Pub Date : 2024-11-16DOI: 10.1016/j.conengprac.2024.106167
Mingwei Jia , Lingwei Jiang , Bing Guo , Yi Liu , Tao Chen
Data-driven soft sensors in the process industry, whilst intensively investigated, struggle to handle unforeseen disruptions and operating changes not covered in the training data. Incorporating physical knowledge, such as mass/energy balances and reaction mechanisms, into a data-driven model is a potential remedy. In this study, a physical-anchored graph learning (PAGL) soft sensor is proposed, integrating process variable causality and mass balances. Knowledge-derived causality is further supplemented by mining dependencies from data. PAGL uses causality and mass balance as physical anchors to predict key indicators and evaluate whether the prediction logic aligns with physical principles, ensuring physical consistency in inference. The case study on wastewater treatment demonstrates PAGL's interpretability and reliability, maintaining physical consistency instead of acting as a black box.
{"title":"Physical-anchored graph learning for process key indicator prediction","authors":"Mingwei Jia , Lingwei Jiang , Bing Guo , Yi Liu , Tao Chen","doi":"10.1016/j.conengprac.2024.106167","DOIUrl":"10.1016/j.conengprac.2024.106167","url":null,"abstract":"<div><div>Data-driven soft sensors in the process industry, whilst intensively investigated, struggle to handle unforeseen disruptions and operating changes not covered in the training data. Incorporating physical knowledge, such as mass/energy balances and reaction mechanisms, into a data-driven model is a potential remedy. In this study, a physical-anchored graph learning (PAGL) soft sensor is proposed, integrating process variable causality and mass balances. Knowledge-derived causality is further supplemented by mining dependencies from data. PAGL uses causality and mass balance as physical anchors to predict key indicators and evaluate whether the prediction logic aligns with physical principles, ensuring physical consistency in inference. The case study on wastewater treatment demonstrates PAGL's interpretability and reliability, maintaining physical consistency instead of acting as a black box.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106167"},"PeriodicalIF":5.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656849","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 : 2024-11-16DOI: 10.1016/j.conengprac.2024.106160
Quan-Zhi Liu, Liu Zhang, Yang Xiao, Le Zhang, Guo-Wei Fan
This study addresses the challenge of achieving high-precision attitude control in flexible spacecraft subjected to multiple disturbances (MD). A predictive sliding mode (PSM) control method is proposed to tackle this issue. First, a second-order fully actuated (SOFA) system model for the attitude control of flexible spacecraft is established. Subsequently, sliding mode variables are introduced to enhance the robustness of the closed-loop system. Then, a Diophantine equation and sliding mode variables are applied to establish an incremental second-order fully actuated (ISOFA) sliding mode predictive model. A sliding mode reference is designed using a double power function to eliminate jitter. Based on the designed sliding mode predictive model, the multi-step ahead predictions are developed to optimize attitude tracking performance and suppress MD. Furthermore, the control performance and stability of the system are analyzed. Finally, a series of simulation results demonstrate the effectiveness of the proposed method.
{"title":"Predictive sliding mode control for flexible spacecraft attitude tracking with multiple disturbances","authors":"Quan-Zhi Liu, Liu Zhang, Yang Xiao, Le Zhang, Guo-Wei Fan","doi":"10.1016/j.conengprac.2024.106160","DOIUrl":"10.1016/j.conengprac.2024.106160","url":null,"abstract":"<div><div>This study addresses the challenge of achieving high-precision attitude control in flexible spacecraft subjected to multiple disturbances (MD). A predictive sliding mode (PSM) control method is proposed to tackle this issue. First, a second-order fully actuated (SOFA) system model for the attitude control of flexible spacecraft is established. Subsequently, sliding mode variables are introduced to enhance the robustness of the closed-loop system. Then, a Diophantine equation and sliding mode variables are applied to establish an incremental second-order fully actuated (ISOFA) sliding mode predictive model. A sliding mode reference is designed using a double power function to eliminate jitter. Based on the designed sliding mode predictive model, the multi-step ahead predictions are developed to optimize attitude tracking performance and suppress MD. Furthermore, the control performance and stability of the system are analyzed. Finally, a series of simulation results demonstrate the effectiveness of the proposed method.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106160"},"PeriodicalIF":5.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656850","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 : 2024-11-15DOI: 10.1016/j.conengprac.2024.106162
Kai Zhao , Jia Song , Yang Liu
This paper proposes a three-dimensional spatial–temporal cooperative guidance law for striking maneuvering targets, with consideration of no-fly zones avoidance. A fixed-time convergent integral sliding mode guidance law based on a second-order system consensus protocol is proposed to ensure the consistency of the remaining distance and radial relative velocity, instead of using estimates of time-to-go based on small angle assumptions. In the elevation and azimuth directions, to mitigate excessive guidance commands during the initial phase, a nonlinear sliding surface and a finite-time reaching law are designed to meet impact angle constraints. In addition, considering the stagnation points escape in the process of no-fly zones avoidance an integrated cooperation and obstacle avoidance guidance law is proposed, which effectively avoids no-fly zones, accelerates the convergence speed of cooperative consistency, and reduces terminal errors. Using Lyapunov’s theory, this paper theoretically proves the fixed-time and finite-time convergence characteristics of the proposed algorithm. Simulation results indicate that the miss distance and terminal elevation and azimuth angle errors of the proposed algorithm are 55.04%, 27.5%, and 81.75% of those of the comparison algorithm, respectively.
{"title":"Spatial–temporal cooperative guidance with no-fly zones avoidance","authors":"Kai Zhao , Jia Song , Yang Liu","doi":"10.1016/j.conengprac.2024.106162","DOIUrl":"10.1016/j.conengprac.2024.106162","url":null,"abstract":"<div><div>This paper proposes a three-dimensional spatial–temporal cooperative guidance law for striking maneuvering targets, with consideration of no-fly zones avoidance. A fixed-time convergent integral sliding mode guidance law based on a second-order system consensus protocol is proposed to ensure the consistency of the remaining distance and radial relative velocity, instead of using estimates of time-to-go based on small angle assumptions. In the elevation and azimuth directions, to mitigate excessive guidance commands during the initial phase, a nonlinear sliding surface and a finite-time reaching law are designed to meet impact angle constraints. In addition, considering the stagnation points escape in the process of no-fly zones avoidance an integrated cooperation and obstacle avoidance guidance law is proposed, which effectively avoids no-fly zones, accelerates the convergence speed of cooperative consistency, and reduces terminal errors. Using Lyapunov’s theory, this paper theoretically proves the fixed-time and finite-time convergence characteristics of the proposed algorithm. Simulation results indicate that the miss distance and terminal elevation and azimuth angle errors of the proposed algorithm are 55.04%, 27.5%, and 81.75% of those of the comparison algorithm, respectively.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106162"},"PeriodicalIF":5.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656848","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 : 2024-11-13DOI: 10.1016/j.conengprac.2024.106158
Fabio Widmer, Stijn van Dooren, Christopher H. Onder
The electrification of public transport vehicles offers the potential to relieve city centers of pollutant and noise emissions. Furthermore, electric buses have lower life-cycle greenhouse gas (GHG) emissions than diesel buses, particularly when operated with sustainably produced electricity. However, the heating, ventilation, and air-conditioning (HVAC) system can consume a significant amount of energy, thus limiting the achievable driving range. In this paper, we address the HVAC system in an electric city bus by analyzing the trade-off between the energy consumption and the thermal comfort of the passengers. We do this by developing a dynamic thermal model for the bus, which we simplify by considering it to be in steady state. We introduce a method that is able to quickly optimize the steady-state HVAC system inputs for a large number of samples representative of a year-round operation. A comparison between the results from the steady-state optimization approach and a dynamic simulation reveals small deviations in both the HVAC system power demand and achieved thermal comfort. Thus, the approximation of the system performance with a steady-state model is justified. We present two case studies to demonstrate the practical relevance of the approach. First, we show how the method can be used to compare different HVAC system designs based on a year-round performance evaluation. Second, we show how the method can be used to extract setpoints for online controllers that achieve close-to-optimal performance without any predictive information. In conclusion, this study shows that a steady-state analysis of the HVAC systems of an electric city bus is a valuable approach to evaluate and optimize its performance.
{"title":"Optimization of the energy-comfort trade-off of HVAC systems in electric city buses based on a steady-state model","authors":"Fabio Widmer, Stijn van Dooren, Christopher H. Onder","doi":"10.1016/j.conengprac.2024.106158","DOIUrl":"10.1016/j.conengprac.2024.106158","url":null,"abstract":"<div><div>The electrification of public transport vehicles offers the potential to relieve city centers of pollutant and noise emissions. Furthermore, electric buses have lower life-cycle greenhouse gas (GHG) emissions than diesel buses, particularly when operated with sustainably produced electricity. However, the heating, ventilation, and air-conditioning (HVAC) system can consume a significant amount of energy, thus limiting the achievable driving range. In this paper, we address the HVAC system in an electric city bus by analyzing the trade-off between the energy consumption and the thermal comfort of the passengers. We do this by developing a dynamic thermal model for the bus, which we simplify by considering it to be in steady state. We introduce a method that is able to quickly optimize the steady-state HVAC system inputs for a large number of samples representative of a year-round operation. A comparison between the results from the steady-state optimization approach and a dynamic simulation reveals small deviations in both the HVAC system power demand and achieved thermal comfort. Thus, the approximation of the system performance with a steady-state model is justified. We present two case studies to demonstrate the practical relevance of the approach. First, we show how the method can be used to compare different HVAC system designs based on a year-round performance evaluation. Second, we show how the method can be used to extract setpoints for online controllers that achieve close-to-optimal performance without any predictive information. In conclusion, this study shows that a steady-state analysis of the HVAC systems of an electric city bus is a valuable approach to evaluate and optimize its performance.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106158"},"PeriodicalIF":5.4,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656575","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 : 2024-11-13DOI: 10.1016/j.conengprac.2024.106157
Hai-Nam Nguyen , Bảo-Huy Nguyễn , Thanh Vo-Duy , João Pedro F. Trovão , Minh C. Ta
For years, developing energy management strategies (EMS) for hybrid energy storage systems (HESS) of electric vehicles (EV) has been a topic of great interest thanks to the mutual support of energy sources. In this paper, we approach the energy management problems from the control point of view to exploit the remarkable advantages of control techniques in treating state constraints, system stability, and optimality. By that, we propose a sliding-mode strategy for the EMS of the battery–supercapacitor HESS on EVs. In order to prolong the lifespan of the battery, the rate of change in battery reference current is directly handled as the control input of the management system which is, to our best knowledge, novel in literature. Control parameters of the proposed EMS are optimally tuned by using Particle Swarm Optimization. The performance of the proposed EMS is validated by off-line simulation as well as real-time experiments on a Signal Hardware-in-the-Loop system with various comparisons, testing scenarios, and quality indices. The results and the approach of the paper illustrate the effectiveness and feasibility of the management system that can be applied not only to EVs but also to larger-scale energy networks in further research.
{"title":"Sliding-mode energy management strategy for dual-source electric vehicles handling battery rate of change of current","authors":"Hai-Nam Nguyen , Bảo-Huy Nguyễn , Thanh Vo-Duy , João Pedro F. Trovão , Minh C. Ta","doi":"10.1016/j.conengprac.2024.106157","DOIUrl":"10.1016/j.conengprac.2024.106157","url":null,"abstract":"<div><div>For years, developing energy management strategies (EMS) for hybrid energy storage systems (HESS) of electric vehicles (EV) has been a topic of great interest thanks to the mutual support of energy sources. In this paper, we approach the energy management problems from the control point of view to exploit the remarkable advantages of control techniques in treating state constraints, system stability, and optimality. By that, we propose a sliding-mode strategy for the EMS of the battery–supercapacitor HESS on EVs. In order to prolong the lifespan of the battery, the rate of change in battery reference current is directly handled as the control input of the management system which is, to our best knowledge, novel in literature. Control parameters of the proposed EMS are optimally tuned by using Particle Swarm Optimization. The performance of the proposed EMS is validated by off-line simulation as well as real-time experiments on a Signal Hardware-in-the-Loop system with various comparisons, testing scenarios, and quality indices. The results and the approach of the paper illustrate the effectiveness and feasibility of the management system that can be applied not only to EVs but also to larger-scale energy networks in further research.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106157"},"PeriodicalIF":5.4,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656379","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 : 2024-11-12DOI: 10.1016/j.conengprac.2024.106153
Beatriz Lourenço , Daniel Silvestre
The advent of autonomous driving technologies has paved the way for notable advancements in the realm of transportation systems. This paper explores the dynamic field of truck platooning, focusing on the development of a Nonlinear Model Predictive Control (NMPC) approach within a Cooperative Adaptive Cruise Control (CACC) framework. The research tackles the critical challenges in obstacle avoidance and lane-changing manoeuvres. The core contribution of this work lies in the development and implementation of a novel NMPC algorithm tailored to platoon control. This framework integrates a penalty soft constraint to guarantee obstacle avoidance and maintain platoon coherence while optimising control inputs in real-time. Several experiments, including static and dynamic obstacle avoidance scenarios, validate the efficacy of the proposed approach. In all experiments, the vehicles closely follow one another, resulting in smooth trajectories for all system states and control input signals. Even in the event of abrupt braking by the ego vehicle, the platoon remains cohesive. Moreover, the proposed NMPC proves to be computationally efficient when compared to the state-of-the-art.
{"title":"Enhancing truck platooning efficiency and safety—A distributed Model Predictive Control approach for lane-changing manoeuvres","authors":"Beatriz Lourenço , Daniel Silvestre","doi":"10.1016/j.conengprac.2024.106153","DOIUrl":"10.1016/j.conengprac.2024.106153","url":null,"abstract":"<div><div>The advent of autonomous driving technologies has paved the way for notable advancements in the realm of transportation systems. This paper explores the dynamic field of truck platooning, focusing on the development of a Nonlinear Model Predictive Control (NMPC) approach within a Cooperative Adaptive Cruise Control (CACC) framework. The research tackles the critical challenges in obstacle avoidance and lane-changing manoeuvres. The core contribution of this work lies in the development and implementation of a novel NMPC algorithm tailored to platoon control. This framework integrates a penalty soft constraint to guarantee obstacle avoidance and maintain platoon coherence while optimising control inputs in real-time. Several experiments, including static and dynamic obstacle avoidance scenarios, validate the efficacy of the proposed approach. In all experiments, the vehicles closely follow one another, resulting in smooth trajectories for all system states and control input signals. Even in the event of abrupt braking by the ego vehicle, the platoon remains cohesive. Moreover, the proposed NMPC proves to be computationally efficient when compared to the state-of-the-art.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106153"},"PeriodicalIF":5.4,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656378","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 : 2024-11-08DOI: 10.1016/j.conengprac.2024.106155
Aigerim Nurbayeva, Matteo Rubagotti
This paper proposes a methodology for safely planning the motion of a robot manipulator sharing its workspace with a human operator. The motion of the robot is continuously re-planned via nonlinear model predictive control (NMPC), imposing the so-called speed and separation monitoring (SSM) condition to guarantee human safety. Contrary to previous works in the field, the NMPC algorithm is designed with an ellipsoidal terminal constraint, to enlarge the domain of attraction compared to the case in which a point terminal constraint was imposed. This is a very important aspect in real-world applications, allowing the robot to plan its motion from initial configurations that are relatively far from the goal point. Theoretical results are proved on recursive feasibility and closed-loop stability for both cases of NMPC with point and set terminal constraints, under the simplifying assumption of a static human. The effectiveness of the proposed approach is verified via numerical evaluation of the domain of attraction and with experiments on a UR5 manipulator.
{"title":"Nonlinear model predictive control with set terminal constraint for safe robot motion planning via speed and separation monitoring","authors":"Aigerim Nurbayeva, Matteo Rubagotti","doi":"10.1016/j.conengprac.2024.106155","DOIUrl":"10.1016/j.conengprac.2024.106155","url":null,"abstract":"<div><div>This paper proposes a methodology for safely planning the motion of a robot manipulator sharing its workspace with a human operator. The motion of the robot is continuously re-planned via nonlinear model predictive control (NMPC), imposing the so-called <em>speed and separation monitoring</em> (SSM) condition to guarantee human safety. Contrary to previous works in the field, the NMPC algorithm is designed with an ellipsoidal terminal constraint, to enlarge the domain of attraction compared to the case in which a point terminal constraint was imposed. This is a very important aspect in real-world applications, allowing the robot to plan its motion from initial configurations that are relatively far from the goal point. Theoretical results are proved on recursive feasibility and closed-loop stability for both cases of NMPC with point and set terminal constraints, under the simplifying assumption of a static human. The effectiveness of the proposed approach is verified via numerical evaluation of the domain of attraction and with experiments on a UR5 manipulator.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106155"},"PeriodicalIF":5.4,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656377","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 : 2024-11-06DOI: 10.1016/j.conengprac.2024.106152
Leontine Aarnoudse , Peter den Toom , Tom Oomen
Iterative feedback tuning (IFT) enables the tuning of feedback controllers using only measured data to obtain the gradient of a cost criterion. The aim of this paper is to reduce the required number of experiments for MIMO IFT. It is shown that, through a randomization technique, an unbiased gradient estimate can be obtained from a single dedicated experiment, regardless of the size of the MIMO system. The gradient estimate is used in a stochastic gradient descent algorithm. The approach is experimentally validated on a mechatronic system, showing a significantly reduced number of experiments compared to standard IFT.
迭代反馈调谐（IFT）可以仅使用测量数据来获得成本准则的梯度，从而对反馈控制器进行调谐。本文旨在减少 MIMO IFT 所需的实验次数。研究表明，通过随机化技术，无论多输入多输出系统的规模如何，都能从一次专门实验中获得无偏梯度估计值。梯度估计值用于随机梯度下降算法。该方法在机电一体化系统上进行了实验验证，结果表明，与标准 IFT 相比，实验次数大大减少。
{"title":"Randomized iterative feedback tuning for fast MIMO feedback design of a mechatronic system","authors":"Leontine Aarnoudse , Peter den Toom , Tom Oomen","doi":"10.1016/j.conengprac.2024.106152","DOIUrl":"10.1016/j.conengprac.2024.106152","url":null,"abstract":"<div><div>Iterative feedback tuning (IFT) enables the tuning of feedback controllers using only measured data to obtain the gradient of a cost criterion. The aim of this paper is to reduce the required number of experiments for MIMO IFT. It is shown that, through a randomization technique, an unbiased gradient estimate can be obtained from a single dedicated experiment, regardless of the size of the MIMO system. The gradient estimate is used in a stochastic gradient descent algorithm. The approach is experimentally validated on a mechatronic system, showing a significantly reduced number of experiments compared to standard IFT.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106152"},"PeriodicalIF":5.4,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593553","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 : 2024-11-05DOI: 10.1016/j.conengprac.2024.106142
Sourav Sinha , Mazen Farhood , Daniel J. Stilwell
This paper addresses the design and analysis of path-following controllers for an autonomous underwater vehicle (AUV) using a robustness analysis framework based on integral quadratic constraints (IQCs). The AUV is modeled as a linear fractional transformation (LFT) on uncertainties and is affected by exogenous inputs such as measurement noise and ocean currents. The proposed approach leverages a learning-based method to approximate the nonlinear hydrodynamic model with a linear parameter-varying one. Additionally, modeling uncertainties are incorporated into the other subsystem models of the AUV to capture the discrepancies between the outputs of the postulated mathematical abstractions and the experimental data. The resulting uncertain LFT system adequately captures the AUV behavior within a desired envelope. Ocean current disturbances are treated as uncertainties within the LFT system and properly characterized to reduce conservatism. The robust performance level, obtained from IQC analysis, serves as a qualitative measure of a controller’s performance, and is utilized in guiding the controller design process. The proposed approach is employed to design and controllers for the AUV. A comprehensive IQC-based analysis is subsequently conducted to demonstrate the robustness of the designed controllers to modeling uncertainties and disturbances. To validate the analysis results, extensive nonlinear simulations and underwater experiments are performed. The outcomes showcase the efficacy and reliability of the proposed approach in achieving robust control for the AUV.
{"title":"Control design and analysis for autonomous underwater vehicles using integral quadratic constraints","authors":"Sourav Sinha , Mazen Farhood , Daniel J. Stilwell","doi":"10.1016/j.conengprac.2024.106142","DOIUrl":"10.1016/j.conengprac.2024.106142","url":null,"abstract":"<div><div>This paper addresses the design and analysis of path-following controllers for an autonomous underwater vehicle (AUV) using a robustness analysis framework based on integral quadratic constraints (IQCs). The AUV is modeled as a linear fractional transformation (LFT) on uncertainties and is affected by exogenous inputs such as measurement noise and ocean currents. The proposed approach leverages a learning-based method to approximate the nonlinear hydrodynamic model with a linear parameter-varying one. Additionally, modeling uncertainties are incorporated into the other subsystem models of the AUV to capture the discrepancies between the outputs of the postulated mathematical abstractions and the experimental data. The resulting uncertain LFT system adequately captures the AUV behavior within a desired envelope. Ocean current disturbances are treated as uncertainties within the LFT system and properly characterized to reduce conservatism. The robust performance level, obtained from IQC analysis, serves as a qualitative measure of a controller’s performance, and is utilized in guiding the controller design process. The proposed approach is employed to design <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> controllers for the AUV. A comprehensive IQC-based analysis is subsequently conducted to demonstrate the robustness of the designed controllers to modeling uncertainties and disturbances. To validate the analysis results, extensive nonlinear simulations and underwater experiments are performed. The outcomes showcase the efficacy and reliability of the proposed approach in achieving robust control for the AUV.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106142"},"PeriodicalIF":5.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586645","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 : 2024-11-05DOI: 10.1016/j.conengprac.2024.106154
Weiguang Yu , Daokui Qu , Fang Xu , Lei Zhang , Fengshan Zou , Zhenjun Du
To meet the demands of high-speed and high-accuracy applications of robotic manipulators, this paper proposes a time-optimal multi-point trajectory planning method with continuous jerk and constant average acceleration. A piecewise sine jerk model is developed for jerk continuity throughout the entire motion profile. An equivalent transformation of this complex model into the simple trapezoidal velocity model is proposed, effectively reducing the computational complexity and ensuring the reliability of real-time planning. The introduction of a parameter, named the trajectory smoothness coefficient, allows for a convenient trade-off between the priorities of speed and smoothness. The adaptive computation algorithm for peak jerk results in a constant average acceleration along paths of any length, ensuring a consistent level of work efficiency regardless of the density of path control points. Through a comprehensive evaluation of the critical constraints for each potential profile type, the single joint’s time-optimal and multiple joints’ time-synchronized planning problems are solved with closed-form solutions. Furthermore, by designing a multi-joint multi-point velocity look-ahead strategy, time-optimal multi-point trajectory planning for robotic manipulators is realized. Simulation and experimental results on a manipulator demonstrate the effectiveness of the proposed approach in improving time efficiency.
{"title":"Time-optimal multi-point trajectory generation for robotic manipulators with continuous jerk and constant average acceleration","authors":"Weiguang Yu , Daokui Qu , Fang Xu , Lei Zhang , Fengshan Zou , Zhenjun Du","doi":"10.1016/j.conengprac.2024.106154","DOIUrl":"10.1016/j.conengprac.2024.106154","url":null,"abstract":"<div><div>To meet the demands of high-speed and high-accuracy applications of robotic manipulators, this paper proposes a time-optimal multi-point trajectory planning method with continuous jerk and constant average acceleration. A piecewise sine jerk model is developed for jerk continuity throughout the entire motion profile. An equivalent transformation of this complex model into the simple trapezoidal velocity model is proposed, effectively reducing the computational complexity and ensuring the reliability of real-time planning. The introduction of a parameter, named the trajectory smoothness coefficient, allows for a convenient trade-off between the priorities of speed and smoothness. The adaptive computation algorithm for peak jerk results in a constant average acceleration along paths of any length, ensuring a consistent level of work efficiency regardless of the density of path control points. Through a comprehensive evaluation of the critical constraints for each potential profile type, the single joint’s time-optimal and multiple joints’ time-synchronized planning problems are solved with closed-form solutions. Furthermore, by designing a multi-joint multi-point velocity look-ahead strategy, time-optimal multi-point trajectory planning for robotic manipulators is realized. Simulation and experimental results on a manipulator demonstrate the effectiveness of the proposed approach in improving time efficiency.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106154"},"PeriodicalIF":5.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586646","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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