Publications

This paper considers an optimal formation tracking problem for a network of agents with multiple noncooperative and moving targets. The agents intend to not only form a desired geometric pattern but also track the unknown and time-varying centroid of the targets at an optimal distance. A hierarchical framework, which is composed of a centroid estimation level and an optimal formation tracking level, is proposed to deal with the formulated problem. In the centroid estimation level, a novel centroid estimation algorithm is established by using consensus-like protocols. To achieve accurate centroid estimation, the agents are divided into two subsets, i.e., an observation subset and a leader-following subset. The agents in the observation subset estimate the centroid of the moving targets by using their observed trajectories of the targets and the agents in the leader-following subset get an estimate on the centroid of the targets by following the references provided by the observation agents. Based on the estimated centroid, a time-varying aggregative game is designed to model the optimal formation tracking problem. By using average consensus protocols, gradient optimization algorithms, and regularization techniques, a time-varying Nash equilibrium seeking strategy is proposed. It is shown through Lyapunov stability analysis that the centroid estimation algorithm and the time-varying Nash equilibrium seeking strategy are effective. A distinguished feature of the proposed method is that formation and global time-varying optimization can be simultaneously achieved. A numerical example is provided to validate the effectiveness of the proposed method.

This paper is concerned with event-triggered H∞ control for a class of nonlinear networked control systems. An event-triggered transmission scheme is introduced to select 'necessary' sampled data packets to be transmitted so that precious communication resources can be saved significantly. Under the event-triggered transmission scheme, the closed-loop system is modeled as a system with an interval time-varying delay. Two novel integral inequalities are established to provide a tight estimation on the derivative of the Lyapunov–Krasovskii functional. As a result, a novel sufficient condition on the existence of desired event-triggered H∞ controllers is derived in terms of solutions to a set of linear matrix inequalities. No parameters need to be tuned when controllers are designed. The proposed method is then applied to the robust stabilization of a class of nonlinear networked control systems, and some linear matrix inequality-based conditions are formulated to design both event-triggered and time-triggered H∞ controllers. Finally, two numerical examples are given to demonstrate the effectiveness of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

This chapter is concerned with load sharingLoad sharing and voltage regulation in DC microgrids. In order to address this issue, a multi-objective optimization problem with tunable weighting coefficients is first formulated for DC microgridsMicrogrids. Second, a...

This paper is concerned with the resilient and secure remote monitoring of a cyber-physical system of a discrete time-varying state-space form against attacks. The specific statistical characteristic, magnitude, occurring place and time of the attack signals are not required during the monitor design and attack detection procedures. First, an optimal ellipsoidal state prediction and estimation method is delicately developed in such a way that the recursively computed prediction ellipsoid and estimate ellipsoid can both guarantee the containment of the true system state at each time step regardless of the unknown but bounded input signal. It is expected that the two ellipsoids can resist certain attacks as the calculated state prediction and state estimate are sets in state-space rather than single pointwise vectors, thus potentially enhancing the resilience of the remote monitoring system. Second, a set-based evaluation mechanism in combination with a remedy measure are proposed to provide timely detection of certain attacks. Furthermore, a numerically efficient algorithm is established to achieve resilience and attack detection of the remote monitoring system. Finally, it is shown through several case studies on a water supply distribution system that the proposed methods can provide quantitative analysis and evaluation of the potential consequences of various attacks on the remote monitoring system.

Platooning represents one of the key features that connected automated vehicles may possess as it allows multiple automated vehicles to be maneuvered cooperatively with small headways on roads. However, a critical challenge in accomplishing automated vehicle platoons is to deal with the effects of intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources. This paper addresses the co-design problem of dynamic event-triggered communication scheduling and cooperative adaptive cruise control for a convoy of automated vehicles with diverse spacing policies. The central aim is to achieve automated vehicle platooning under various gap references with desired platoon stability and spacing performance requirements, while simultaneously improving communication efficiency. Toward this aim, a dynamic event-triggered scheduling mechanism is developed such that the intervehicle data transmissions are scheduled dynamically and efficiently over time. Then, a tractable co-design criterion on the existence of both the admissible event-driven cooperative adaptive cruise control law and the desired scheduling mechanism is derived. Finally, comparative simulation results are presented to substantiate the effectiveness and merits of the obtained results.

This paper is concerned with stability of a linear system with a time-varying delay. First, an improved reciprocally convex inequality including some existing ones as its special cases is derived. Compared with an extended reciprocally convex inequality recently reported, the improved reciprocally convex inequality can provide a maximum lower bound with less slack matrix variables for some reciprocally convex combinations. Second, an augmented Lyapunov–Krasovskii functional is tailored for the use of a second-order Bessel–Legendre inequality. Third, a stability criterion is derived by employing the proposed reciprocally convex inequality and the augmented Lyapunov–Krasovskii functional. Finally, two well-studied numerical examples are given to show that the obtained stability criterion can produce a larger upper bound of the time-varying delay than some existing criteria.

This chapter is concerned with fixed-time consensus tracking for second-order multi-agent systems in networks with directed topology. Nonlinear consensus protocols are constructed with the aid of a sliding surface for each double-integrator agent dynamics. In...

This paper deals with the problem of odor source localization using a multi-robot system. A cooperative control system, which can coordinate the multi-robot system to locate the source of odor, is designed and independently executed by each robot. The proposed cooperative control system consists of three levels. In the first level, based on a mixture ensemble Kalman filtering theory, a new cooperative search algorithm, which can predict the probable position of the odor source by exploiting the information among the multi-robot system, is proposed. In the second level, a trajectory planning algorithm, by which the next position of a robot can be generated according to the predicted position of the odor source, detection events and nondetection events, is developed. In the third level, a consensus algorithm is used to control the robot to move toward the next position. Finally, the performance capabilities of the proposed cooperative control system are illustrated for the problem of odor source localization.

This paper is concerned with finite-time L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> leader-follower consensus of networked Euler-Lagrange systems in the presence of external disturbances. A distributed finite-time L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> control protocol is proposed by using backstepping design such that a group of follower agents modeled by Euler-Lagrange systems can follow a desired leader agent and achieve leader-follower consensus in finite time. Moreover, the finite-time L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> gain is less than or equal to a prescribed value. A simulation example of a network composed of seven two-link manipulators is given to show the effectiveness of the theoretical results.

This article addresses event-triggered optimal load dispatching based on collaborative neurodynamic optimization. Two cardinality-constrained global optimization problems are formulated and two event-triggering functions are defined for event-triggered load dispatching in thermal energy and electric power systems. An event-triggered dispatching method is developed in the collaborative neurodynamic optimization framework with multiple projection neural networks and a meta-heuristic updating rule. Experimental results are elaborated to demonstrate the efficacy and superiority of the approach against many existing methods for optimal load dispatching in air conditioning systems and electric power generation systems.

This paper addresses the problem of cluster formation control for a networked multi-agent system (MAS) in the simultaneous presence of aperiodic sampling and communication delays. First, to fulfill multiple formation tasks, a group of agents are decomposed into M distinct and nonoverlapping clusters. The agents in each cluster are then driven to achieve a desired formation, whereas the MAS as a whole accomplishes M cluster formations. Second, by a proper modeling of aperiodic sampling and communication delays, an aperiodic sampled-data cluster formation protocol (CFP) is delicately constructed such that the information exchanges among neighboring agents only occur intermittently at discrete instants of time. Third, a detailed theoretical analysis of cluster formability is carried out and a sufficient and necessary condition is provided such that the system is M-cluster formable. Furthermore, a discontinuous Lyapunov functional approach is developed to derive a design criterion on the existence of an admissible sampled-data CFP. Finally, numerical simulations on a team of nonholonomic mobile robots are given to illustrate the effectiveness of the obtained theoretical result.

This paper is concerned with the sampled-data control for a class of linear time-varying system. A classic Halanay inequality is first extended to the time-varying sampled-data system. Then based on the comparison principle and the extended Halanay inequality, new criteria for globally uniformly exponential stability and globally uniformly asymptotic stability of the corresponding closed-loop system are derived. Furthermore, an algorithm is presented to solve the gain synthesis problem. Finally, one example is given to show the effectiveness of the obtained results.

This paper is concerned with the neural-network-based (NN-based) output-feedback control issue for a class of nonlinear systems. For the purpose of effectively mitigating the phenomena of data congestion/collision, the stochastic communication protocols are favorably utilized to orchestrate the data transmissions, and the resultant closed-loop plant is represented by a so-called protocol-induced Markovian jump system with uncertain transition probability matrices. Taking such an uncertainty probability into account, a novel iterative adaptive dynamic programming (ADP) algorithm is developed to obtain the desired suboptimal solution with the help of auxiliary quasi-HJB equation, and the algorithm convergence is also investigated via the intensive use of the mathematical analysis. In this ADP framework, an NN-based observer with a novel adaptive tuning law is first adopted to reconstruct the system states. Then, based on the reconfigurable system, an actor–critic NN scheme with online learning is developed to realize the considered control strategy. Furthermore, in light of the Lyapunov theory, some sufficient conditions are derived to guarantee the stability of the zero equilibrium point of the closed-loop system as well as the boundedness of the estimation errors for critic and actor NN weights. Finally, a simulation example is employed to demonstrate the effectiveness of the developed suboptimal control scheme.

PROFESSOR Yitang Zhang, a number theorist at the University of California, Santa Barbara, USA, has posted a paper on arXiv [1] that hints at the possibility that he may have solved the Landau-Siegel zeros conjecture. He has claimed that he has disproved a weaker version of the Landau-Siegel zeroes conjecture, an important problem related to the hypothesis. The conjecture is that there are solutions to the zeta function that do not assume the form prescribed by the Riemann hypothesis. Inspired by his work, in this Perspective, we would like to discuss about the distribution of zeros of quasi-polynomials for linear time-invariant (LTI) systems with time delays.

This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.

This study is concerned with the simultaneous H ∞ stabilisation problem for a physically interconnected large‐scale system working in multiple operation modes. A distributed networked control framework is developed. The network‐based distributed DOF controllers are designed, which use not only the local measurements but also the neighbouring controllers' broadcasts. The designed controllers guarantee the mean‐square stability of the large‐scale system in multiple operation modes, and achieve the prescribed H ∞ disturbance attenuation level. Furthermore, the consecutive packet dropouts that occur in multiple communication channels (from the local sensor to the local controller, from the neighbouring controllers to the local controller, and from the local controller to the local actuator) are considered. Based on a stochastic control approach and an orthogonal complement space technique, a sufficient condition for the existence of the simultaneous H ∞ stabilisation controllers is provided, and a parameterisation of the controller gains is derived. An iterative LMI algorithm is established to seek a feasible solution. Finally, a numerical simulation example is exploited to illustrate the validity of the proposed scheme.