M. E. Geurts;A. Katriniok;E. Silvas;N. J. Brouwer;W. P. M. H. Heemels
{"title":"Model Predictive Control for Lane Merging Automation With Recursive Feasibility Guarantees and Its Experimental Validation","authors":"M. E. Geurts;A. Katriniok;E. Silvas;N. J. Brouwer;W. P. M. H. Heemels","doi":"10.1109/TCST.2024.3485306","DOIUrl":"https://doi.org/10.1109/TCST.2024.3485306","url":null,"abstract":"To improve on road safety when autonomous vehicles (AVs) are introduced for highway or urban driving, in this article, we design an automated merging algorithm for an AV into a mixed-traffic flow scenario (i.e., traffic including autonomous and manually driven vehicles). In particular, we propose a novel model predictive control (MPC)-based solution to perform a merging procedure from a double lane into a single lane and continue with (adaptive) cruise control [(A)CC] functionality after the merge in one integrated algorithm. The proposed MPC balances fast progress along the path with comfort, while obeying a state-dependent safety distance and velocity bounds. Recursive feasibility, leading to safety and proper behavior (i.e., rigorously satisfying constraints), is guaranteed by the design of proper terminal sets, extending existing terminal sets in the literature. The resulting MPC problem is a mixed-integer quadratic program (MIQP) problem, which can be solved for global optimality. Through numerical simulations and experimental validation of the algorithm with multibrand cars, we demonstrate desirable behavior and verify the effectiveness of the proposed MPC merging scheme.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"566-581"},"PeriodicalIF":4.9,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489061","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}
{"title":"Identification of the Photovoltaic Module Dynamic Model via Dynamic Regressor Extension and Mixing","authors":"Alexey Bobtsov;Fernando Mancilla-David;Stanislav Aranovskiy;Romeo Ortega","doi":"10.1109/TCST.2024.3483438","DOIUrl":"https://doi.org/10.1109/TCST.2024.3483438","url":null,"abstract":"This brief deals with the problem of online parameter identification of the parameters of the dynamic model of a photovoltaic (PV) array connected to a power system through a power converter. It has been shown in the literature that when interacting with switching power converters, the dynamic model is able to better account for the PV array operation compared to the classical five-parameter static model of the array. While there are many results of identification of the parameters of the latter model, to the best of our knowledge, no one has provided a solution for the aforementioned more complex dynamic model since it concerns the parameter estimation of a nonlinear, underexcited system with unmeasurable state variables. Achieving such an objective is the main contribution of this brief. We propose a new parameterization of the dynamic model, which, combined with the powerful identification technique of dynamic regressor extension and mixing (DREM), ensures a fast and accurate online estimation of the unknown parameters. Realistic numerical examples via computer simulations are presented to assess the performance of the proposed approach—even being able to track the parameter variations when the system changes operating point.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"799-806"},"PeriodicalIF":4.9,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489089","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}
R. de Haan;T. P. J. van der Sande;E. Lefeber;I. J. M. Besselink
{"title":"Cooperative Adaptive Cruise Control for Heterogeneous Platoons With Delays: Controller Design and Experiments","authors":"R. de Haan;T. P. J. van der Sande;E. Lefeber;I. J. M. Besselink","doi":"10.1109/TCST.2024.3478475","DOIUrl":"https://doi.org/10.1109/TCST.2024.3478475","url":null,"abstract":"Cooperative adaptive cruise control (CACC) has the potential to increase road throughput and safety. To achieve full deployment of CACC on highways, controllers should be able to deal with heterogeneities in the vehicle string. Moreover, actuation delays have shown to be detrimental to the performance of controllers in such settings. In this article, we present a controller design for heterogeneous platoons, where the ego vehicle experiences an actuation delay in the driveline. The proposed controller does not require driveline information of the preceding vehicle, yielding a control approach suitable for heterogeneous platoons. Moreover, no constraints are imposed on the ordering of the delays throughout the platoon. We derive input-to-state stability conditions for the closed-loop system with delay and analyze the string stability properties of the system, taking into account both actuation and communication delay. The proposed controller is experimentally validated with a platoon consisting of two vehicles.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1361-1371"},"PeriodicalIF":4.9,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502892","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}
{"title":"Automated Lane Change via Adaptive Interactive MPC: Human-in-the-Loop Experiments","authors":"Viranjan Bhattacharyya;Ardalan Vahidi","doi":"10.1109/TCST.2024.3478028","DOIUrl":"https://doi.org/10.1109/TCST.2024.3478028","url":null,"abstract":"This article presents a new optimal control-based interactive motion planning algorithm for an autonomous vehicle interacting with a human-driven vehicle. The ego vehicle solves a joint optimization problem for its motion planning involving costs and coupled constraints of both vehicles and applies its own actions. The nonconvex feasible region and lane discipline are handled by introducing integer decision variables and the resulting optimization problem is a mixed-integer quadratic program (MIQP) which is implemented via model predictive control (MPC). Furthermore, the ego vehicle imputes the cost of human-driven neighboring vehicle (NV) using an inverse optimal control method based on Karush-Kuhn–Tucker (KKT) conditions and adapts the joint optimization cost accordingly. We call the algorithm adaptive interactive mixed-integer MPC (aiMPC). Its interaction with human subjects driving the NV in a mandatory lane change (MLC) scenario is tested in a developed software-and-human-in-the-loop simulator. Results show the effectiveness of the presented algorithm in terms of enhanced mobility of both vehicles compared to baseline methods.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1246-1257"},"PeriodicalIF":4.9,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502814","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}
{"title":"Automated Lane Merging via Game Theory and Branch Model Predictive Control","authors":"Luyao Zhang;Shaohang Han;Sergio Grammatico","doi":"10.1109/TCST.2024.3477354","DOIUrl":"https://doi.org/10.1109/TCST.2024.3477354","url":null,"abstract":"We propose an integrated behavior and motion planning framework for the lane-merging problem. The behavior planner combines search-based planning with game theory to model vehicle interactions and plan multivehicle trajectories. Inspired by human drivers, we model the lane-merging problem as a gap selection process and determine the appropriate gap by solving a matrix game. Moreover, we introduce a branch model predictive control (BMPC) framework to account for the uncertain equilibrium strategies adopted by the surrounding vehicles, including Nash and Stackelberg strategies. A tailored numerical solver is developed to enhance computational efficiency by exploiting the tree structure inherent in BMPC. Finally, we validate our proposed integrated planner using real traffic data and demonstrate its effectiveness in handling interactions in dense traffic scenarios.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1258-1269"},"PeriodicalIF":4.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501032","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}
{"title":"Trust-Aware Safe Control for Autonomous Navigation: Estimation of System-to-Human Trust for Trust-Adaptive Control Barrier Functions","authors":"Saad Ejaz;Masaki Inoue","doi":"10.1109/TCST.2024.3470533","DOIUrl":"https://doi.org/10.1109/TCST.2024.3470533","url":null,"abstract":"A trust-aware safe control system for autonomous navigation in the presence of humans, specifically pedestrians, is presented. The system combines model predictive control (MPC) with control barrier functions (CBFs) and system-to-human trust (SHT) estimation to ensure safe and reliable navigation in human-populated environments. In the context of this article, we refer to SHT as the confidence score that a system has in an agent/pedestrian’s attentiveness. Pedestrian SHT values are computed based on features, extracted from camera sensor images, such as mutual eye contact, smartphone usage, and pose fluctuations and are integrated into the MPC controller’s CBF constraints, allowing the autonomous vehicle to make informed decisions considering pedestrian behavior. Simulations conducted in the CARLA driving simulator demonstrate the feasibility and effectiveness of the proposed system, showcasing more conservative behavior around inattentive pedestrians and vice versa. The results highlight the practicality of the system in real-world applications, providing a promising approach to enhance the safety and efficiency of autonomous navigation systems, especially self-driving vehicles.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1151-1163"},"PeriodicalIF":4.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502894","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}
{"title":"Fast Sparse Dynamic Matrix Estimation Method With Differential Information for Industrial Process Monitoring","authors":"Mingliang Cui;Xin Ma;Youqing Wang;Jipeng Guo;Tongze Hou","doi":"10.1109/TCST.2024.3483431","DOIUrl":"https://doi.org/10.1109/TCST.2024.3483431","url":null,"abstract":"With increasing complexity of industrial processes, a number of variables are becoming increasingly large in modeling and monitoring steps, which is particularly prominent in dynamic processes. To address the issue of information redundancy in dynamic processes, this study proposes a sparse dynamic matrix estimation method (SDMEM) based on joint sparse constraints, which can effectively remove the irrelevant process variables and implement a more flexible structure for a dynamic process. Accordingly, the problem that dynamic features are difficult to extract owing to the high sampling rate is effectively solved by introducing differential information. Furthermore, a fast iterative optimization algorithm is designed for the proposed SDMEM with differential information (SDMEM-DI). A theoretical analysis shows the superiority of the proposed optimization algorithm in reducing computational complexity. Finally, experiments are conducted on a numerical example, a continuous stirred tank reactor (CSTR), and a catalytic cracking unit data of a refining and chemical plant, and the results show the effectiveness of the proposed SDMEM-DI.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"512-525"},"PeriodicalIF":4.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489087","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}
{"title":"Event-Triggered Protocol-Based Control for Cyber–Physical Systems Vulnerable to Dual-Channel DoS Attacks","authors":"Xiaohang Li;Zhaoyang Tian;Dunke Lu","doi":"10.1109/TCST.2024.3477936","DOIUrl":"https://doi.org/10.1109/TCST.2024.3477936","url":null,"abstract":"This article proposes a dynamic event-triggered protocol (ETP)-based controller for a quadruple-tank model to defend against dual-channel denial-of-service (DoS) attacks. Such an attack may inflict serious damage on two communication channels: the sampler-to-controller (STC) and controller-to-actuator (CTA) channels. To reduce bandwidth occupation and energy consumption, a dynamic ETP (DETP) is introduced in the control scheme, which shows resilience against dual-channel attacks. Based on the proposed protocol, a resilient controller with three formulations in view of the occurrences of attacks is codesigned by using triggered data to mitigate the dual-channel DoS attacks and ensure good response characteristics. The designed controller can be proven to make the resultant closed-loop system robustly and asymptotically stable, respectively, by using a piecewise Lyapunov functional method. Simulation results have verified the effectiveness of the proposed control strategy.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"369-383"},"PeriodicalIF":4.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912527","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}
{"title":"Enhancing Accuracy of Finite-Dimensional Models for Lithium-Ion Batteries, Observer Design, and Experimental Validation","authors":"Mira Khalil;Romain Postoyan;Stéphane Raël","doi":"10.1109/TCST.2024.3473769","DOIUrl":"https://doi.org/10.1109/TCST.2024.3473769","url":null,"abstract":"Accurate estimation of the internal states of lithium-ion batteries is key toward improving their management for safety, efficiency, and longevity purposes. Various approaches exist in the literature in this context, among which is designing an observer based on an electrochemical model of the battery dynamics. With this approach, the performance of the observer depends on the accuracy of the considered model. It appears that electrochemical models, and thus their associated observers, typically require to be of high dimension to generate accurate internal variables. In this work, we present a method to mitigate this limitation by correcting the lithium concentrations generated by a general class of finite-dimensional electrochemical models such that they asymptotically match those generated by the original partial differential equations (PDEs) they are based on, for constant input currents. These corrections apply to finite-dimensional models of any order of the considered class. The proposed corrections lead to a new state-space model for which we design observers, whose global, robust convergences are supported by a Lyapunov analysis. Both numerical and experimental validations are presented, which show the improvement of the accuracy of the state estimates as a result of the proposed corrections.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"327-342"},"PeriodicalIF":4.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905839","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}
{"title":"Optimizing Urban Mobility for Saving Lives and Economy During an Epidemic Outbreak, With Application to Grenoble","authors":"Ujjwal Pratap;Carlos Canudas-de-Wit;Federica Garin","doi":"10.1109/TCST.2024.3477990","DOIUrl":"https://doi.org/10.1109/TCST.2024.3477990","url":null,"abstract":"This article addresses the problem of controlling human mobility in order to mitigate an epidemic in a city. We consider a discrete-time human mobility model that captures daily mobility pattern between residences and different destinations in a city and also incorporates epidemic spread at each location. For this city-wide model, we provide techniques to compute optimal mobility control policies, which tune the operating capacities of different destinations depending on their type. To obtain this kind of policies, we solve an optimization problem that takes into account the current epidemic status and maximizes the socioeconomic activity while keeping the total infections below a desired threshold. The proposed solution techniques use an outer approximation method, thanks to the monotonic nature the problem, and a receding-horizon approach. We apply these techniques to the mobility network of Grenoble metropolitan area.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"288-303"},"PeriodicalIF":4.9,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905747","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}