IEEE Transactions on Control Systems Technology最新文献

{"title":"Real-Time Ground Fault Detection for Inverter-Based Microgrid Systems","authors":"Jingwei Dong;Yucheng Liao;Haiwei Xie;Jochen Cremer;Peyman Mohajerin Esfahani","doi":"10.1109/TCST.2024.3458467","DOIUrl":"https://doi.org/10.1109/TCST.2024.3458467","url":null,"abstract":"Ground fault detection in inverter-based microgrid (IBM) systems is challenging, particularly in a real-time setting, as the fault current deviates slightly from the nominal value. This difficulty is reinforced when there are partially decoupled disturbances and modeling uncertainties. The conventional solution of installing more relays to obtain additional measurements is costly and also increases the complexity of the system. In this brief, we propose a data-assisted diagnosis scheme based on an optimization-based fault detection filter with the output current as the only measurement. Modeling the microgrid dynamics and the diagnosis filter, we formulate the filter design as a quadratic programming (QP) problem that accounts for decoupling partial disturbances, robustness to nondecoupled disturbances and modeling uncertainties by training with data, and ensuring fault sensitivity simultaneously. To ease the computational effort, we also provide an approximate but analytical solution to this QP. Additionally, we use classical statistical results to provide a thresholding mechanism that enjoys probabilistic false-alarm guarantees. Finally, we implement the IBM system with Simulink and real-time digital simulator (RTDS) to verify the effectiveness of the proposed method through simulations.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"392-399"},"PeriodicalIF":4.9,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912577","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":"Interaction-Aware Traffic Prediction and Scenario-Based Model Predictive Control for Autonomous Vehicles on Highways","authors":"Xiaorong Zhang;Sahar Zeinali;Georg Schildbach","doi":"10.1109/TCST.2024.3458817","DOIUrl":"https://doi.org/10.1109/TCST.2024.3458817","url":null,"abstract":"This article addresses the problem of traffic prediction and control of autonomous vehicles on highways. An interacting multiple model Kalman filter (IMM-KF)-related algorithm is applied to predict the motion behavior of the traffic participants by considering their interactions. A scenario generation component is used to produce plausible scenarios of the vehicles. A novel integrated decision-making and control system is proposed by applying a scenario-based model predictive control (MPC) approach. The designed controller considers safety, driving comfort, and traffic rules. The recursive feasibility of the controller is guaranteed under the inclusion of the “worst case” as an additional scenario to obtain safe inputs. Finally, the proposed scheme is evaluated under a high-fidelity IPG CarMaker and Simulink co-simulation environment. Simulation results indicate that the vehicle performs safe maneuvers under the designed control framework in different traffic situations.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1235-1245"},"PeriodicalIF":4.9,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502915","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":"Predictive Control for Autonomous Driving With Uncertain, Multimodal Predictions","authors":"Siddharth H. Nair;Hotae Lee;Eunhyek Joa;Yan Wang;H. Eric Tseng;Francesco Borrelli","doi":"10.1109/TCST.2024.3451370","DOIUrl":"10.1109/TCST.2024.3451370","url":null,"abstract":"We propose a stochastic model predictive control (SMPC) formulation for path planning with autonomous vehicles in scenarios involving multiple agents with multimodal predictions. The multimodal predictions capture the uncertainty of urban driving in distinct modes/maneuvers (e.g., yield and keep speed) and driving trajectories (e.g., speed and turning radius), which are incorporated for multimodal collision avoidance chance constraints for path planning. In the presence of multimodal uncertainties, it is challenging to reliably compute feasible path planning solutions at real-time frequencies (<inline-formula> <tex-math>${geq }10~mathrm {Hz}$ </tex-math></inline-formula>). Our main technological contribution is a convex SMPC formulation that simultaneously 1) optimizes over parameterized feedback policies and 2) allocates risk levels for each mode of the prediction. The use of feedback policies and risk allocation enhances the feasibility and performance of the SMPC formulation against multimodal predictions with large uncertainty. We evaluate our approach via simulations and road experiments with a full-scale vehicle interacting in closed loop with virtual vehicles. We consider distinct, multimodal driving scenarios: 1) negotiating a traffic light (TL) and a fast, tailgating agent; 2) executing an unprotected left turn at a traffic intersection; and 3) changing lanes in the presence of multiple agents. For all these scenarios, our approach reliably computes multimodal solutions to the path-planning problem at real-time frequencies.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1178-1192"},"PeriodicalIF":4.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142250991","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":"High-Speed Interception Multicopter Control by Image-Based Visual Servoing","authors":"Kun Yang;Chenggang Bai;Zhikun She;Quan Quan","doi":"10.1109/TCST.2024.3451293","DOIUrl":"10.1109/TCST.2024.3451293","url":null,"abstract":"In recent years, reports of illegal drones threatening public safety have increased. For the invasion of fully autonomous drones, traditional methods, such as radio frequency interference and GPS shielding, may fail. This article proposes a scheme that uses an autonomous multicopter with a strapdown camera to intercept a maneuvering intruder unmanned aerial vehicle (UAV). The interceptor multicopter can autonomously detect and intercept intruders moving at high speed in the air. The strapdown camera avoids the complex mechanical structure of the electro-optical pod, making the interceptor multicopter compact. However, the coupling of the camera and multicopter motion makes interception tasks difficult. To solve this problem, an image-based visual servoing (IBVS) controller is proposed to make the interception fast and accurate. Then, in response to the time delay of sensor imaging and image processing relative to attitude changes in high-speed scenarios, a delayed Kalman filter (DKF) observer is generalized to predict the current image position and increase the update frequency. Finally, hardware-in-the-loop (HITL) simulations and outdoor flight experiments verify that this method has a high interception accuracy and success rate. In the flight experiments, a high-speed interception is achieved with a terminal speed of 20m/s.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"119-135"},"PeriodicalIF":4.9,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219175","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":"Real-Time Mixed-Integer Quadratic Programming for Vehicle Decision-Making and Motion Planning","authors":"Rien Quirynen;Sleiman Safaoui;Stefano Di Cairano","doi":"10.1109/TCST.2024.3449703","DOIUrl":"10.1109/TCST.2024.3449703","url":null,"abstract":"We develop a real-time feasible mixed-integer programming-based decision-making (MIP-DM) system for automated driving (AD). Using a linear vehicle model in a road-aligned coordinate frame, the lane change constraints, collision avoidance, and traffic rules can be formulated as mixed-integer inequalities, resulting in a mixed-integer quadratic program (MIQP). The proposed MIP-DM performs maneuver selection and trajectory generation by solving the MIQP at each sampling instant. While solving MIQPs in real time has been considered intractable in the past, we show that our recently developed solver \u0000<monospace>BB-ASIPM</monospace>\u0000 is capable of solving MIP-DM problems on embedded hardware in real time. The performance of this approach is illustrated in simulations in various scenarios, including merging points and traffic intersections, and hardware-in-the-loop (HIL) simulations in dSPACE Scalexio and MicroAutoBox-III (MABX-III). Finally, we show experiments using small-scale vehicles.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"77-91"},"PeriodicalIF":4.9,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219176","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":"Hierarchical Control for Vehicle Repositioning in Autonomous Mobility-on-Demand Systems","authors":"Pengbo Zhu;Giancarlo Ferrari-Trecate;Nikolas Geroliminis","doi":"10.1109/TCST.2024.3448300","DOIUrl":"10.1109/TCST.2024.3448300","url":null,"abstract":"Balancing passenger demand and vehicle availability is crucial for ensuring the sustainability and effectiveness of urban transportation systems. To address this challenge, we propose a novel hierarchical strategy for the efficient distribution of empty vehicles in urban areas. The proposed approach employs a data-enabled predictive control (DeePC) algorithm to develop a high-level controller, which guides the inter-regional allocation of idle vehicles. This algorithm utilizes historical data on passenger demand and vehicle supply in each region to construct a nonparametric representation of the system, enabling it to determine the optimal number of vehicles to be repositioned or retained in their current regions without modeling the system. At the low level, a coverage control-based controller is designed to provide inter-regional position guidance, determining the desired road intersection each vehicle should target. With the objective of optimizing area coverage, it aligns the vehicle distribution with the demand across different districts within a single region. The effectiveness of the proposed method is validated through simulation experiments on the real road network of Shenzhen, China. The integration of the two layers provides better performance compared to applying either layer in isolation, demonstrating its potential to reduce passenger waiting time and answer more requests, thus promoting the development of more efficient and sustainable transportation systems.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1463-1476"},"PeriodicalIF":4.9,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219177","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":"Sharable Clothoid-Based Continuous Motion Planning for Connected Automated Vehicles","authors":"Sanghoon Oh;Qi Chen;H. Eric Tseng;Gaurav Pandey;Gábor Orosz","doi":"10.1109/TCST.2024.3448328","DOIUrl":"10.1109/TCST.2024.3448328","url":null,"abstract":"A continuous motion planning method for connected automated vehicles (CAVs) is considered for generating feasible trajectories in real-time using three consecutive clothoids. The proposed method reduces path planning to a small set of nonlinear algebraic equations such that the generated path can be efficiently checked for feasibility and collision. After path planning, velocity planning is executed while maintaining a parallel simple structure. Key strengths of this framework include its interpretability, shareability, and ability to specify boundary conditions. Its interpretability and shareability stem from the succinct representation of the resulting local motion plan using a handful of physically meaningful parameters. Vehicles may share these parameters via vehicle-to-everything (V2X) communication so that the recipients can precisely reconstruct the planned trajectory of the senders and respond accordingly. The proposed local planner guarantees the satisfaction of boundary conditions, thus ensuring seamless integration with a wide array of higher-level global motion planners. The tunable nature of the method enables tailoring the local plans to specific maneuvers like turns at intersections, lane changes, and U-turns.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1372-1386"},"PeriodicalIF":4.9,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219179","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":"Single Intersection MPC Traffic Signal Control in Presence of Automated Vehicles","authors":"Francesco Liberati;Manuel Donsante;Andrea Tortorelli","doi":"10.1109/TCST.2024.3449188","DOIUrl":"10.1109/TCST.2024.3449188","url":null,"abstract":"This article presents a model predictive control (MPC) approach for the management of traffic lights (TLs) at a single road intersection. The proposed controller incorporates a microscopic traffic model, capturing the position, velocity, and acceleration of every single vehicle at the intersection. This allows us to achieve a detailed modeling of the dynamics of the queues. The proposed controller can adapt to work in scenarios that go from one in which vehicles are manually controlled by the drivers, to one in which some or all of the vehicles are automatically driven. In the former scenario, the dynamics of the vehicles’ variables are intended to mimic the drivers’ behavior, in the latter ones (i.e., semi or fully autonomous driving), vehicles’ variables are references to the automated vehicles, sent by the TL controller. Numerical simulations on a real intersection with realistic traffic characteristics are discussed and results in the scenarios from the manual one to the fully automated one are compared, evaluating the performance in terms of queue length and waiting times. It is shown how the proposed controller can significantly improve the management of the intersection, leading to less traffic.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1432-1446"},"PeriodicalIF":4.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219178","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":"Joint Estimation and Planar Affine Formation Control With Displacement Measurements","authors":"Qingkai Yang;Xiaozhen Zhang;Hao Fang;Ming Cao;Jie Chen","doi":"10.1109/TCST.2024.3449008","DOIUrl":"10.1109/TCST.2024.3449008","url":null,"abstract":"This article investigates the problem of planar affine formation maneuver control with a matrix-valued formation shape variation parameter. The matrix representation renders full degree of freedom (DOF) motion associated with linear mappings in the context of affine transformation. Unlike the typical leader–follower setup, where all the leaders know the prescribed formation information, only a portion of leaders are informed of the matrix parameter in this article. To achieve affine formation stabilization, two types of distributed estimators are developed for the remaining leaders to infer constant and dynamic matrix parameters, utilizing only local displacement measurements. Then, we establish a joint estimation and cooperative control framework, generating corresponding formation shape changes in consistent with the matrix parameter. The system stability and precise estimation convergence are verified via both rigorous theoretical analyses and simulations with large-scale swarms. Finally, experiments conducted on the Crazyflie robots also validate the effectiveness and practicality of the proposed control approach.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"92-105"},"PeriodicalIF":4.9,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219186","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":"Control-Oriented Forecasting for Soil Moisture","authors":"Gregory Conde;Sandra M. Guzmán","doi":"10.1109/TCST.2024.3445660","DOIUrl":"10.1109/TCST.2024.3445660","url":null,"abstract":"The challenge of increasing irrigation efficiency to meet the demands of a growing population while protecting natural resources requires the contributions of multiple disciplines, including engineering, agronomical, horticultural, and environmental sciences. Specifically, automatic control can play a pivotal role in improving irrigation scheduling. In this context, incorporating real-time soil moisture (SM) forecasting in irrigation can potentially improve the efficiency of crop water management. However, the complexity of the analytical models that describe soil-water dynamics limits the development of practical and accurate solutions that include SM forecasting in decision-making. Currently, irrigation decisions are based on present and past SM data. This approach can be enhanced if, in addition to those, future or SM forecasting is incorporated. We formulated an SM model-based moving horizon estimation (MHE) and prediction strategy. For this, we propose a parametrizable blue SM control-oriented prediction model (SMCOPM) that obeys a soil-water balance. The SMCOPM is periodically parametrized using a proposed MHE approach, which provides adaptability, guarantees optimality, prevents overfitting, and ensures the water balance fulfillment and stability of the SMCOPM. The SM forecasting is performed by solving the parametrized SMCOPM as a function of rain, irrigation, and temperature forecasts. We evaluated the MHE and prediction strategy using, as a case study, observed data from a commercial sweetcorn field using subsurface irrigation in South Florida. The results show that by using this strategy, the SM can be predicted three days in advance with an average SM prediction error and a dispersion that significantly improves as the SMCOPM adapts over time, demonstrating convergence toward an error less than 2% and dispersion less than 3%. Consequently, the results corroborate the SMCOPM suitability, the proposed estimation strategy’s quality, and the SM behavior’s predictability. The proposed strategy has the potential for use in formulating predictive control approaches toward automating the irrigation process or scheduling irrigation actions.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"106-118"},"PeriodicalIF":4.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219180","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}