Publications

treatment, and measurement of industrial processes.

Islanded microgrids face some challenges in maintaining stable frequency and sharing proper power among distributed generators (DGs) in the presence of external disturbances. This paper develops a novel fully distributed approach to achieve accelerated secondary frequency regulation (FR) and active power sharing (APS) in islanded microgrids, which enhances system performance and robustness against external disturbances. The proposed control strategy combines advanced consensus algorithms with distributed secondary control loops, eliminating the requirement for a central control unit thereby improving the scalability. Particularly, the fully distributed feature of the proposed control strategy can be understood from two aspects. On one hand, the controller itself is not using global information of (1) communication topology, such as the second smallest eigenvalue of its Laplacian matrix; and (2) the total number of DGs in the microgrid. On the other hand, the estimated settling time is independent of the aforementioned global information. Therefore, the proposed fully distributed control scheme has the potential of becoming a promising solution for the resilient and efficient management of large-scale islanded microgrids. The effectiveness of the designed controllers is validated through numerical examples, demonstrating superior performance in terms of FR, APS, and transient response under various operating conditions.

This paper studies the problems of H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance optimization and controller synthesis for discrete-time networked control systems (NCSs) with limited communication channels and data drift. By taking the non-uniform distribution characteristic of packet dropout into full consideration, and proposing the channel utilization-based switched controller, novel models for NCSs with limited communication channels and data drift are presented. A new Lyapunov functional is presented, and new bounding inequalities for cross product of vectors are also given. Then, the quantitative relationships between packet dropout probability and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance of NCSs are presented. Numerical example is given to illustrate the merits and effectiveness of the proposed methods.

This paper is concerned with a finite-time particle swarm optimization algorithm for odor source localization. First, a continuous-time finite-time particle swarm optimization (FPSO) algorithm is developed based on the continuous-time model of the particle swarm optimization (PSO) algorithm. Since the introduction of a nonlinear damping item, the proposed continuous-time FPSO algorithm can converge over a finite-time interval. Furthermore, in order to enhance its exploration capability, a tuning parameter is introduced into the proposed continuous-time FPSO algorithm. The algorithm’s finite-time convergence is analyzed by using the Lyapunov approach. Second, the discrete-time FPSO algorithm is obtained by using a given dicretization scheme. The corresponding convergence condition is derived by using a linear matrix inequality (LMI) approach. Finally, the features and performance of the proposed FPSO algorithm are illustrated by using two ill-posed functions and twenty-five benchmark functions, respectively. In numerical simulation results, the problem of odor source localization is presented to validate the effectiveness of the proposed FPSO algorithm.

An event-triggered distributed state estimation problem is investigated for a class of discrete-time nonlinear stochastic systems with unknown parameters over sensor networks (SNs) subject to switched topologies. An event-triggered communication strategy is employed to govern the information broadcast and reduce the unnecessary resource consumption. Based on the adopted communication strategy, a distributed state estimator is designed to estimate the plant states and also identify the unknown parameters. In the framework of input-to-state stability, sufficient conditions with an average dwell time are established to ensure the boundedness of estimation errors in mean-square sense. In addition, the gains of the designed estimators are dependent on the solution of a set of matrix inequalities whose dimensions are unrelated to the scale of underlying SNs, thereby fulfill the scalability requirement. Finally, an illustrative simulation is utilized to verify the feasibility of the proposed design scheme.

This article is concerned with the extended dissipativity of discrete-time neural networks (NNs) with time-varying delay. First, the necessary and sufficient condition on matrix-valued polynomial inequalities reported recently is extended to a general case, where the variable of the polynomial does not need to start from zero. Second, a novel Lyapunov functional with a delay-dependent Lyapunov matrix is constructed by taking into consideration more information on nonlinear activation functions. By employing the Lyapunov functional method, a novel delay and its variation-dependent criterion are obtained to investigate the effects of the time-varying delay and its variation rate on several performances, such as H∞ performance, passivity, and l2-l∞ performance, of a delayed discrete-time NN in a unified framework. Finally, a numerical example is given to show that the proposed criterion outperforms some existing ones.

This paper addresses the co-design problem of event-triggered communication scheduling and cooperative longitudinal control for automated vehicles subject to unknown external disturbances and vehicular accelerations. The central aim is to achieve automated vehicle platoons with desired platoon stability and robustness as well as prescribed spacing requirement, while simultaneously accomplishing improved communication efficiency. Toward this aim, a novel dynamic event-triggered platooning control strategy is developed such that the inter-vehicle communications are scheduled efficiently over time. Then, a co-design criterion of the admissible platoon control laws and the desired dynamic triggering laws is derived. It is shown that the co-design criterion empowers a comprehensive trade-off analysis between due communication efficiency and prescribed platoon performance. Finally, simulation results are presented to demonstrate the merits of the proposed co-design approach.

This paper developed a scalable parallel computing method that can be used for platoon simulations and controller validations. A scalable adaptive platooning control law was firstly designed, which accommodates a variety of vehicle-to-vehicle communication topologies. A road vehicle dynamics model that considered the Magic Formula tyre model and suspension dynamics was then derived and validated. The parallel computing method adopted the Message Passing Interface technique to allow fast and scalable simulations. Platoon length changes do not require controller and algorithm changes. An 11-vehicle platoon on a real-world 10 km long road section was simulated. Different localisation sensor errors, communication delays, heterogenous vehicle masses and driving modes were considered. Results show that localisation errors have negligible influences on space errors. Aggressive driving and heterogeneous vehicle masses slightly increase space errors (increases less than 0.23 m). Communication delays are the greatest influencer for space errors. Increases for 15, 45 and 75 ms delays were 0.43, 1.41 and 2.41 m, respectively. It is further shown that parallel computing can improve the computing speed by three times on personal computers and seven to 12 times on workstations.

This article investigates the problem of finite-time consensus tracking for incommensurate fractional-order nonlinear multiagent systems (MASs) with general directed switching topology. For the leader with bounded but arbitrary dynamics, a neighborhood-based saturated observer is first designed to guarantee that the observer's state converges to the leader's state in finite time. By utilizing a fuzzy-logic system to approximate the heterogeneous and unmodeled nonlinear dynamics, an observer-based adaptive parameter control protocol is designed to solve the problem of finite-time consensus tracking of incommensurate fractional-order nonlinear MASs on directed switching topology with a restricted dwell time. Then, the derived result is further extended to the case of directed switching topology without a restricted dwell time by designing an observer-based adaptive gain control protocol. By artfully choosing a piecewise Lyapunov function, it is shown that the consensus tracking error converges to a small adjustable residual set in finite time for both the cases with and without a restricted dwell time. It should be noted that the proposed adaptive gain consensus tracking protocol is completely distributed in the sense that there is no need for any global information. The effectiveness of the proposed consensus tracking scheme is illustrated by numerical simulations.

With the ever-increasing demand for electricity, the exhaustion of traditional energy resources (e.g., coal, fossil oil, gas) and environmental deterioration have been becoming the major concern for the modern society. This stimulates the rapid development of green...

The robust stability of uncertain linear neutral systems with time-varying discrete and neutral delays is investigated. The uncertainties under consideration are nonlinear time-varying parameter perturbations and norm-bounded uncertainties, respectively. Both delay-dependent and delay-derivative-dependent stability criteria are proposed and are formulated in the form of linear matrix inequalities. The presented results contain some existing results as their special cases. Numerical examples are also given to indicate significant improvements over existing results.

The rapid advancement of large models has led to the development of increasingly sophisticated models capable of generating diverse, personalized, and high-qual

This paper is concerned with controller design for continuous-time networked control systems (NCSs) under consideration of non-uniformly distributed time-varying sampling periods, network-induced delays and packet dropouts. By taking the non-uniformly distributed time-varying sampling periods into consideration, a new closed-loop model for an NCS is presented. A Lyapunov functional is proposed to derive the stabilization criteria. Even for an NCS considering a constant sampling period, the proposed modelling and design method is still applicable. A numerical example is given to illustrate the merits and effectiveness of the obtained results.

This paper is concerned with cyber attack detection problem in a platoon-based vehicular networked control system. In such a system, the information among vehicles is transmitted through a shared wireless communication network and also each vehicle has access to its own information measured by local sensors. These kind of systems are highly vulnerable to cyber attacks and therefore, cyber-security issues need to be properly addressed to ensure the safety of the systems. Among various cyber-security aspects, reliable attack detection is of utmost importance as the ability to detect cyber attacks in a timely manner can reduce the damage to the systems. Therefore, we present a cyber attack detection algorithm that is capable of detecting attacks violating both measurements and control command data. This algorithm is based on an ellipsoidal set-membership filtering approach which consists of two sets: prediction ellipsoid set and an estimation ellipsoid set calculated through updating the prediction ellipsoid set with the measurement data. The detection method depends on the existence of intersection between these two sets computed by the filter. Simulation results for some possible cyber attacks are provided to demonstrate the effectiveness of the proposed method.