IEEE Transactions on Control Systems Technology最新文献

{"title":"Invariant Set Planning for Quadrotors: Design, Analysis, Experiments","authors":"Marcus Greiff;Himani Sinhmar;Avishai Weiss;Karl Berntorp;Stefano Di Cairano","doi":"10.1109/TCST.2024.3492813","DOIUrl":"https://doi.org/10.1109/TCST.2024.3492813","url":null,"abstract":"We propose a motion planner for quadrotor unmanned aerial vehicles (UAVs) implemented as a graph search over robust positive invariant (PI) sets. We model the positional error dynamics of the quadrotor in closed loop with an onboard controller as a second-order system with polytopic uncertainty in the gains. We also consider bounded attitude tracking errors and additive input disturbances. We propose a method for computing ellipsoidal robust PI (RPI) sets using linear matrix inequalities that are expanded such that all trajectories therein remain safe, i.e., do not intersect obstacles and ensure satisfaction of UAV constraints. We construct a graph where the vertices are equilibrium positions and the edges are transitions between equilibria occurring within the PI sets. Hence, a graph search returns a sequence of setpoints steering the UAV from an initial position to a target, while remaining within the safe invariant sets. We show that subject to the properties of the graph, from any initial position within an invariant set, any RPI set in the graph is reachable in finite time. The graph construction is offline, and the online graph search and plan execution are simple and fast, thus allowing for real-time planning. We demonstrate the method in extensive simulations and in experiments with a Crazyflie 2.1 quadrotor.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"449-462"},"PeriodicalIF":4.9,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489060","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":"Optimal Performance Guaranteed Motion Control for Libration Point Orbit Rendezvous: A Semianalytical Predictive Approach","authors":"Caisheng Wei;Guanhua Huang;Zeyang Yin;Biao Luo;Yong Xu","doi":"10.1109/TCST.2024.3492795","DOIUrl":"https://doi.org/10.1109/TCST.2024.3492795","url":null,"abstract":"In light of the importance of libration point orbits (LPOs) in deep space explorations, a highly reliable and precise position control method is required to guarantee safety and effectiveness during spacecraft proximity and rendezvous operations. Different from the existing works, this article investigates a novel semianalytical optimal performance guaranteed control approach for LPO rendezvous subject to actuator saturation. First, the unified error transformation technique is applied to remove the performance constraints quantitatively characterizing the transient and static responses of the LPO motion dynamics. Then, an explicit receding horizon predictive control strategy with guaranteed prescribed performance is devised by exploiting sequential action control structure under actuator saturation. Accordingly, a syncretic iterative control action sequence is developed based on the two controllers designed earlier. Compared with the existing methods, the major merit of the proposed one lies in that the optimal control efficiency of the motion tracking performance is improved dramatically with a low-complexity computation burden. Finally, three groups of illustrative examples are employed to validate the effectiveness of the proposed control method.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"629-642"},"PeriodicalIF":4.9,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489110","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":"2023-2024 Index IEEE Transactions on Control Systems Technology Vol. 32","authors":"","doi":"10.1109/TCST.2024.3495392","DOIUrl":"https://doi.org/10.1109/TCST.2024.3495392","url":null,"abstract":"","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2500-2545"},"PeriodicalIF":4.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10750117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636413","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}

{"title":"SIMBa: System Identification Methods Leveraging Backpropagation","authors":"Loris Di Natale;Muhammad Zakwan;Philipp Heer;Giancarlo Ferrari-Trecate;Colin Neil Jones","doi":"10.1109/TCST.2024.3477301","DOIUrl":"https://doi.org/10.1109/TCST.2024.3477301","url":null,"abstract":"This manuscript details and extends the system identification methods leveraging the backpropagation (SIMBa) toolbox presented in previous work, which uses well-established machine learning tools for discrete-time linear multistep-ahead state-space system identification (SI). SIMBa leverages linear-matrix-inequality-based free parameterizations of Schur matrices to guarantee the stability of the identified model by design. In this article, backed up by novel free parameterizations of Schur matrices, we extend the toolbox to show how SIMBa can incorporate known sparsity patterns or true values of the state-space matrices to identify without jeopardizing stability. We extensively investigate SIMBa’s behavior when identifying diverse systems with various properties from both simulated and real-world data. Overall, we find it consistently outperforms traditional stable subspace identification methods (SIMs), and sometimes significantly, especially when enforcing desired model properties. These results hint at the potential of SIMBa to pave the way for generic structured nonlinear SI. The toolbox is open-sourced at <uri>https://github.com/Cemempamoi/simba</uri>.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"418-433"},"PeriodicalIF":4.9,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489116","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":"A Privacy-Preserving Framework for Cloud-Based HVAC Control","authors":"Zhenan Feng;Ehsan Nekouei","doi":"10.1109/TCST.2024.3487019","DOIUrl":"https://doi.org/10.1109/TCST.2024.3487019","url":null,"abstract":"The objective of this work is: 1) to develop an encrypted cloud-based heating, ventilation, and air-conditioning (HVAC) control framework to ensure the privacy of occupancy information; 2) to reduce the communication and computation costs of encrypted HVAC control; and 3) to reduce the leakage of private information via the triggering time instances in event-based encrypted HVAC control systems. Occupancy of a building is sensitive and private information that can be accurately inferred by cloud-based HVAC controllers using HVAC sensor measurements. To ensure the privacy of the occupancy information, in our framework, the sensor measurements of an HVAC system are encrypted by a fully homomorphic encryption (FHE) technique prior to communication with the cloud controller. We first develop an encrypted fast gradient algorithm that allows the cloud controller to regulate the indoor temperature and CO2 of a building by solving two model predictive control (MPC) problems using encrypted HVAC sensor measurements. We next develop an event-triggered control policy to reduce the communication and computation costs of the encrypted HVAC control. We cast the optimal design of the event-triggering policy as an optimal control problem wherein the objective is to minimize a linear combination of the control and communication costs. Using Bellman’s optimality principle, we study the structural properties of the optimal event-triggering policy and show that the optimal triggering policy is a function of the current state, the last communicated state with the cloud, and the time since the last communication with the cloud. We also show that the optimal design of the event-triggering policy can be transformed into a Markov decision process (MDP) by introducing two new states. As the triggering time instances are not encrypted, there is a risk that the cloud may use them to deduce sensitive information. To mitigate this risk, we introduce two randomized triggering strategies that reduce the leakage of private information via the triggering time instances. We finally study the performance of the developed encrypted HVAC control framework using the TRNSYS simulator. Our numerical results show that the proposed framework not only ensures efficient control of the indoor temperature and CO2 but also reduces the computation and communication costs of encrypted HVAC control by at least 60%.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"643-657"},"PeriodicalIF":4.9,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489058","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":"Recursively Feasible Chance-Constrained Model Predictive Control Under Gaussian Mixture Model Uncertainty","authors":"Kai Ren;Colin Chen;Hyeontae Sung;Heejin Ahn;Ian M. Mitchell;Maryam Kamgarpour","doi":"10.1109/TCST.2024.3477089","DOIUrl":"https://doi.org/10.1109/TCST.2024.3477089","url":null,"abstract":"We present a chance-constrained model predictive control (MPC) framework under Gaussian mixture model (GMM) uncertainty. Specifically, we consider the uncertainty that arises from predicting future behaviors of moving obstacles, which may exhibit multiple modes (for example, turning left or right). To address multimodal uncertainty distribution, we propose three MPC formulations: nominal chance-constrained planning, robust chance-constrained planning, and contingency planning. We prove that closed-loop trajectories generated by the three planners are safe. The approaches differ in conservativeness and performance guarantee. In particular, the robust chance-constrained planner is recursively feasible under certain assumptions on the propagation of prediction uncertainty. On the other hand, the contingency planner generates a less conservative closed-loop trajectory than the nominal planner. We validate our planners using state-of-the-art trajectory prediction algorithms in autonomous driving simulators.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 4","pages":"1193-1206"},"PeriodicalIF":4.9,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502816","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":"Revisiting the Optimal PMU Placement Problem in Multimachine Power Networks","authors":"Mohamad H. Kazma;Ahmad F. Taha","doi":"10.1109/TCST.2024.3487029","DOIUrl":"https://doi.org/10.1109/TCST.2024.3487029","url":null,"abstract":"To provide real-time visibility of physics-based states, phasor measurement units (PMUs) are deployed throughout power networks. PMU data enable real-time grid monitoring and control—and are essential in transitioning to smarter grids. Various considerations are taken into account when determining the geographic, optimal PMU placements (OPPs). This article focuses on the control-theoretic, observability aspect of OPP. A myriad of studies have investigated observability-based formulations to determine the OPP within a transmission network. However, they have mostly adopted a simplified representation of system dynamics, ignored basic algebraic equations that model power flows, disregarded renewables such as solar and wind, and did not model their uncertainty. Consequently, this article revisits the observability-based OPP problem by addressing the literature’s limitations. A nonlinear differential algebraic (NDAE) representation of the power system is considered. The system is discretized using various discretization approaches while explicitly accounting for uncertainty. A moving horizon estimation (MHE) approach is explored to reconstruct the joint differential and algebraic initial states of the system, as a gateway to the OPP problem, which is then formulated as a computationally tractable integer program (IP). Comprehensive numerical simulations on standard power networks are conducted to validate different aspects of this approach and test its robustness to various dynamical conditions.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"493-511"},"PeriodicalIF":4.9,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10745884","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489090","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}

{"title":"Incentive Design of Shared ESS Energy Trading Game","authors":"Jaeyeon Jo;Jihwan Yu;Jinkyoo Park","doi":"10.1109/TCST.2024.3483440","DOIUrl":"https://doi.org/10.1109/TCST.2024.3483440","url":null,"abstract":"This study introduces a hierarchical interaction model between a shared energy storage system (ESS) operator and self-interested ESS users, referred to as the shared ESS energy trading game (EET game). In the EET game, the ESS operator sets time-varying energy selling and buying prices to regulate energy trading among ESS users. Meanwhile, the ESS users make decisions regarding their energy selling (charging energy to the shared ESS) and buying (discharging energy from the shared ESS) schedules. We model the EET game as a generalized Stackelberg game (GSG) and define a generalized Stackelberg equilibrium (GSE) to identify the optimal strategies for both the ESS operator and ESS users. Within the EET game, we prove the existence of a variational Stackelberg equilibrium (VSE), which is a GSE. To compute this equilibrium, we utilize a gradient-based algorithm that incorporates an implicit gradient. Finally, we validate our model by simulation studies using residential households’ energy demand data and show the effectiveness of our approach in reducing both total energy cost (EC) and the peak-to-average ratio (PAR).","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"408-415"},"PeriodicalIF":4.9,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912566","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":"Passivity-Based Control Approach for Photovoltaic DC-DC Conversion and Output Voltage Regulation","authors":"Hayden Phillips-Brenes;Mauricio Muñoz-Arias;Roberto Pereira-Arroyo;Luis Miguel Esquivel-Sancho;Renato Rimolo-Donadio","doi":"10.1109/TCST.2024.3483094","DOIUrl":"https://doi.org/10.1109/TCST.2024.3483094","url":null,"abstract":"This article introduces a novel control approach for tackling the maximum power point tracking (MPPT) and output voltage regulation (VR) in photovoltaic (PV) cell systems. Leveraging the port-Hamiltonian (pH) formalism, an energy-based framework known for its physically multidomain modeling and control methodologies, our proposed control law offers promising solutions. Our control design is rooted in an interconnection damping assignment passivity-based strategy, incorporating temperature dependencies of the internal PV cell parameters. To validate the efficacy of our approach, we modeled, implemented, and calibrated a prototype system comprising a PV cell, a dc–dc buck converter, and a dc–dc boost converter that feeds a battery load. The entire setup is designed within the pH framework, ensuring a cohesive integration of energy-based control. To highlight our energy-based strategy’s reliability and performance, we evaluated it against a commercial solar charger under real solar irradiance conditions. Our experimental findings unequivocally demonstrate that the control mechanism employed by the commercial solar charger demands a significantly higher amount of energy and exhibits a premature collapse at lower power levels when compared to our proposed system and control strategy.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 2","pages":"479-492"},"PeriodicalIF":4.9,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489088","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":"Computationally Efficient Control for Cooperative Optical Beam Tracking With Guaranteed Finite-Time Convergence","authors":"Pratap Bhanu Solanki;Shaunak D. Bopardikar;Xiaobo Tan","doi":"10.1109/TCST.2024.3478476","DOIUrl":"https://doi.org/10.1109/TCST.2024.3478476","url":null,"abstract":"Achieving and maintaining line-of-sight (LOS) is an essential attribute for free-space optical (FSO) communication systems as the optical signals are highly directional. We consider the problem of achieving LOS between two agents in a planar setting. We model the underlying agent motion as a discrete-time dynamical system. Each agent seeks to maximize its own output (measurement) function that depends on the states (orientations) of both agents, and furthermore, the agents are required to simultaneously make their moves. Since the output functions are nonconflicting, the beam tracking problem is inherently cooperative; improving one output function concurrently optimizes the other. Nonetheless, challenges arise from the lack of communication between the agents, the absence of state information, and the requirement for simultaneous actions. We propose a novel computationally efficient output feedback control algorithm meeting all these constraints. In particular, we establish that when the level sets of the output functions satisfy certain conditions, the proposed control procedure guarantees that, in a finite number of steps, the system reaches a limiting set that contains the global optimum. The size of this limiting set is proportional to the step size. Simulation results based on an FSO communication setup demonstrate the efficacy of the approach and establish its superiority over two competing approaches, namely the classical extremum seeking control approach and an approach based on the use of an extended Kalman filter, in terms of convergence speed and robustness to disturbance. Experimental results on a setup involving two robots further validate the efficacy and quantify the proposed approach’s performance.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 1","pages":"245-260"},"PeriodicalIF":4.9,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905849","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}