the path planning of a 6-degree-of-freedom free-floating space robotic manipulator, focusing on collision and obstacle avoidance through reinforcement learning. It addresses the challenges of dynamic coupling between the spacecraft and the robotic manipulator, which significantly affects control and precision in the space environment. An innovative reward function is introduced in the reinforcement learning framework to ensure accurate alignment of the manipulator’s end effector with its target, despite disturbances from the spacecraft and the need for obstacle and collision avoidance. A key feature of this study is the use of quaternions for orientation representation to avoid the singularities associated with conventional Euler angles and enhance the training process’ efficiency. Furthermore, the reward function incorporates joint velocity constraints to refine the path planning for the manipulator joints, enabling efficient obstacle and collision avoidance. Another key feature of this study is the inclusion of observation noise in the training process to enhance the robustness of the agent. Results demonstrate that the proposed reward function enables effective exploration of the action space, leading to high precision in achieving the desired objectives. The study provides a solid theoretical foundation for the application of reinforcement learning in complex free-floating space robotic operations and offers insights for future space missions.
{"title":"Reinforcement learning for path planning of free-floating space robotic manipulator with collision avoidance and observation noise","authors":"Ahmad Al Ali, Zheng H. Zhu","doi":"10.3389/fcteg.2024.1394668","DOIUrl":"https://doi.org/10.3389/fcteg.2024.1394668","url":null,"abstract":"This study introduces a novel approach for the path planning of a 6-degree-of-freedom free-floating space robotic manipulator, focusing on collision and obstacle avoidance through reinforcement learning. It addresses the challenges of dynamic coupling between the spacecraft and the robotic manipulator, which significantly affects control and precision in the space environment. An innovative reward function is introduced in the reinforcement learning framework to ensure accurate alignment of the manipulator’s end effector with its target, despite disturbances from the spacecraft and the need for obstacle and collision avoidance. A key feature of this study is the use of quaternions for orientation representation to avoid the singularities associated with conventional Euler angles and enhance the training process’ efficiency. Furthermore, the reward function incorporates joint velocity constraints to refine the path planning for the manipulator joints, enabling efficient obstacle and collision avoidance. Another key feature of this study is the inclusion of observation noise in the training process to enhance the robustness of the agent. Results demonstrate that the proposed reward function enables effective exploration of the action space, leading to high precision in achieving the desired objectives. The study provides a solid theoretical foundation for the application of reinforcement learning in complex free-floating space robotic operations and offers insights for future space missions.","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140974330","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 : 2024-04-03DOI: 10.3389/fcteg.2024.1343851
Hanjie Wang, Diana Guimaraes, Tobias Nef, Kenneth J. Hunt
A self-paced (SP) heart rate (HR) control system proposed in a previous study was found to be feasible for healthy participants. The aims of this work were to investigate whether the SP HR control system is feasible to achieve accurate HR control in a participant with gait impairments, and to assess its interaction with an existing motor-driven body weight support (BWS) system.One participant with cerebral palsy was recruited in this case study. Three preliminary tests were completed to determine the appropriate mean value and amplitude of the target heart rate curve, and to identify a customised heart rate response model. Two series of formal self-paced heart rate control tests were then conducted to investigate the influence of different heart rate compensators and the presence of the BWS system.The customised heart rate controller achieved improved accuracy in heart rate control and reduced oscillation in the treadmill target speed: the root-mean-square heart rate tracking error (RMSE) was 2.38 beats per minute (bpm) vs. 3.91 bpm (customised controller vs. nominal controller), and the average power of changes in the treadmill target speed was 0.4 × 10−4 m2/s2 vs. 8.4 × 10−4 m2/s2. The BWS system resulted in improved HR tracking accuracy: RMSE on heart rate tracking was 3.02 bpm vs. 3.50 bpm (with BWS vs. without BWS). The BWS system had no influence on the automatic position control accuracy: RMSE on distance tracking was 0.0159 m vs. 0.0164 m.After customising the heart rate compensator, the self-paced heart rate control system is feasible to achieve accurate heart rate control in an individual with gait impairments, and it can correctly interact with the BWS system.
{"title":"Self-paced heart rate control during treadmill exercise for persons with gait impairment: a case study","authors":"Hanjie Wang, Diana Guimaraes, Tobias Nef, Kenneth J. Hunt","doi":"10.3389/fcteg.2024.1343851","DOIUrl":"https://doi.org/10.3389/fcteg.2024.1343851","url":null,"abstract":"A self-paced (SP) heart rate (HR) control system proposed in a previous study was found to be feasible for healthy participants. The aims of this work were to investigate whether the SP HR control system is feasible to achieve accurate HR control in a participant with gait impairments, and to assess its interaction with an existing motor-driven body weight support (BWS) system.One participant with cerebral palsy was recruited in this case study. Three preliminary tests were completed to determine the appropriate mean value and amplitude of the target heart rate curve, and to identify a customised heart rate response model. Two series of formal self-paced heart rate control tests were then conducted to investigate the influence of different heart rate compensators and the presence of the BWS system.The customised heart rate controller achieved improved accuracy in heart rate control and reduced oscillation in the treadmill target speed: the root-mean-square heart rate tracking error (RMSE) was 2.38 beats per minute (bpm) vs. 3.91 bpm (customised controller vs. nominal controller), and the average power of changes in the treadmill target speed was 0.4 × 10−4 m2/s2 vs. 8.4 × 10−4 m2/s2. The BWS system resulted in improved HR tracking accuracy: RMSE on heart rate tracking was 3.02 bpm vs. 3.50 bpm (with BWS vs. without BWS). The BWS system had no influence on the automatic position control accuracy: RMSE on distance tracking was 0.0159 m vs. 0.0164 m.After customising the heart rate compensator, the self-paced heart rate control system is feasible to achieve accurate heart rate control in an individual with gait impairments, and it can correctly interact with the BWS system.","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140747885","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 : 2024-02-21DOI: 10.3389/fcteg.2024.1380005
Daigo Shishika, M. Dorothy, D. Macharet, Jason R. Marden, Panagiotis Tsiotras
{"title":"Editorial: Cooperative control and team behaviors in adversarial environments","authors":"Daigo Shishika, M. Dorothy, D. Macharet, Jason R. Marden, Panagiotis Tsiotras","doi":"10.3389/fcteg.2024.1380005","DOIUrl":"https://doi.org/10.3389/fcteg.2024.1380005","url":null,"abstract":"","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140443540","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 : 2023-11-03DOI: 10.3389/fcteg.2023.1279811
{"title":"Erratum: Global versus local Lyapunov approach used in disturbance observer-based wind turbine control","authors":"","doi":"10.3389/fcteg.2023.1279811","DOIUrl":"https://doi.org/10.3389/fcteg.2023.1279811","url":null,"abstract":"","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139289712","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 : 2023-11-02DOI: 10.3389/fcteg.2023.1279454
Daigo Shishika, Michael Dorothy, Douglas G. Macharet
Interesting and effective team behaviors arise when a group of agents contend with adversaries. Examples range from animal group behaviors observed in nature to strategies used in team sports. This mini review goes over literature in multiagent systems that study group control in adversarial scenarios. We identify different ways of formulating adversaries and discuss various types of teaming behavior that arise. Specifically from the perspective of multiagent task assignment, the types of tasks and the nature of assignments brought by the adversary are categorized. The frontiers of the current literature and the direction for future research are discussed at the end.
{"title":"Teaming behavior in adversarial scenarios","authors":"Daigo Shishika, Michael Dorothy, Douglas G. Macharet","doi":"10.3389/fcteg.2023.1279454","DOIUrl":"https://doi.org/10.3389/fcteg.2023.1279454","url":null,"abstract":"Interesting and effective team behaviors arise when a group of agents contend with adversaries. Examples range from animal group behaviors observed in nature to strategies used in team sports. This mini review goes over literature in multiagent systems that study group control in adversarial scenarios. We identify different ways of formulating adversaries and discuss various types of teaming behavior that arise. Specifically from the perspective of multiagent task assignment, the types of tasks and the nature of assignments brought by the adversary are categorized. The frontiers of the current literature and the direction for future research are discussed at the end.","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135935022","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 : 2023-08-17DOI: 10.3389/fcteg.2023.1237759
Leon Babić, M. Lauricella, G. Ceusters, M. Biskoping
This paper presents a stochastic model predictive control approach combined with a time-series forecasting technique to tackle the problem of microgrid energy management in the face of uncertainty. The data-driven non-parametric chance constraint method is used to formulate chance constraints for stochastic model predictive control, while removing the dependency on probability density assumptions of uncertain variables and retaining the linear structure of the resulting optimization problem. The proposed approach is suitable for implementation on systems with limited computational power or limited memory storage, thanks to its simple linear structure and its ability to provide accurate results within pre-defined confidence levels, even when using small data batches. The proposed forecasting and stochastic model predictive control approaches are applied on a numerical example featuring a small grid-connected microgrid with PV generation, a battery storage system, and a non-controllable load, showing the ability to reduce costs by reducing the confidence level, and to satisfy pre-defined confidence levels.
{"title":"Data-driven non-parametric chance-constrained model predictive control for microgrids energy management using small data batches","authors":"Leon Babić, M. Lauricella, G. Ceusters, M. Biskoping","doi":"10.3389/fcteg.2023.1237759","DOIUrl":"https://doi.org/10.3389/fcteg.2023.1237759","url":null,"abstract":"This paper presents a stochastic model predictive control approach combined with a time-series forecasting technique to tackle the problem of microgrid energy management in the face of uncertainty. The data-driven non-parametric chance constraint method is used to formulate chance constraints for stochastic model predictive control, while removing the dependency on probability density assumptions of uncertain variables and retaining the linear structure of the resulting optimization problem. The proposed approach is suitable for implementation on systems with limited computational power or limited memory storage, thanks to its simple linear structure and its ability to provide accurate results within pre-defined confidence levels, even when using small data batches. The proposed forecasting and stochastic model predictive control approaches are applied on a numerical example featuring a small grid-connected microgrid with PV generation, a battery storage system, and a non-controllable load, showing the ability to reduce costs by reducing the confidence level, and to satisfy pre-defined confidence levels.","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45944996","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 : 2023-06-08DOI: 10.3389/fcteg.2023.1228462
A. Visioli
The aim of this Research Topic is to focus on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of Control and Automation Systems. Motivated bymany factors such as the need of an increased quality of the products, of a reduction of costs and of an increment in flexibility of the production, there has been a tremendous development of industrial control and automation systems in the last decades. In fact, in the context of Industry 4.0 paradigm, with the (almost) full digitalization of the production, control systems play a key role in the different layers of the automation pyramid. Three papers have been gathered in the Research Topic. The first one deals with education. In it, Rossiter explains that the advancements in control systems and their increased pervasiveness at different levels require to rethink the topics to be taught in a first (possibly unique) control course at the university. In addition, the availability of many resources in the web (such as videos, virtual, and remote laboratories, interactive tools, etc.) can be exploited to improve teaching and to achieve an effective learning for each student. Indeed, the COVID-19 pandemic has pushed instructors to use such a kind of tools and has raised the expectations from the students. A recent survey organized by the Technical Committee on Education of the International Federation of Automatic Control has given guidelines in this context: rather than providing many mathematical details, a first control course should enthused students in order to make them aware of the role of control systems in different fields. Further, software tools and online resources can be exploited to help students in focusing on the main concepts rather than on tedious mathematical calculations (which can be left to subsequent courses), thus making their more prepared to face the diverse problems posed by industry nowadays. In the second paper, Alfaro and Vilanova address a relevant practical issue when Proportional-Integral-Derivative (PID) controllers are used. PID controllers are the most employed feedback controllers in industry and they represent the fundamental brick of the lowest layer in an automation system. For this reason, it is essential they provide a high performance, in particular if optimization algorithms (for example, model predictive control) are used on their top to define the set-points that optimize the overall production. Since PID controllers can be implemented in different forms (in particular the proportional and/or the derivative action can be applied to the control error or directly to the process variable), it is important to investigate if tuning rules that are designed for a given form provide the required performance and robustness when applied on PID controller with a different form. This concept is denoted as resilience and its analysis highlights the need of carefully considering the PID controller st
{"title":"Editorial: Insights in control and automation systems","authors":"A. Visioli","doi":"10.3389/fcteg.2023.1228462","DOIUrl":"https://doi.org/10.3389/fcteg.2023.1228462","url":null,"abstract":"The aim of this Research Topic is to focus on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of Control and Automation Systems. Motivated bymany factors such as the need of an increased quality of the products, of a reduction of costs and of an increment in flexibility of the production, there has been a tremendous development of industrial control and automation systems in the last decades. In fact, in the context of Industry 4.0 paradigm, with the (almost) full digitalization of the production, control systems play a key role in the different layers of the automation pyramid. Three papers have been gathered in the Research Topic. The first one deals with education. In it, Rossiter explains that the advancements in control systems and their increased pervasiveness at different levels require to rethink the topics to be taught in a first (possibly unique) control course at the university. In addition, the availability of many resources in the web (such as videos, virtual, and remote laboratories, interactive tools, etc.) can be exploited to improve teaching and to achieve an effective learning for each student. Indeed, the COVID-19 pandemic has pushed instructors to use such a kind of tools and has raised the expectations from the students. A recent survey organized by the Technical Committee on Education of the International Federation of Automatic Control has given guidelines in this context: rather than providing many mathematical details, a first control course should enthused students in order to make them aware of the role of control systems in different fields. Further, software tools and online resources can be exploited to help students in focusing on the main concepts rather than on tedious mathematical calculations (which can be left to subsequent courses), thus making their more prepared to face the diverse problems posed by industry nowadays. In the second paper, Alfaro and Vilanova address a relevant practical issue when Proportional-Integral-Derivative (PID) controllers are used. PID controllers are the most employed feedback controllers in industry and they represent the fundamental brick of the lowest layer in an automation system. For this reason, it is essential they provide a high performance, in particular if optimization algorithms (for example, model predictive control) are used on their top to define the set-points that optimize the overall production. Since PID controllers can be implemented in different forms (in particular the proportional and/or the derivative action can be applied to the control error or directly to the process variable), it is important to investigate if tuning rules that are designed for a given form provide the required performance and robustness when applied on PID controller with a different form. This concept is denoted as resilience and its analysis highlights the need of carefully considering the PID controller st","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47449983","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 : 2023-04-20DOI: 10.3389/fcteg.2023.1185502
Gengjin Shi, Miaomiao Ma, Donghai Li, Yanjun Ding, Kwang Y. Lee
Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants. Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID). Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants.
{"title":"A process-model-free method for model predictive control via a reference model-based proportional-integral-derivative controller with application to a thermal power plant","authors":"Gengjin Shi, Miaomiao Ma, Donghai Li, Yanjun Ding, Kwang Y. Lee","doi":"10.3389/fcteg.2023.1185502","DOIUrl":"https://doi.org/10.3389/fcteg.2023.1185502","url":null,"abstract":"Introduction: Model predictive control (MPC) is an advanced control strategy which can achieve fast reference tracking response and deal with process constraints, time delay and multivariable problems. However, thermal processes in coal-fired power plants are usually difficult to model accurately, which limits the application of MPC to thermal power plants. Methods: To solve the problem, this paper proposes a process-model-free method for MPC via a reference model (RM)-based controller, i.e., a desired dynamic equational (DDE) proportional-integral-derivative (PID) controller (DDE-PID). Results and Discussion: The DDE-PID can provide the design model and enhance the disturbance rejection ability for MPC. Simulations and results of field tests on a coal-fired unit show the superiorities of the proposed controller in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of the field application of the MPC with DDE-PID, or MPC-DDE in short, to thermal power plants.","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49611067","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 : 2023-04-11DOI: 10.3389/fcteg.2023.1188846
Jairo Inga, S. Rothfuss, Y. Saito, C. Sentouh
Human–machine cooperation and shared control have become major areas of interest in various scientific communities. Humans and machines working together as a team yield a high potential which can be leveraged in numerous application domains. The articles in this Research Topic review state-of-the-art methods and present recent approaches for the modeling and design of human–machine cooperative systems, showcasing the latest research for a variety of applications. In addition, the articles show different ways in which the interaction between humans and machines can take place. The huge variety of interaction scenarios as well as the “type” of interaction lead to a similarly large spectrum of models and methods for designing machines that are capable of completing tasks together with a human. One of the most prominent application domains of cooperative and shared control systems is highly automated driving. This is reflected in two articles reporting on research in this application field. The article titled “A review of shared control in automated vehicles: System evaluation” by Sarabia et al. acknowledges the pivotal role of human–machine cooperative driving in future transportation and provides a survey of recent literature focusing on studies with real drivers. The authors emphasize the importance of turning the attention to the evaluation methodology of shared control approaches. The article reviews the recent literature, focusing both on the study design and on the various metrics used in the studies. The authors provide valuable conclusions. For example, research on shared longitudinal control should catch up with research on shared lateral control. Control authority shifting based on driver state should keep receiving increasing attention. Lastly, the evaluation of the interaction itself and of safety have not been performed as intensively as the evaluation of driving performance. The work of Oudainia et al. aims at minimizing conflicts between drivers and lane keeping systems of intelligent vehicles. In their article titled “Online driver model parameter identification using the Lyapunov approach based shared control,” the authors present a driving assistance system for lane keeping, which is based on a dynamic driver model. To robustly identify the driver model parameters for different drivers and situations, a OPEN ACCESS
{"title":"Editorial: Model-based methods for human–machine cooperative and shared control systems","authors":"Jairo Inga, S. Rothfuss, Y. Saito, C. Sentouh","doi":"10.3389/fcteg.2023.1188846","DOIUrl":"https://doi.org/10.3389/fcteg.2023.1188846","url":null,"abstract":"Human–machine cooperation and shared control have become major areas of interest in various scientific communities. Humans and machines working together as a team yield a high potential which can be leveraged in numerous application domains. The articles in this Research Topic review state-of-the-art methods and present recent approaches for the modeling and design of human–machine cooperative systems, showcasing the latest research for a variety of applications. In addition, the articles show different ways in which the interaction between humans and machines can take place. The huge variety of interaction scenarios as well as the “type” of interaction lead to a similarly large spectrum of models and methods for designing machines that are capable of completing tasks together with a human. One of the most prominent application domains of cooperative and shared control systems is highly automated driving. This is reflected in two articles reporting on research in this application field. The article titled “A review of shared control in automated vehicles: System evaluation” by Sarabia et al. acknowledges the pivotal role of human–machine cooperative driving in future transportation and provides a survey of recent literature focusing on studies with real drivers. The authors emphasize the importance of turning the attention to the evaluation methodology of shared control approaches. The article reviews the recent literature, focusing both on the study design and on the various metrics used in the studies. The authors provide valuable conclusions. For example, research on shared longitudinal control should catch up with research on shared lateral control. Control authority shifting based on driver state should keep receiving increasing attention. Lastly, the evaluation of the interaction itself and of safety have not been performed as intensively as the evaluation of driving performance. The work of Oudainia et al. aims at minimizing conflicts between drivers and lane keeping systems of intelligent vehicles. In their article titled “Online driver model parameter identification using the Lyapunov approach based shared control,” the authors present a driving assistance system for lane keeping, which is based on a dynamic driver model. To robustly identify the driver model parameters for different drivers and situations, a OPEN ACCESS","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47801796","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 : 2023-03-31DOI: 10.3389/fcteg.2023.1162318
Ying Xiong, Xuhua Shi, Yongjian Ma, Yifan Chen
Crude Oil Distillation Unit (CDU) is one of the most important separation installations in the petroleum refinery industries. In this work, a Bi-level Surrogate column model Aided Constrained Optimization Design (Bi-SACOD) is proposed for time-consuming objectives and constraints in the evolutionary optimization design of CDUs. The main components of Bi-SACOD include bi-level surrogate model construction (Bi-SMC), bi-level model management (Bi-MM), and particle swarm optimization (PSO) mixed-integer constrained evolutionary (PSO-MICE) search. Bi-SMC implements surrogate column model construction and feasible domain identification. Bi-MM combines surrogate column models with rigorous CDU simulations to perform model management, and PSO-MICE implements optimum search works. The optimization results of the CDUs indicate that Bi-SACOD outperforms the single-level surrogate column model approaches, and are more consistent with the rigorous CDU model optimization approach, whereas the evaluation numbers of the time-consuming rigorous models are significantly reduced.
{"title":"Optimization design of crude oil distillation unit using bi-level surrogate model","authors":"Ying Xiong, Xuhua Shi, Yongjian Ma, Yifan Chen","doi":"10.3389/fcteg.2023.1162318","DOIUrl":"https://doi.org/10.3389/fcteg.2023.1162318","url":null,"abstract":"Crude Oil Distillation Unit (CDU) is one of the most important separation installations in the petroleum refinery industries. In this work, a Bi-level Surrogate column model Aided Constrained Optimization Design (Bi-SACOD) is proposed for time-consuming objectives and constraints in the evolutionary optimization design of CDUs. The main components of Bi-SACOD include bi-level surrogate model construction (Bi-SMC), bi-level model management (Bi-MM), and particle swarm optimization (PSO) mixed-integer constrained evolutionary (PSO-MICE) search. Bi-SMC implements surrogate column model construction and feasible domain identification. Bi-MM combines surrogate column models with rigorous CDU simulations to perform model management, and PSO-MICE implements optimum search works. The optimization results of the CDUs indicate that Bi-SACOD outperforms the single-level surrogate column model approaches, and are more consistent with the rigorous CDU model optimization approach, whereas the evaluation numbers of the time-consuming rigorous models are significantly reduced.","PeriodicalId":73076,"journal":{"name":"Frontiers in control engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47249115","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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