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To improve the voltage and power sharing of distributed generations, the hierarchical controls are widely used in microgrids while the dependent communication network makes it difficult to ensure the performance under limited bandwidth. In this paper, a predictive voltage hierarchical controller is designed. With the delayed secondary PI compensation signals, an inner-loop robust control is designed in the primary controller, ensuring stable voltage tracking. Then, a predictive controller is designed to provide neighbor and local predictions, such that the data integrity is improved by an accurate predictive compensation under bidirectional data-loss. Final case study results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Methods for distributed optimization have received significant attention in recent years owing to their wide applicability in various domains including machine learning, robotics, and sensor networks. A distributed optimization method typically consists of two key components: communication and computation. More specifically, at every iteration (or every several iterations) of a distributed algorithm, each node in the network requires some form of information exchange with its neighboring nodes (communication) and the computation step related to a (sub)-gradient (computation). The standard way of judging an algorithm via only the number of iterations overlooks the complexity associated with each iteration. Moreover, various applications deploying distributed methods may prefer a different composition of communication and computation. Motivated by this discrepancy, in this paper, we propose an adaptive cost framework that adjusts the cost measure depending on the features of various applications. We present a flexible algorithmic framework, where communication and computation steps are explicitly decomposed to enable algorithm customization for various applications. We apply this framework to the well-known distributed gradient descent (DGD) method, and show that the resulting customized algorithms, which we call DGD $^t$ , NEAR-DGD $^t$ , and NEAR-DGD $^+$ , compare favorably to their base algorithms, both theoretically and empirically. The proposed NEAR-DGD $^+$ algorithm is an exact first-order method where the communication and computation steps are nested, and when the number of communication steps is adaptively increased, the method converges to the optimal solution. We test the performance and illustrate the flexibility of the methods, as well as practical variants, on quadratic functions and classification problems that arise in machine learning, in terms of iterations, gradient evaluations, communications, and the proposed cost framework. [ABSTRACT FROM AUTHOR]

This paper addresses the cooperative output regulation problem of linear multi-agent systems under switching communication topologies. A distributed event-triggered control scheme is proposed so that the cooperative output regulation problem is solved with only intermittent communication. The communication topology is not required to be connected at every time instant under the jointly connected assumption. With the proposed triggering mechanism, each agent only transmits the information to its neighbors at its own triggering times or the switching times. By introducing a fixed timer, Zeno behavior is strictly excluded for each agent. The effectiveness of the proposed control scheme is demonstrated by an example. [ABSTRACT FROM AUTHOR]

The push-sum algorithm allows distributed computing of the average on a directed graph, and is particularly relevant when one is restricted to one-way and/or asynchronous communications. We investigate its behavior in the presence of unreliable communication channels where messages can be lost. We show that exponential convergence still holds and deduce fundamental properties that implicitly describe the distribution of the final value obtained. We analyze the error of the final common value we get for the essential case of two nodes, both theoretically and numerically. We provide performance comparison with a standard consensus algorithm. [ABSTRACT FROM AUTHOR]

This technical note focuses on the leader-following consensus problem of multiple uncertain Euler–Lagrange systems subject to communication delays and switching networks. By integrating the feedforward control approach with the adaptive control approach, a new adaptive distributed controller is developed. As opposed to the existing literature, our result has its distinct advantages in that it can accommodate arbitrarily bounded nonuniform time-varying communication delays, and directed jointly connected switching communication networks. The effectiveness of the main result is demonstrated by some exemplary applications to cooperative control of some practical multiple mechanical systems. [ABSTRACT FROM AUTHOR]

We consider the problem of multiagent consensus where some agents are subject to faults/attacks and might make updates arbitrarily. The network consists of agents taking integer-valued (i.e., quantized) states under directed communication links. The goal of the healthy normal agents is to form consensus in their state values, which may be disturbed by the non-normal, malicious agents. We develop update schemes to be equipped by the normal agents whose interactions are asynchronous and subject to nonuniform and time-varying time delays. In particular, we employ a variant of the so-called mean subsequence reduced algorithms, which have been long studied in computer science, where each normal agent ignores extreme values from its neighbors. We solve the resilient quantized consensus problems in the presence of totally/locally bounded adversarial agents and provide necessary and sufficient conditions in terms of the connectivity notion of graph robustness. Furthermore, it will be shown that randomization is essential both in quantization and in the updating times when normal agents interact in an asynchronous manner. The results are examined through a numerical example. [ABSTRACT FROM AUTHOR]

This paper is concerned with the asynchronous state estimation for a class of discrete-time switched complex networks with communication constraints. An asynchronous estimator is designed to overcome the difficulty that each node cannot access to the topology/coupling information. Also, the event-based communication, signal quantization, and the random packet dropout problems are studied due to the limited communication resource. With the help of switched system theory and by resorting to some stochastic system analysis method, a sufficient condition is proposed to guarantee the exponential stability of estimation error system in the mean-square sense and a prescribed H\infty performance level is also ensured. The characterization of the desired estimator gains is derived in terms of the solution to a convex optimization problem. Finally, the effectiveness of the proposed design approach is demonstrated by a simulation example. [ABSTRACT FROM AUTHOR]

This paper is devoted to a distributed consensus problem for second-order multiagent systems with nonconvex velocity and control input constraints. A distributed control algorithm is introduced using local information. It is shown that consensus can be achieved as long as the union of the communication graphs has directed spanning trees among each time interval of certain bounded length in the presence of arbitrarily bounded communication delays. Finally, a numerical example is included to illustrate the theoretical results. [ABSTRACT FROM PUBLISHER]

We provide a comprehensive solution to the estimation problem of the state for a linear time-invariant system in a distributed fashion over networks that allow only intermittent information transmission. By attaching to each node an observer that employs information received from its neighbors triggered by asynchronous communication events, we propose a distributed state observer that guarantees global exponential stability of the zero estimation error set. The design of parameters is formulated as linear matrix inequalities. A thorough robustness analysis of the proposed observer to unmodeled dynamics, unknown communication times, as well as measurement and communication noise characterized in terms of input-to-state stability is presented. These properties of the proposed observer are shown analytically and validated numerically. [ABSTRACT FROM PUBLISHER]

This note addresses the output consensus problem of discrete-time heterogeneous linear multiagent systems with switching topology and time delays. Three types of time delays are considered: communication delays, input delays, and output delays. A distributed predictor-based controller is proposed and it is shown that the output consensus problem can be solved via the proposed controller. A key to the proof of our main results is the establishment of a new property of graphs, that is, uniform sequential connectivity and uniform quasi-strong connectivity are equivalent. A simulation example is provided to illustrate the effectiveness of our results. [ABSTRACT FROM PUBLISHER]

This paper describes an on-chip interface for recovering power and providing full-duplex communication over an AC-coupled 4-wire lead between active implantable devices. The target application requires two modules to be implanted in the brain (cortex) and upper chest; connected via a subcutaneous lead. The brain implant consists of multiple identical “optrodes” that facilitate a bidirectional neural interface (electrical recording and optical stimulation), and the chest implant contains the power source (battery) and processor module. The proposed interface is integrated within each optrode ASIC allowing full-duplex and fully-differential communication based on Manchester encoding. The system features a head-to-chest uplink data rate (up to 1.6 Mbps) that is higher than that of the chest-to-head downlink (100 kbps), which is superimposed on a power carrier. On-chip power management provides an unregulated 5-V dc supply with up to 2.5-mA output current for stimulation, and two regulated voltages (3.3 and 3 V) with 60-dB power supply rejection ratio for recording and logic circuits. The 4-wire ASIC has been implemented in a 0.35- \mu \textm CMOS technology, occup-ying a 1.5-mm2 silicon area, and consumes a quiescent current of 91.2~\mu \textA . The system allows power transmission with measured efficiency of up to 66% from the chest to the brain implant. The downlink and uplink communication are successfully tested in a system with two optrodes and through a 4-wire implantable lead. [ABSTRACT FROM AUTHOR]

This paper addresses the issue of synchronization of switched delayed neural networks with communication delays via event-triggered control. For synchronizing coupled switched neural networks, we propose a novel event-triggered control law which could greatly reduce the number of control updates for synchronization tasks of coupled switched neural networks involving embedded microprocessors with limited on-board resources. The control signals are driven by properly defined events, which depend on the measurement errors and current-sampled states. By using a delay system method, a novel model of synchronization error system with delays is proposed with the communication delays and event-triggered control in the unified framework for coupled switched neural networks. The criteria are derived for the event-triggered synchronization analysis and control synthesis of switched neural networks via the Lyapunov-Krasovskii functional method and free weighting matrix approach. A numerical example is elaborated on to illustrate the effectiveness of the derived results. [ABSTRACT FROM AUTHOR]

In this paper, we study the robust consensus problem for a group of linear discrete-time or continuous-time agents to coordinate over an uncertain communication network, which is to achieve consensus against transmission errors and noises. We model the network by communication links subject to deterministic uncertainties, which can be additive perturbations described by either some unknown transfer functions or norm bounded matrices. We show that the robust consensus problem can generally be solved by solving a simultaneous $H_\infty$ control problem for a set of low-dimensional subsystems. We also derive necessary conditions for the existence of a protocol achieving robust consensus. The results show that for discrete-time agents the uncertainty size must not exceed the inverse of the Mahler measure of the agents, while for continuous-time agents it must be less than the unity. Sufficient conditions in terms of linear matrix inequalities are further presented to design the robust consensus protocols. [ABSTRACT FROM AUTHOR]

This paper investigates performance limitation issues of multivariable networked feedback systems with multiport communication channels. We develop a general information-theoretic paradigm for analyzing the limitations and tradeoffs imposed by communication channels, which is enabled by the development of new information measures and Bode-type integral inequalities. The integral inequalities quantify the tradeoffs in disturbance attenuation for broad classes of systems consisting of linear time-invariant plants and causal, possibly nonlinear, time-varying stabilizing controllers communicating over general noisy channels with causal encoders and decoders. The channel blurredness, a newly developed information measure for the quality of multiport communication channels, is used to characterize the effect of communication channel constraints on the integrals and henceforth the tradeoff in disturbance attenuation. For several canonical channels with power constraints, such as additive white Gaussian noise channels, additive colored Gaussian noise channels, and fading channels, we derive explicit forms for the channel blurredness, which, together with the Bode-type integral inequalities, show that to mitigate the noise effect on performance tradeoff, the power of the communication channels must be distributed in ways fundamentally different from the Shannon’s classical “water-filling” power allocation policy. [ABSTRACT FROM AUTHOR]

For millions of people around the globe, the Internet is a simple fact of life. We take for granted the invisible network that enables us to communicate, navigate, investigate, flirt, shop, and play. Early on, this network-of-networks connected only select companies and university campuses. Nowadays, it follows almost all of us into the most intimate areas of our lives. And yet, very few people know how the Internet became social. [ABSTRACT FROM AUTHOR]

In this note, we first propose an adaptive distributed observer for a linear leader system. This observer only assumes those followers who are the children of the leader know the system matrix of the leader system. Then, we further develop a distributed adaptive controller utilizing this adaptive distributed observer to solve the leader-following consensus problem for multiple uncertain Euler-Lagrange systems without assuming that all the followers need to know the system matrix of the leader system. [ABSTRACT FROM AUTHOR]

This technical note addresses the distributed containment control problem for a linear multi-leader multi-agent system with a directed communication topology. A new class of distributed observer-type containment protocols based only on the relative output measurements of the neighboring agents is proposed, removing the impractical assumption in some of the existing approaches that the observers embedded in the multiple dynamic agents have to share information with their neighbors. Under the mild assumption that, for each follower, there exists at least one leader having a directed path to that follower, some sufficient conditions are derived to guarantee the states of the followers to asymptotically converge to a convex hull formed by those of the dynamic leaders. Finally, some numerical simulations on containment of a multi-vehicle system are given to verify the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, a high level of accuracy is required in time synchronization to maintain time consistency of sensed data and to reduce idle listening times. In this technical note, we propose two fully distributed protocols for time synchronization. They are based on algorithms of multi-agent consensus and hence do not require any leader node. Further, they employ an event-based scheme to enhance communication efficiency. We analyze their convergence properties and show that clock synchronization can be achieved with less communication at guaranteed precision. [ABSTRACT FROM PUBLISHER]

We investigate supervisory control of networked discrete event systems with asynchronous communication between the plant and supervisor. The observation and control may be randomly delayed. The delays are bounded and will not change the order of observation (FIFO). Our goal is to synthesize a supervisor such that the behavior of the supervised system is both adequate and legal (safe). We derive a necessary and sufficient condition for the existence of such a supervisor. When the condition is satisfied, we find a minimally-permissive state-estimate-based control policy which can be implemented offline or online. Furthermore, we derive an algorithm to check the condition for the existence of the supervisor by constructing an augmented automaton. The algorithm allows us to obtain a maximally-permissive control policy by iteration. [ABSTRACT FROM PUBLISHER]

The stochastic consensus problem of linear multi-input multi-output (MIMO) multi-agent systems (MASs) with communication noises and Markovian switching topologies is studied in this technical note. The agent's full state is first estimated by the state observer, and then the estimated state is exchanged with neighbor agents through a noisy communication environment. The communication topology is randomly switching and the switching law is described by a continuous-time Markovian chain. Then a consensus protocol is proposed for this MAS, and some sufficient conditions are obtained for ensuring the mean square and almost sure consensus. In addition, if the communication topology is fixed, some necessary and sufficient conditions for the mean square consensus can be obtained according to whether or not each agent in the system has parents. [ABSTRACT FROM AUTHOR]

We study the problem of multi-robot target assignment to minimize the total distance traveled by the robots until they all reach an equal number of static targets. In the first half of the paper, we present a necessary and sufficient condition under which true distance optimality can be achieved for robots with limited communication and target-sensing ranges. Moreover, we provide an explicit, non-asymptotic formula for computing the number of robots needed to achieve distance optimality in terms of the robots' communication and target-sensing ranges with arbitrary guaranteed probabilities. The same bounds are also shown to be asymptotically tight. In the second half of the paper, we present suboptimal strategies for use when the number of robots cannot be chosen freely. Assuming first that all targets are known to all robots, we employ a hierarchical communication model in which robots communicate only with other robots in the same partitioned region. This hierarchical communication model leads to constant approximations of true distance-optimal solutions under mild assumptions. We then revisit the limited communication and sensing models. By combining simple rendezvous-based strategies with a hierarchical communication model, we obtain decentralized hierarchical strategies that achieve constant approximation ratios with respect to true distance optimality. Results of simulation show that the approximation ratio is as low as 1.4. [ABSTRACT FROM AUTHOR]

This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware. [ABSTRACT FROM AUTHOR]

We consider a remote estimation problem with an energy harvesting sensor and a remote estimator. The sensor observes the state of a discrete-time source which may be a finite state Markov chain or a multidimensional linear Gaussian system. It harvests energy from its environment (say, for example, through a solar cell) and uses this energy for the purpose of communicating with the estimator. Due to randomness of the energy available for communication, the sensor may not be able to communicate all of the time. The sensor may also want to save its energy for future communications. The estimator relies on messages communicated by the sensor to produce real-time estimates of the source state. We consider the problem of finding a communication scheduling strategy for the sensor and an estimation strategy for the estimator that jointly minimizes the expected sum of communication and distortion costs over a finite time horizon. Our goal of joint optimization leads to a decentralized decision-making problem. By viewing the problem from the estimator's perspective, we obtain a dynamic programming characterization for the decentralized decision-making problem that involves optimization over functions. Under some symmetry assumptions on the source statistics and the distortion metric, we show that an optimal communication strategy is described by easily computable thresholds and that the optimal estimate is a simple function of the most recently received sensor observation. [ABSTRACT FROM AUTHOR]

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies. [ABSTRACT FROM AUTHOR]

This work models and synthesizes communicating decentralized supervisors for Discrete-Event System (DES) which communicate the information about observed events. This is done within the authors' framework of Distributed Supervised DESs (DSDESs), using agent-wise labeling maps to reveal the informational dependencies among the supervisors. Communication between every two supervisors is modeled by the maps from the sender's observable events to its set of recently observed event, or an empty set. Thereby, the synthesis of communicating decentralized supervisors is reduced to the design of these maps. [ABSTRACT FROM AUTHOR]

We consider sensor data scheduling for remote state estimation. Due to constrained communication energy and bandwidth, a sensor needs to decide whether it should send the measurement to a remote estimator for further processing. We propose an event-based sensor data scheduler for linear systems and derive the corresponding minimum squared error estimator. By selecting an appropriate event-triggering threshold, we illustrate how to achieve a desired balance between the sensor-to-estimator communication rate and the estimation quality. Simulation examples are provided to demonstrate the theory. [ABSTRACT FROM AUTHOR]

This paper presents a new Class-E power amplifier (PA) with a \pi-matching output network. The PA is targeted at low output power wireless applications. Analytical formulae are derived to aid the PA design, characterization and optimization. A fully integrated 2.4-GHz PA for short distance communications has been implemented in 0.13 \mu\ m CMOS technology to verify the proposed design method. The measured output power levels vary from -3.2 to 5.7 dBm while achieving maximum overall efficiency of 55%. [ABSTRACT FROM AUTHOR]

We apply recent results on robust global asymptotic stabilization of the attitude of a single rigid body to the problem of globally synchronizing the attitude of a network of rigid bodies using a decentralized strategy. The proposed hybrid feedback scheme relies on the communication of a binary logic variable between each pair of neighboring rigid bodies that determines the orientation of a torque component acting to reduce their relative error. Through a hysteretic switch of this logic variable, the hybrid feedback achieves global synchronization under the assumption that the network is connected and acyclic. The hysteresis eliminates chattering while preventing the “unwinding phenomenon” apparent in some quaternion-based attitude control schemes. The results are exercised in a numerical example. [ABSTRACT FROM AUTHOR]

This paper presents the design and analysis of a wideband inductorless variable-gain amplifier (VGA) for high-speed communication receiver systems. The proposed methodology of using a dual-feedback network for bandwidth extension and dc offset cancellation is analyzed theoretically. The proof of concept is verified by a measured stand-alone VGA chip and it achieves several record performances compared to the existing publications up to date. The chip achieves a 2.2 GHz 3-dB bandwidth with wide tuning range from -10 dB up to 50 dB. Moreover, it consumes only 2.5 mW through a 1 V supply and occupies 0.01 mm2 active area in a standard 90 nm CMOS technology. [ABSTRACT FROM PUBLISHER]

Approximation techniques are useful for implementing pattern recognizers, communication decoders and sensory processing algorithms where computational precision is not critical to achieve the desired system level performance. In our previous work, we had proposed margin propagation (MP) as an efficient piecewise linear (PWL) approximation technique to a log-sum-exp function and had demonstrated its advantages for implementing probabilistic decoders. In this paper, we present a systematic and a generalized approach for synthesizing analog piecewise-linear (PWL) computing circuits using the MP principle. MP circuits use only addition, subtraction and threshold operations and hence can be implemented using universal conservation principles like the Kirchoff's current law. Thus, unlike the conventional translinear CMOS current-mode circuits, the operation of the MP circuits are functionally similar in weak, moderate, and strong inversion regimes of the MOS transistor making the design approach bias-scalable. This paper presents measured results from MP circuits prototyped in a 0.5 μm standard CMOS process verifying the bias-scalable property. As an example, we apply the synthesis approach towards designing linear classifiers and we verify its performance using measured results. [ABSTRACT FROM AUTHOR]

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the co-authors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index. [ABSTRACT FROM PUBLISHER]

Consider a first order linear time-invariant discrete time system driven by process noise, a pre-processor that accepts causal measurements of the state of the system, and a state estimator. The pre-processor and the state estimator are not co-located, and, at every time-step, the pre-processor transmits either a real number or a free symbol to the estimator. We seek the pre-processor and the estimator that jointly minimize a cost that combines two terms; the expected squared state estimation error and a communication cost. In our formulation, the transmission of a real number from the pre-processor to the estimator incurs a positive cost while free symbols induce zero cost. This paper proves analytically that a symmetric threshold policy at the pre-processor and a Kalman-like filter at the estimator, which updates its estimate linearly in the presence of free symbols, are jointly optimal for our problem. [ABSTRACT FROM AUTHOR]

In this technical note, we consider the problem of periodic sensor scheduling with limited resources. Two sensors are used to measure the state of a discrete-time linear process. We assume that each sensor has a maximum duty cycle and at most one sensor can communicate with a remote estimator at each time step due to the limited communication bandwidth. When a sensor is scheduled to send data, it sends the most recent D measurement data to the estimator. Upon receiving the measurement data from the sensors, the estimator computes the optimal estimate of the state of the process. We first present a necessary condition for a periodic sensor schedule to be optimal. Based on this necessary condition, we construct an optimal periodic schedule that minimizes the estimation error at the estimator and at the same time satisfies the energy and communication bandwidth constraints. Examples are provided throughout the technical note to demonstrate the results developed. [ABSTRACT FROM AUTHOR]

We study the effect of feedback from the receiver through the transmission layer protocol on the problem of estimating a linear time-invariant process across communication links that erase data stochastically. We compare the stability and performance for two cases: i) when the transmission layer protocol provides acknowledgements for any data successfully transmitted and the sensor transmits new data only on obtaining such an acknowledgement for previously transmitted data (so-called transmission control protocol (TCP)-like protocols), and ii) when there is no feedback from the estimator and the source transmits new data at every time step (so-called user datagram protocol (UDP)-like protocols). Due to the latency introduced by acknowledgements and retransmissions, it is often assumed that such feedback will necessarily degrade control/estimation performance. We show that this statement does not hold in general. When a single sensor transmits data across a single link, we prove that TCP-like protocols always perform worse than UDP-like protocols in the sense of minimizing the error covariance. When either multiple sensors or multiple links are present, we prove that feedback may lead to better performance. [ABSTRACT FROM AUTHOR]

Multicarrier modulations (MCMs) have been considered as a good means to combat the frequency-selective fading. In practice, the MCM idea has already been integrated in most of the modern communication applications, including power line communications (PLCs). However, even in the MCM conception, there still exist several proposals of different schemes that remain competing with each other. In this paper, we unveil a flexibility gain that can possibly be obtained from the coexistence of different MCMs. This flexibility is termed as “modulation flexibility,” meaning that we switch among different MCM schemes according to the transmission environment, and such idea can be eventually realized by a unified MCM transceiver. This paper includes a presentation of its efficient implementation as well as its performance evaluation. [ABSTRACT FROM PUBLISHER]

The small-gain condition presented by Polushin et al. may be replaced by a strictly weaker one to obtain essentially the same result. The necessary minor modifications of the proof are given. Using essentially the same arguments, a global version of the result is also presented. [ABSTRACT FROM AUTHOR]

This paper gives sufficient conditions for string instability in an array of linear time-invariant autonomous vehicles with communication constraints. The vehicles are controlled autonomously and are subject to a rigid or semi-rigid formation policy. The individual controllers are assumed to have a limited range of forward and backward communication with other vehicles. Sufficient conditions are given that imply a lower bound on the peak of the frequency response magnitude of the transfer function mapping a disturbance to the leading vehicle to a vehicle in the chain. This lower bound quantifies the effect of spacing separation policy, intervehicle communication policy, and vehicle settling response performance. These results extend earlier works to give a unified treatment of heterogeneous, non-nearest neighbor communication and semi-rigid one-dimensional formation control. [ABSTRACT FROM AUTHOR]

Consensusability of multi-agent systems (MASs) is a fundamental problem in the MAS research area, since when starting to design a consensus protocol, one should know whether or not there exists such a protocol that has the ability to make the MAS involved consensus. This technical note is aimed at studying the joint impact of the agent dynamic structure and the communication topology on consensusability. For the MASs with fixed topology and agents described by linear time-invariant systems, a necessary condition of consensusability with respect to a set of admissible consensus protocols is given, which is shown, under some mild conditions, to be necessary and sufficient. [ABSTRACT FROM AUTHOR]

We consider a distributed average consensus algorithm over a network in which communication links fail with independent probability. In such stochastic networks, convergence is defined in terms of the variance of deviation from average. We first show how the problem can be recast as a linear system with multiplicative random inputs which model link failures. We then use our formulation to derive recursion equations for the second order statistics of the deviation from average in networks with and without additive noise. We give expressions for the convergence behavior in the asymptotic limits of small failure probability and large networks. We also present simulation-free methods for computing the second order statistics in each network model and use these methods to study the behavior of various network examples as a function of link failure probability. [ABSTRACT FROM AUTHOR]

The consensus problem is considered for a team of second-order mobile agents communicating via a network with noise, variable delays and occasional packet losses. A queuing mechanism is applied and the switching process of the interaction topology of the network is modeled as a Bernoulli random process. In such a framework, a necessary and sufficient condition is presented for the mean-square robust consensus. Moreover, a necessary and sufficient condition of the solvability of the mean-square robust consensus problem is established. An approach to designing consensus protocol is proposed and numerical examples are given to illustrate the results. [ABSTRACT FROM AUTHOR]

We study a decentralized control problem of discrete event systems with communication. We first give a general automata-theoretic formalism that enables us to handle various types of communication, including delay. The decentralized control problem is shown to be undecidable under this formalism. Next we propose a semi-decision procedure for computing finite-state controllers to achieve a given specification in the sense of bisimilarity between the controlled system and a given specification. Using this procedure, we prove decidability of the problem for two special cases, one is the case in which the communication behavior is given as k-bounded-delay communication, and the other is the case in which any cycle in the state transition diagram of the system contains an event observable by all controllers. We also show a method for optimizing controllers based on a graph problem. [ABSTRACT FROM AUTHOR]

A version of the input-to-output stability (IOS) small gain theorem is derived for interconnections where the subsystems communicate asynchronously over multiple channels, and the communication is subject to multiple time-varying possibly unbounded communication delays. It is shown that a "multi-dimensional" version of the small gain condition guarantees the stability of the interconnection of IOS subsystems under certain mild assumptions imposed on communication process. The fulfillment of these assumptions does not depend on characteristics of the communication channels, but can always be guaranteed by implementation of certain features of the underlying communication protocol. This result is applicable to a wide range of dynamical systems whose parts communicate over networks, such as Internet-based teleoperators. [ABSTRACT FROM AUTHOR]

System throughput is one of the widely used performance measures in manufacturing, communication, and service networks. Although there are exceptions, throughput of such systems typically increases with additional capacity. We investigate how this improvement in throughput depends on the traffic load. More specifically, we consider M/M/1/m, M/G/1/m - PS, and M/G/c/c queues, all of which arise in a variety of contexts. For the M/G/c/c queue, we show that throughput improvement (both nominal and relative) that would be obtained by adding an extra server is increasing in the traffic load. For the M/M/1 /m and M/G/1/m - PS queues, we show that throughput improvement (both nominal and relative) that would be obtained by adding an extra buffer space is unimodal in traffic load. In particular, the relative improvement is maximized when the traffic load is one regardless of the buffer size. We also prove a new structural property for the blocking probability of the M/M/1/m and M/G/1/m - PS queues. [ABSTRACT FROM AUTHOR]

We provide an example proving that there exists no quadratic Lyapunov function for a certain class of linear agreement/consensus algorithms, a fact that had been numerically verified in [6]. We also briefly discuss sufficient conditions for the existence of such a Lyapunov function. [ABSTRACT FROM AUTHOR]

We describe a framework for the design of collective behaviors for groups of identical mobile agents. The approach is based on decentralized simultaneous estimation and control, where each agent communicates with neighbors and estimates the global performance properties of the swarm needed to make a local control decision. Challenges of the approach include designing a control law with desired convergence properties, assuming each agent has perfect global knowledge; designing an estimator that allows each agent to make correct estimates of the global properties needed to implement the controller; and possibly modifying the controller to recover desired convergence properties when using the estimates of global performance. We apply this framework to the problem of controlling the moment statistics describing the location and shape of a swarm. We derive conditions which guarantee that the formation statistics are driven to desired values, even in the presence of a changing network topology. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for extracting the spectral information of a multigigahertz jittery signal without using an ideal reference clock. This method utilizes existing on-chip single-shot period measurement techniques to measure single periods of a multigigahertz signal for analysis. Utilizing the same sampling and measuring principle, we propose another less computationally intensive method, based on the derivative principle, to extract only the random jitter component of the signal. To perform analysis on higher frequency signals, both methods are extended to measures multiple signal periods, instead of a single period, at each sampling. These methods do not require an ideal sampling clock, nor any additional measurement beyond existing techniques. Experimental results based on simulation show that these methods can accurately estimate the sinusoidal and random jitters of a multigigahertz signal. Extracted values can be used for estimating the bit-error rate of serial communication systems. [ABSTRACT FROM AUTHOR]

The paper studies asynchronous consensus problems of continuous-time multi-agent systems with discontinuous information transmission. The proposed consensus control strategy is implemented based on the state information of each agent's neighbors at some discrete times. The asynchrony means that each agent's update times, at which the agent adjusts its dynamics, are independent of others'. Furthermore, it is assumed that the communication topology among agents is time-dependent and the information transmission is with bounded time-varying delays. If the union of the communication topology across any time interval with some given length contains a spanning tree, the consensus problem is shown to be solvable. The analysis tool developed in this paper is based on nonnegative matrix theory and graph theory. The main contribution of this paper is to provide a valid distributed consensus algorithm that overcomes the difficulties caused by unreliable communication channels, such as intermittent information transmission, switching communication topology, and time-varying communication delays, and therefore has its obvious practical applications. Simulation examples are provided to demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of designing embedded decentralized discrete-event controllers over communication networks. It is assumed that there is a path between every pair of processes in the network. The control objective is specified by a prefix-closed language that is controllable and observable, but not coobservable. The paper is focused on communication among processes necessary to meet the control objective. As such, process models are left unspecified; it is only required that disabling any of the controllable events do not block communication among processes. Our findings support the idea that in the presence of ideal communication channels, the protocol design for noncoobservable specifications can be reduced to the synthesis of communicating decentralized supervisors, and we propose solutions for a restricted class of problems. The paper is concluded with a positive result for the case where channels are unreliable. [ABSTRACT FROM AUTHOR]

In a distributed discrete-event system with decentralized information, agents at the various sites (e.g., controllers or diagnosers) may be required to communicate in order to correctly perform some prescribed tasks. Bandwidth, power, or security constraints motivate the design of communication protocols among agents that minimize the number of required communications. This note presents an algorithm that can synthesize such a communication protocol given a set of "essential transitions" that constitute the initial required communications. The synthesized communication protocol is shown to be minimal. [ABSTRACT FROM AUTHOR]