This study investigates the problem of event-based privacy-preserving platooning control for connected automated vehicles subject to limited communication resources and data falsification attacks. First, a novel dynamic event-triggered mechanism (DETM)-based encryption and decryption strategy is proposed to regulate the frequency of data encryption and transmission in response to real-time network bandwidth occupancy and vehicular states, thereby safeguarding data privacy while improving communication resource utilization. Then, a unified and general attack modeling method is established to characterize various forms of data falsification attacks on sensor measurements and driving commands. Building upon this, a secure observer-based platooning control protocol is derived, where the controller gains, observer parameters, and communication topology are co-designed to ensure the desired secure platooning performance while ensuring vehicular data privacy and efficient utilization of communication resources. Finally, several comparative case studies with quantified metrics are conducted to demonstrate the efficacy and merits of the proposed methods from the perspectives of platoon stability, security, communication efficiency and data privacy.

This article is concerned with the trajectory tracking problem for autonomous ground vehicles (AGVs) under unknown dynamics and external disturbances. To solve this problem, a tracking control scheme, which integrates recurrent neural network (RNN)-assisted guidance optimization and structured fuzzy uncertainty modeling, is designed. Specifically, an RNN-based velocity optimization mechanism is introduced to reshape velocity commands into smooth, bounded, and learning-friendly signals, thereby smoothing aggressive commands to improve fuzzy system convergence and approximation accuracy at the kinetic layer. Then, a structured fuzzy modeling method is developed to separately approximate state-dependent unknown dynamics and disturbance-related uncertainties, leading to more accurate modeling and enhanced robustness. Based on the optimized velocity commands and fuzzy uncertainty estimates, two kinetic control laws are developed to drive AGVs to track desired trajectories. Subsequently, two stability-oriented fuzzy weight update laws are constructed, which ensure the uniform ultimate boundedness (UUB) of the closed-loop error dynamics. Simulation and experimental results on an AGV platform demonstrate the effectiveness and practical feasibility of the proposed control scheme.

A distributed optimal double-layer formation control problem for multi-cluster systems, which has rarely been reported, is addressed in this paper. Specifically, the agents in each cluster are required to form a desired shape, while the centroids of the clusters must also adhere to a specified geometric pattern. Beyond this double layer formation task, the agents are faced with a global optimization problem, which should be resolved concurrently. The paper mainly faces the following challenges: (1) how to deal with both inter-cluster and intra-cluster formation problems; (2) how to simultaneously achieve the double-layer formation control and global optimization; (3) how to estimate the averaged state of each cluster, which is unknown to all agents. To achieve optimal double-layer formation control, a multi-cluster aggregative double-layer formation (MCADF) game is first formulated. Following the MCADF game formulation, an efficient broadcasting method is developed to estimate and disseminate the averaged state of each cluster. Moreover, distributed Nash equilibrium seeking strategies for multi-cluster aggregative games are established by incorporating regularization techniques, gradient algorithms, dynamic average consensus protocols and “improved” consensus tracking protocols. It is formally proven by Lyapunov stability analysis that the proposed strategies can steer agents to achieve optimal double-layer formation. Finally, a numerical simulation example on a multiple target enclosing problem is given to verify the effectiveness of the proposed method.

This paper proposes a novel secure frequency control approach for microgrids with online attack detection-based data scheduling and remedy mechanisms. First, taking into account the dynamics of photovoltaic (PV) units, energy storage systems (ESSs) and electric vehicle (EV) aggregators with state of charge (SOC)-dependent charging/discharging characteristics, a generic frequency control system model of PV-ESS-EV microgrids is established. Second, a two-step state estimation method involving a one-step-ahead state predictor and a measurement-update-based state estimator is proposed to estimate the microgrid system state, generating optimal prediction and estimation ellipsoids enclosing the true states during the whole operation time. Third, an attack detection scheme is provided for online detection of potential attacks by calculating the intersection over union (IOU) of the two generated ellipsoids. Upon successful attack detection, novel active data scheduling and two-stage data remedy mechanisms are derived for responsively reducing the negative effects of adversarial attacks. Then, a co-design approach, dependent on time-varying IOU signals, to the secure frequency controller and the scheduling mechanism parameters is presented. Finally, the efficacy and merits of the proposed frequency control strategy with attack detection-based data scheduling and remedy are verified through several case studies.

This article investigates the resilient cooperative maneuvering problem for a group of electric mobile robots (EMRs) subject to falsified motor inputs. A comprehensive EMR dynamic model is first established by explicitly incorporating direct current (dc)-motor characteristics and pulse-width modulation (PWM)-based actuation mechanisms, which enables accurate modeling of low-level motor voltage manipulations. To counteract falsified inputs, a three-layer resilient cooperative control framework is proposed, consisting of: 1) a networked guidance law for kinematic coordination; 2) an adaptive torque control law for dynamic motion control; and 3) a resilient voltage control law for motor voltage regulation and compensation. Rigorous Lyapunov-based analysis proves the stability of the resulting closed-loop system. At last, both simulation and experimental results demonstrate that the proposed control framework reduces trajectory tracking errors by more than 20%-75% under voltage falsification attacks, ensuring accurate formation maintenance.

This paper studies the problem of distributed cooperative control of connected and automated vehicles (CAVs) in the presence of denial-of-service (DoS) attacks in open environments, where vehicles can perform joining and leaving maneuvers freely in the platoon. First, inspired by the framework of switched systems feature multi-mode and multi-dimensional, the characteristic of platoon maneuvers is described by a switching communication topology. The framework allows for concurrent changes in both the number of vehicles and the topology graph at switching instants caused by joining/leaving of vehicles and DoS attacks. Besides, a full-order distributed observer is designed for each follower vehicle to observe its states. Second, a distributed platooning controller suitable for such a dynamic environment is constructed for effective and secure cooperative vehicle tracking control with the exponential convergence of relative positions and velocities to the leader. Finally, numerical simulations are presented to demonstrate the effectiveness of the theoretical results and merits of the proposed cooperative control design approach on maintaining the desired platooning performance.

This paper investigates distributed platooning control of connected and autonomous vehicles (CAVs) under practical spacing policies with vehicular data privacy protection. A practical spacing policy is first designed to adaptively regulate inter-vehicle distances by incorporating real-time traffic flow variations, road friction conditions, and safety distance requirements. The resulting spacing-policy-induced uncertainties are then addressed through an augmented system-based estimation approach. To safeguard vehicular privacy, a differential privacy-enhanced encoding-decoding mechanism is developed, enabling protection of both initial vehicular state information and broadcast vehicular data against eavesdropping attacks. Upon that, a co-design strategy is further proposed to jointly synthesize the privacy protection scheme, estimator, and distributed controller, ensuring reliable platoon tracking performance with data confidentiality. Finally, comparative case studies are conducted to validate the enhanced platoon tracking stability, driving safety, and privacy preservation in realistic traffic scenarios.

Current sharing and voltage regulation in multi-bus DC microgrids are two fundamental control objectives, between which there is a tradeoff due to their conflicting nature. Different from the existing literature, this paper focuses on distributed accurate proportional current sharing with the minimization of voltage regulation deviations in multi-bus DC microgrids. First, a novel game-theoretic framework is established, where each bus node in the DC microgrid acts as a player and the problem of proportional current sharing and voltage regulation can be reformulated as a Nash equilibrium seeking problem. Then, based on the formulated game, a new regularization-based distributed least-norm Nash equilibrium seeking strategy is proposed, which incorporates a gradient-based algorithm, a leader-following consensus algorithm and a dynamic average consensus algorithm. It is demonstrated that the proposed strategy can ensure accurate proportional current sharing while minimizing the deviations of all bus voltage regulation. In the end, the efficacy of the proposed strategy is validated through several case studies on a six-bus DC microgrid system, in terms of performance evaluation, robustness to load variations and communication failures, and plug-and-play ability.

This paper proposes a distributed event-based two-level model predictive control (EMPC-2L) strategy for heterogeneous electric vehicle (EV) platoons, enhancing both energy economy and communication resource efficiency. First, a two-level architecture is developed, where the upper level performs receding-horizon optimization at the leader vehicle to minimize the total energy consumption of the platoon, while the lower level enables follower vehicles to cooperatively perform local predictive control based on the leader's trajectory. Second, an event-triggered mechanism is designed to jointly determine the triggering of communication and optimization computation for follower vehicles, adapting dynamically to realtime resource occupancy to reduce unnecessary updates. Third, an event-based predictive control scheme is formulated to ensure the platoon stability and control performance with enhanced energy economy and resource efficiency. Comparative simulation results validates that the proposed EMPC-2L strategy significantly improves energy efficiency, reduces communication and computation load while enhances ride comfort in EV platoon driving.

A co-monitoring problem of state of charge (SOC) and state of health (SOH) under resource-constrained and insecure communication is addressed in this paper. First, an SOC/SOH co-monitoring framework is established to account for battery SOC and SOH dynamics, unknown-but-bounded (UBB) process and measurement noises, dual coupled monitors, and intermittent measurement updates at multi-time scales. Second, a resource-efficient communication mechanism is proposed for determining the measurement updates according to not only the measurement variations but also the realtime network conditions, realizing reasonable utilization of constrained and time-varying communication resources. Third, dual coupled monitors are developed based on state predictors and estimators for SOC/SOH co-monitoring, which provide prediction and estimation ellipsoids enclosing the true states of SOC/SOH dynamics at all times. Then, encountering potential attacks, attack detection strategies are derived by calculating the intersection over union (IOU) of the prediction and estimation ellipsoids. Upon occurrences of attacks, a compensation mechanism is presented to replace the contaminated measurement-based state estimates by the attack influence-free predicted states, suppressing the adverse effects of attacks. Finally, comparative case studies are carried out to verify the efficacy and merit of the proposed methods.

This paper presents a dynamic event-triggered distributed model predictive control (DMPC) strategy for heterogeneous vehicle platoons subject to disturbances and input constraints. A dynamic event-triggered mechanism considering bandwidth occupancy status integrated with a dual-mode control method is utilized to determine not only whether the optimal control problem should be solved or not but also the data transmission actions at each sampling time instant for each vehicle. In such a context, a dynamic event-triggered dual-mode DMPC algorithm is proposed to ensure the desired platooning control performance as well as the effective reduction of computational and communication loads. Building upon that, formal feasibility and stability analyses are correspondingly conducted, which provide theoretical validation for the proposed dynamic event-triggered DMPC strategy. Finally, a specific simulation example is given to demonstrate the efficacy of the proposed algorithm in terms of platooning control performance and communication resource efficiency.

Based on the consensus theory of multi-agent systems (MAS), this article proposes a distributed fixed-time control strategy for heterogeneous battery energy storage systems (BESSs) in droop-controlled microgrids. The droop control of microgrids creates frequency deviations from the target value, leading to decreased accuracy of power sharing and frequency. A fixed time secondary control method is proposed to address the deviations arising from the primary control as well as to achieve the objectives of frequency regulation, active power sharing, and energy level balancing within a fixed timeframe. Additionally, the fixed-time control approach can provide an explicit estimate of the settling time without any dependence on the initial conditions. With the foundation of theoretical analyses, the consistency and convergence of the control algorithms are clearly revealed. Eventually, the suggested control strategy is validated by conducting case studies using a modified IEEE 34-bus testing system implemented in MATLAB.

This paper addresses the problem of communication resource-efficient secondary frequency regulation of power grids under vehicle-to-grid supplementary service. First, an event-based frequency regulation framework is established for power grids incorporated with electric vehicle (EV) participation, enabling system performance analysis and control design under event-based communication. The framework also takes into account the EV aggregator dynamics with battery charging/discharging processes under practical travel demands. Second, a novel resource-efficient event-based broadcast mechanism (REBM) is developed for intelligent transmissions of command signals from the dispatch center to the power plant and distributed EV aggregators. By deciding the broadcast actions with the particular consideration of the real-time bandwidth occupancy, the designed REBM is capable to flexibly adapt the command transmission rate to variable network status. Then, a co-design approach to the desired REBM and frequency controller is derived, based on which an implementation algorithm is provided for achieving satisfying secondary frequency regulation performance with enhanced communication efficiency. Finally, the efficacy of the proposed approach is verified through comparative case studies.

Dear Editor, This letter addresses the resilient distributed cooperative control problem of a virtually coupled train convoy under stochastic disturbances and cyber attacks. The main purpose is to achieve distributed coordination of virtually coupled high-speed trains with the prescribed inter-train distance and same cruise velocity, while preserving driving security of the train convoy against a class of topological attacks. First, a resilient distributed cooperative control framework of the virtually coupled train convoy is established, which incorporates the longitudinal train dynamics, stochastic disturbances, and topological attacks on inter-train information flows. Building on that, a distributed cooperative control protocol and a topology reconfiguration algorithm are designed for attack-resilient train convoy tracking. Furthermore, a formal stability analysis is performed for the exponential convergence of the convoy tracking errors. Finally, a numerical case study on a 56 km-line segment of a real-world high-speed railway is carried out to validate the efficacy of our results.

This paper porposes a distributed average integral (DAI) algorithm based on event-triggering for secondary frequency control in microgrids. Initially, the study considers a heterogeneous microgrid consisting of synchronous generators, droop-controlled inverters, and loads. The objective is to ensure zero frequency deviations for all nodes in the grid and the prescribed allocation of active power. Subsequently, in order to significantly reduce communication utilization, a DAI algorithm based on periodic sampling event-triggering is proposed, with data exchange occurring exclusively when predefined triggering conditions are violated. Furthermore, the stability of the closed-loop system is analyzed, based on which the sufficient conditions for consensus of system states are derived. Finally, simulation experiments are conducted on Kundur’s two-area four-machine test system. Through simulation verification, it demonstrates that the proposed event-triggered DAI algorithm is capable of realizing good performance in secondary frequency control while significantly reducing the utilization of communication resources.

The paper investigates the problem of distributed vehicular platooning control under the premise of privacy preservation. First, an encryption-decryption scheme is introduced to secure the data transmitted among vehicles, preventing potential external breaches that might compromise the confidentiality of the original vehicular data, thereby enhancing the privacy and security of vehicle interactions. Second, an event-triggered mechanism is utilized to enable data exchanges among vehicles only when specific conditions are met. The employment of such event triggering significantly reduces the utilization of communication resources, thereby improving communication efficiency. Then, a distributed platooning control strategy is proposed to ensure that each vehicle within the platoon achieves the desired tracking performance. Finally, stability analysis of the closed-loop event-triggered encryption-decryption platooning control system is conducted. The feasibility and the efficacy of the control strategy are demonstrated through a specific numerical example.

This paper is concerned with the event-based coordinated cruise control problem of multiple high-speed trains under sporadic train-to-train (T2T) information flows. First, a novel bandwidth occupancy-aware event-based communication mechanism is devised to schedule T2T information exchanges. Two salient features of the mechanism lie in the awareness of the real-time bandwidth occupancy and the inclusion of the historically transmitted train data in determining the communication events. In this way, the limited communication resource can be occupied in a more intelligent and flexible manner. Then, a bandwidth parameter-dependent co-design approach is proposed for each train to determine the desired cruise controller gains and event scheduler parameters. Furthermore, it is shown that under the designed cruise controllers, the follower trains can maintain the desired gap reference from their predecessors and keep the same speed profile with the leader train, while simultaneously realizing promising communication resource efficiency. Finally, several case studies are performed to validate the efficacy of the co-design approach.

This paper deals with the co-design problem of event-triggered communication scheduling and platooning control over vehicular ad-hoc networks (VANETs) subject to finite communication resource. First, a unified model is presented to describe the coordinated platoon behavior of leader-follower vehicles in the simultaneous presence of unknown external disturbances and an unknown leader control input. Under such a platoon model, the central aim is to achieve robust platoon formation tracking with desired inter-vehicle spacing and same velocities and accelerations guided by the leader, while attaining improved communication efficiency. Toward this aim, a novel bandwidth-aware dynamic event-triggered scheduling mechanism is developed. One salient feature of the scheduling mechanism is that the threshold parameter in the triggering law is dynamically adjusted over time based on both vehicular state variations and bandwidth status. Then, a sufficient condition for platoon control system stability and performance analysis as well as a co-design criterion of the admissible event-triggered platooning control law and the desired scheduling mechanism are derived. Finally, simulation results are provided to substantiate the effectiveness and merits of the proposed co-design approach for guaranteeing a trade-off between robust platooning control performance and communication efficiency.

This paper is concerned with the design problem of distributed cooperative longitudinal controller and communication topology for automated vehicle platoons subject to heterogenous and uncertain longitudinal dynamics. The main objective is to achieve automated vehicle platooning with desired spacing, same velocity/acceleration, and platoon robustness against uncertainties, while simultaneously incorporating appropriate topology synthesis. For this purpose, a scalable co-design approach is developed, whose salient features include that 1) local state observers are constructed for each platoon vehicle such that only raw vehicular position measurements are demanded; 2) the platoon controllers are capable to accommodate generic communication topologies and various spacing policies; 3) the design criteria on the existence of local state observers and platoon controllers can be verified in a fully offline manner and without requiring any global information regarding the communication topology or platoon scale, which means that the co-design is potentially implementable for practical platooning with a large scale and dynamic lengths; 4) a criterion on the topology link weight selections is established to provide an insight into the effects of the link weights on the platoon control performance. Finally, numerical simulations are given to substantiate the efficacy of the proposed co-design approach.

This paper addresses the secure and safe distributed cooperative control problem of multiple platoons of automated vehicles under unknown data falsification attacks on driving commands. First, a general multi-platoon control framework is developed, which accommodates longitudinal and lateral vehicle dynamics, inter- and intra-platoon information exchanges, falsified driving commands, and unknown external disturbances. To deal with the unknown falsified driving commands on the platoon performance, a neural-network-based adaptive control strategy is developed to compensate their adverse effects. In order to avert both longitudinal and lateral collisions under various maneuvering scenarios, a built-in avoidance mechanism is then designed for each platoon vehicle. Furthermore, a secure and anti-collision multi-platoon control design approach is proposed to ensure the desired inter- and intra-platoon tracking performance with a collision-free guarantee. It is formally proved that the inter- and intra-platoon tracking errors converge to small neighborhood around zero. Finally, several comparative simulation cases are presented to verify the effectiveness and merits of the proposed multi-platoon control approach.