This paper addresses the distributed formation control problem of a networked multi-agent system (MAS) subject to limited communication resources. First, a dynamic event-triggered communication ...mechanism (DECM) is developed to schedule inter-agent communication such that some unnecessary data exchanges among agents can be reduced so as to achieve better resource efficiency. Different from most of the existing event-triggered communication mechanisms, wherein threshold parameters are fixed all the time, the threshold parameter in the developed event triggering condition is dynamically adjustable in accordance with a dynamic rule. It is numerically shown that the proposed DECM can achieve a better tradeoff between reducing inter-agent communication frequency and preserving an expected formation than some existing ones. Second, an event-triggered formation protocol is delicately proposed by using only locally triggered sampled data in a distributed manner. Based on the formation protocol, it is shown that the state formation control problem is cast into an asymptotic stability problem of a reduced-order closed-loop system. Then, criteria for designing desired formation protocol and communication mechanism are derived. Finally, the effectiveness and advantages of the proposed approach are demonstrated through a comparative study in multirobot formation control.
Phase-field method is a density-based computational method at the mesoscale for modeling and predicting the temporal microstructure and property evolution during materials processes. The focus of ...this article is on connecting the most common phase-field equations to the very basic first and second laws of classical thermodynamics through rudimentary irreversible thermodynamics. It briefly discusses the relations of the continuum phase-field equations to their counter parts at the microscopic and atomic levels. It attempts to clarify the contributions of long-range elastic, electrostatic, and magnetic interactions to domain structure evolution during structural, ferroelectric, and ferromagnetic phase transformations by separating order parameter changes due to the presence of quasi-static fields and those arising from phase transformations. A few examples are presented to demonstrate the possibility of employing the phase-field method to provide guidance to designing materials for optimum properties or discovering novel mesoscale phenomena or new materials functionalities. The article ends with a brief perspective on a number of potential future directions on the development and applications of phase-field method beyond its traditional applications to structural alloys.
This paper is concerned with the distributed set-membership filtering problem for a class of general discrete-time nonlinear systems under event-triggered communication protocols over sensor ...networks. To mitigate the communication burden, each intelligent sensing node broadcasts its measurement to the neighboring nodes only when a predetermined event-based media-access condition is satisfied. According to the interval mathematics theory, a recursive distributed set-membership scheme is designed to obtain an ellipsoid set containing the target states of interest via adequately fusing the measurements from neighboring nodes, where both the accurate estimate on Lagrange remainder and the event-based media-access condition are skillfully utilized to improve the filter performance. Furthermore, such a scheme is only dependent on neighbor information and local adjacency weights, thereby fulfilling the scalability requirement of sensor networks. In addition, an optimization algorithm is developed to minimize the trace of the estimated ellipsoid set, and the effect from the adopted event-triggered threshold is thoroughly discussed as well. Finally, a simulation example is utilized to illustrate the usefulness of the proposed distributed set-membership filtering scheme.
Autonomous surface vehicles (ASVs) are marine vessels capable of performing various marine operations without a crew in a variety of cluttered and hostile water/ocean environments. For complex ...missions, there are increasing needs for deploying a fleet of ASVs instead of a single one to complete difficult tasks. Cooperative operations with a fleet of ASVs offer great advantages with enhanced capability and efficacy. Despite various application potentials, coordinated motion control of ASVs pose great challenges due to the multiplicity of ASVs, complexity of intravehicle interactions and fleet formation with collision avoidance requirements, and scarcity of communication bandwidths in sea environments. Coordinated control of multiple ASVs has received considerable attention in the last decade. This article provides an overview of recent advances in coordinated control of multiple ASVs. First, some challenging issues and scenarios in motion control of ASVs are presented. Next, coordinated control architecture and methods of multiple ASVs are briefly discussed. Then, recent results on trajectory-guided, path-guided, and target-guided coordinated control of multiple ASVs are reviewed in detail. Finally, several theoretical and technical issues are suggested to direct future investigations including network-based coordination, event-triggered coordination, collision-free coordination, optimization-based coordination, data-driven coordination of ASVs, and task-region-oriented coordination of multiple ASVs and autonomous underwater vehicles.
This paper addresses the problem of leader-following consensus for networked multi-agent systems subject to limited communication resources and unknown-but-bounded process and measurement noise. ...First, a new distributed event-based communication mechanism on the basis of a time-varying threshold parameter is developed to schedule transmission of each sensor's measurement through a communication network so as to alleviate consecutive occupancy of communication resources. Second, a novel concept of set-membership leader-following consensus is put forward, through which the true states of all followers are guaranteed to always reside in a bounding ellipsoidal set of the leader's state. Third, in the case that full information of followers' states are not measurable, a distributed observer-based consensus protocol is presented to provide a set-membership estimation of each follower's state. Then, based on a recursive computation of confidence state estimation ellipsoids and leader state ellipsoid, a delicate convex optimization algorithm in terms of recursive linear matrix inequalities is proposed to design desired consensus protocol and event-based mechanism. Finally, an illustrative example is given to show the effectiveness and advantage of the developed approach.
This article investigates a neural network (NN)‐based control problem for unknown discrete‐time nonlinear systems with a denial‐of‐service (DoS) attack and an adaptive event‐triggered mechanism ...(ETM). The considered DoS attacks are described by the occurrence frequency and durations and hence more general in comparison with existing stochastic models. To the addressed problem, a novel adaptive rule adjusting the triggering threshold of ETM is constructed to govern the communication schedule, and an NN‐based observer is designed to identify the system dynamics where a piecewise update rule of NN weights is adopted to handle the challenge of the complex time series coming from both ETM and DoS attacks. In light of this kind of protocol‐ and attack‐induced switched systems, a sufficient condition dependent on the occurrence frequency and durations of DoS attacks is elaborately established via the analysis of input‐to‐state stability. Furthermore, an iteration adaptive dynamic programming approach is proposed to handle the addressed control issue, and the boundedness is discussed to both the estimation errors of the Luenberger‐type observer and the identified errors of NN weights of observer networks as well as actor‐critic networks with the help of the Lyapunov theory. Finally, a simulation example is utilized to illustrate the usefulness of the proposed controller design scheme.
Next‐generation microelectronics and electrical power systems call for high‐energy‐density dielectric polymeric materials that can operate efficiently under elevated temperatures. However, the ...currently available polymer dielectrics are limited to relatively low working temperatures. Here, the solution‐processable polymer nanocomposites consisting of readily prepared Al2O3 fillers with systematically varied morphologies including nanoparticles, nanowires, and nanoplates are reported. The field‐dependent electrical conduction of the polymer nanocomposites at elevated temperatures is investigated. A strong dependence of the conduction behavior and breakdown strength of the polymer composites on the filler morphology is revealed experimentally and is further rationalized via computations. The polymer composites containing Al2O3 nanoplates display a record capacitive performance, e.g., a discharged energy density of 3.31 J cm−3 and a charge–discharge efficiency of >90% measured at 450 MV m−1 and 150 °C, significantly outperforming the state‐of‐the‐art dielectric polymers and nanocomposites that are typically prepared via tedious, low‐yield approaches.
High‐temperature dielectric polymer nanocomposites with facilely prepared nanostructured Al2O3 fillers exhibit remarkable electrical energy storage and discharge capabilities at elevated temperatures and high electric fields, outperforming state‐of‐the‐art polymer dielectrics. The significant impact of the filler morphology on conduction behavior and capacitive performance of the composites is revealed.
In this paper, a design method is presented for path-following control of underactuated autonomous underwater vehicles subject to velocity and input constraints, as well as internal and external ...disturbances. In the guidance loop, a kinematic control law of the desired surge speed and pitch rate is derived based on a backstepping technique and a line-of-sight guidance principle. In the control loop, an extended state observer is developed to estimate the extended state composed of unknown internal dynamics and external disturbances. Then, a disturbance rejection control law is constructed using the extended state observer. To bridge the guidance loop and the control loop, a reference governor is proposed for computing optimal guidance signals within the velocity and input constraints. The reference governor is formulated as a quadratically constrained optimization problem. A projection neural network is employed for solving the optimization problem in real time. Simulation results illustrate the effectiveness of the proposed method for path-following control of autonomous underwater vehicles subject to constraints and disturbances simultaneously in the vertical plane.
This paper addresses the consensus problem for a continuous-time multiagent system (MAS) with Markovian network topologies and external disturbance. Different from some existing results, global ...jumping modes of the Markovian network topologies are not required to be completely available for consensus protocol design. A network topology mode regulator (NTMR) is first developed to decompose unavailable global modes into several overlapping groups, where overlapping groups refer to the scenario that there exist commonly shared local modes between any two distinct groups. The NTMR schedules which group modes each agent may access at every time step. Then a new group mode-dependent distributed consensus protocol on the basis of relative measurement outputs of neighboring agents is delicately constructed. In this sense, the proposed consensus protocol relies only on group and partial modes and eliminates the need for complete knowledge of global modes. Sufficient conditions on the existence of desired distributed consensus protocols are derived to ensure consensus of the MAS with a prescribed H_{\infty } performance level. Two examples are provided to show the effectiveness of the proposed consensus protocol.
Industrial cyber-physical systems (CPSs) are large-scale, geographically dispersed, and life-critical systems, in which lots of sensors and actuators are embedded and networked together to facilitate ...real-time monitoring and closed-loop control. Their intrinsic features in geographic space and resources put forward to urgent requirements of reliability and scalability for designed filtering or control schemes. This paper presents a review of the state-of-the-art of distributed filtering and control of industrial CPSs described by differential dynamics models. Special attention is paid to sensor networks, manipulators, and power systems. For real-time monitoring, some typical Kalman-based distributed algorithms are summarized and their performances on calculation burden and communication burden, as well as scalability, are discussed in depth. Then, the characteristics of non-Kalman cases are further disclosed in light of constructed filter structures. Furthermore, the latest development is surveyed for distributed cooperative control of mobile manipulators and distributed model predictive control in industrial automation systems. By resorting to droop characteristics, representative distributed control strategies classified by controller structures are systematically summarized for power systems with the requirements of power sharing and voltage and frequency regulation. In addition, distributed security control of industrial CPSs is reviewed when cyber-attacks are taken into consideration. Finally, some challenges are raised to guide the future research.
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