Limited Communication Data Rate Research Articles

Consensus Control of Linear Discrete-time Multi-agent Systems with Limited Communication Data Rate

Consensus Control of Linear Discrete-time Multi-agent Systems with Limited Communication Data Rate

Practical output consensus of nonlinear heterogeneous multi-agent systems with limited data rate

This paper investigates the consensus problem for nonlinear heterogeneous multi-agent systems with limited communication data rate. Each agent is modeled by a higher-order strict-feedback continuous-time system with unknown nonlinearities and external disturbance, and only the first state variable being measurable. Extended state observers (ESOs) are used to estimate the unmeasurable agent states and the unknown nonlinear dynamics. An ESO-based distributed output feedback protocol with dynamic encoding and decoding is then presented. It is shown that, for a connected undirected network, the proposed protocol guarantees practical output consensus, in which the steady-state consensus error can be made arbitrarily small. The ESO-based protocol also shapes the transient consensus performance, as it is capable of recovering the consensus performance of a linear counterpart with fully measurable states. Furthermore, we prove that for higher-order uncertain nonlinear multi-agent systems, consensus can be achieved with merely one bit information exchange between each pair of adjacent agents at each time step. Finally, simulations on third-order pendulum systems are given, which verify the theoretical results.

Consensus of High-Order Nonlinear Continuous-Time Systems With Uncertainty and Limited Communication Data Rate

This paper considers the consensus problem of high-order nonlinear continuous-time systems with limited communication rate. With the aid of dynamic encoding and decoding, distributed controllers are proposed such that the states of a group of systems without uncertainty reach consensus. If there is uncertainty in each system, an inner-loop and outer-loop controller design approach is proposed. With the aid of this approach, distributed dynamic controllers are designed such that the states of a group of systems reach consensus. Simulations show the effectiveness of the proposed controllers.

Sampled‐data‐based consensus of continuous‐time systems with limited data rate

Leader-following consensus is investigated for second-order continuous-time multi-agent systems with limited communication data rate in this study. The network communication topology is directed and static. Using the sampled position and velocity data, a corresponding discrete-time system, whose leader-following consensus is proved to be equivalent to that of the original system, is given. A distributed protocol is proposed based on dynamic encoding and decoding. A necessary and sufficient condition is given for the existence of such communication and control protocol to ensure the achievement of leader-following consensus, if the upper bound of the communication data rate is predetermined. Two algorithms are also presented to achieve the leader-following consensus if the communication data rate is unfixed or limited, respectively. Finally, simulation examples are given to verify and illustrate the theoretical analysis.

Iterative Learning Control for Multi-Agent Systems With Finite-Leveled Sigma-Delta Quantization and Random Packet Losses

A quantized iterative learning control (QILC) for continuous-time multi-agent systems with finite-leveled sigma-delta ( $\Sigma \Delta$ ) quantization and random packet losses is first proposed in this paper. To realize the digital communication between signals and utilize limited communication bandwidth effectively, we introduce the $\Sigma \Delta$ quantizer with limited communication data rate (quantization bits) into the control field and for the design of the QILC in this paper. In addition, the packet losses are also first considered into the QILC, which makes the controller more close to the practical engineering applications. Since the nonlinearity and randomness introduced by the quantization and packet losses, a decreasing learning gain is utilized with the help of the non-smooth analysis and mathematical expectation for the analysis of convergence. Accurate tracking in the sense of expectation can be obtained based on randomly small number of quantization bits, even merely one bit of quantization information. Numerical simulations are given to show the effectiveness of the proposed protocol.

Quantized Leaderless and Leader-Following Consensus of High-Order Multi-Agent Systems With Limited Data Rate

Distributed consensus with limited communication data rate is an interesting and important problem and has been studied for multi-agent networks with the first order and second order integrator dynamics. However, the problem remains challenging for higher-order systems due to the complexity of consensus analysis and data rate minimization. In this paper, the leaderless and leader-following quantized consensus for a special kind of high-order systems are considered. Each agent is assumed to be controllable and observable with single input and single output, and its system matrix admits n identical eigenvalues of 1. The special case of n-th order integrator multi-agent system with only the first state variable being measurable is first investigated, and it is shown that for a fixed undirected connected network, n bits of information exchange between agents suffice to guarantee the leaderless and leader-following quantized consensus respectively with an exponential convergence rate by employing a suitable encoding-decoding scheme and perturbation analysis of matrices. The obtained results are then extended to the general case of multi-agent dynamics with n identical eigenvalues of 1 by applying the same encoding-decoding scheme and control protocol to an observer system for each agent. The final consensus value and the application to formation control are also discussed.

Containment Control of Single-Integrator Network With Limited Communication Data Rate

This technical note investigates distributed containment control for a single-integrator continuous-time multi-agent system with a limited communication data rate. Network topology is a directed communication graph. The containment control with quantized communication for each follower is designed using only its neighbour's quantized information so that all followers move into the convex hull spanned by the leaders. Necessary and sufficient criteria which guarantee achievement of containment consensus are given if the communication data rates are unfixed or fixed. Under a given bound on communication data rate, an algorithm is established to achieve the containment consensus. Finally, all the theoretical results are illustrated by numerical simulations.

Leader-Following Consensus of Discrete-Time Multiagent Systems With Encoding–Decoding

The leader-following consensus of general linear discrete-time multiagent systems with a limited communication data rate and a directed fixed topology is investigated. The consensus protocol is designed for each agent, which is given in terms of states of its encoder and decoders with time-varying quantization levels. A rigorous analysis for the consensus convergence is provided. A finite lower bound of the communication data rate between each pair of adjacent agents is obtained to ensure consensus. A numerical example is presented to demonstrate the validity of the results obtained.

Event-Triggered Distributed Average Consensus Over Directed Digital Networks With Limited Communication Bandwidth.

In this paper, we consider the event-triggered distributed average-consensus of discrete-time first-order multiagent systems with limited communication data rate and general directed network topology. In the framework of digital communication network, each agent has a real-valued state but can only exchange finite-bit binary symbolic data sequence with its neighborhood agents at each time step due to the digital communication channels with energy constraints. Novel event-triggered dynamic encoder and decoder for each agent are designed, based on which a distributed control algorithm is proposed. A scheme that selects the number of channel quantization level (number of bits) at each time step is developed, under which all the quantizers in the network are never saturated. The convergence rate of consensus is explicitly characterized, which is related to the scale of network, the maximum degree of nodes, the network structure, the scaling function, the quantization interval, the initial states of agents, the control gain and the event gain. It is also found that under the designed event-triggered protocol, by selecting suitable parameters, for any directed digital network containing a spanning tree, the distributed average consensus can be always achieved with an exponential convergence rate based on merely one bit information exchange between each pair of adjacent agents at each time step. Two simulation examples are provided to illustrate the feasibility of presented protocol and the correctness of the theoretical results.

Consensusability of multi-agent systems via observer with limited communication data rate

ABSTRACTThis paper investigates the consensusability of multi-agent systems via observer with limited communication data. A novel algorithm to determine the parameters of quantizer and encoder is provided. The observer-based consensusability with unlimited bandwidth and observer-based consensusability with communication data rate are discussed separately. Finally, a simulation is given to illustrate the results.

Output feedback quantized observer‐based synchronization of linear multi‐agent systems over jointly connected topologies

SummaryThe synchronization problem of linear over‐actuated multi‐agent systems with unmeasurable states is studied in this paper, under both limited communication data rate and switching topology flows. A class of adaptive quantized observer‐based encoding–decoding schemes and a class of certainty equivalence principle‐based control protocols are proposed. By developing the graph‐based space decomposition technique and analyzing the closed‐loop quantized dynamic equations, it is shown that if the network topology flow is jointly connected, the communication channels are periodic active, and the agent dynamics is observable, and with the orthogonal system matrix, the proposed communication and control protocols can ensure the closed‐loop system to achieve synchronization exponentially fast with finite bits of information exchange per step. Copyright © 2015 John Wiley & Sons, Ltd.

Distributed set-valued estimation in sensor networks with limited communication data rate

This paper is concerned with a distributed set-valued estimation problem in noisy sensor networks with limited communication data rate. The sensors iterate a sample-quantize-exchange process: firstly, the sensors synchronously take noisy measurements of the plant; secondly, owing to the communication channel constraint, each sensor makes the manipulation of quantization on its measurement, estimate and performance bound by using a static logarithmic quantizer; thirdly, the quantized information is exchanged among the neighbors. By assuming hard bounds on the process noises and measurement noises, a distributed set-valued estimation strategy is proposed for each sensor to generate a set of estimates in state space which contains the true state of the plant. A sufficient condition for the existence of the distributed set-valued estimators is derived, and the estimator parameters are determined by solving a convex optimization problem. Two illustrative examples are provided to demonstrate the effectiveness of the proposed theoretical results.

Distributed Coordination of Multi-Agent Systems With Quantized-Observer Based Encoding-Decoding

Integrative design of communication mechanism and coordinated control law is an interesting and important problem for multi-agent networks. In this paper, we consider distributed coordination of discrete-time second-order multi-agent systems with partially measurable state and a limited communication data rate. A quantized-observer based encoding-decoding scheme is designed, which integrates the state observation with encoding/decoding. A distributed coordinated control law is proposed for each agent which is given in terms of the states of its encoder and decoders. It is shown that for a connected network, 2-bit quantizers suffice for the exponential asymptotic synchronization of the states of the agents. The selection of controller parameters and the performance limit are discussed. It is shown that the algebraic connectivity and the spectral radius of the Laplacian matrix of the communication graph play key roles in the closed-loop performance. The spectral radius of the Laplacian matrix is related to the selection of control gains, while the algebraic connectivity is related to the spectral radius of the closed-loop state matrix. Furthermore, it is shown that as the number of agents increases, the asymptotic convergence rate can be approximated as a function of the number of agents, the number of quantization levels (communication data rate) and the ratio of the algebraic connectivity to the spectral radius of the Laplacian matrix of the communication graph.

FPGA Based Signal-Processing for Radio Detection of Cosmic Rays

For the observation of ultra high-energy cosmic rays (UHECRs) by the detection of their coherent radio emission an FPGA based trigger and radio frequency interference (RFI) filter was developed. Using radio detection, the electromagnetic part of an air shower in the atmosphere may be studied in detail, thus providing information complementary to that obtained by water Cherenkov detectors which are predominantly sensitive to the muonic content of an air shower at ground. For an extensive radio detector array, due to the limited communication data rate, a sophisticated self trigger is necessary. However, radio signals in the frequency range of 30-80 MHz are significantly contaminated by RFI and human made distortions. The digitized signals are converted from the time to frequency domain by a FFT procedure, then a deconvolution and RFI-filters are applied to correct the frequency response and to suppress the RFI. Finally the filtered data is transformed back into the time domain by an iFFT, also generating an envelope as a base for the final self-trigger. To avoid leakage effect and to create an overlap of successive data blocks, trapezoidal windowing is applied with internal overclocking. The algorithms for two polarization channels have been successfully implemented in a single FPGA and tested in a prototype board with 180 MHz sampling rate, 16-bit dynamic range, and 12-bit resolution.

Distributed consensus over digital networks with limited bandwidth and time-varying topologies

In this paper, we consider discrete-time distributed average-consensus with limited communication data-rate and time-varying communication topologies. We design a distributed encoding-decoding scheme based on quantization of scaled innovations and a control protocol based on a symmetric compensation method. We develop an adaptive scheme to select the numbers of quantization levels according to whether the associated channel is active or not. We prove that if the network is jointly connected, then under the protocol designed, average-consensus can be asymptotically achieved, and the convergence rate is quantified. Especially, if the duration of any link failure in the network is bounded, then the control gain and the scaling function can be selected properly such that 5-level quantizers suffice for asymptotic average-consensus with an exponential convergence rate.

Distributed Consensus With Limited Communication Data Rate

Communication data rate and energy constraints are important factors which have to be considered when investigating distributed coordination of multi-agent networks. Although many proposed average-consensus protocols are available, a fundamental theoretic problem remains open, namely, how many bits of information are necessary for each pair of adjacent agents to exchange at each time step to ensure average consensus? In this paper, we consider average-consensus control of undirected networks of discrete-time first-order agents under communication constraints. Each agent has a real-valued state but can only exchange symbolic data with its neighbors. A distributed protocol is proposed based on dynamic encoding and decoding. It is proved that under the protocol designed, for a connected network, average consensus can be achieved with an exponential convergence rate based on merely one bit information exchange between each pair of adjacent agents at each time step. An explicit form of the asymptotic convergence rate is given. It is shown that as the number of agents increases, the asymptotic convergence rate is related to the scale of the network, the number of quantization levels and the ratio of the second smallest eigenvalue to the largest eigenvalue of the Laplacian of the communication graph. We also give a performance index to characterize the total communication energy to achieve average consensus and show that the minimization of the communication energy leads to a tradeoff between the convergence rate and the number of quantization levels.

Distributed LMS with limited data rate

The problem of distributed least mean-square (D-LMS) on a network with a limited communication data rate is addressed. Each node in the network has a quantiser consisting of a first-order dynamical encoder/decoder and can only communicate with its neighbours. Simulation results demonstrate that for Gaussian data and small step-sizes the proposed cooperative D-LMS with quantisation is mean-square stable in all quantisation levels including the 1-bit case, and its performance approaches unquantised cooperative D-LMS when the quantisation level is fairly small.

Distributed Quantized Averaging under Directed Time-Varying Topologies

AbstractFor multi-agent systems with directed and time-varying communication graph and limited quantized communication data rate, distributed average consensus is investigated. We first give the corresponding convergence results for the case of directed fixed communication network, and then, propose a feedback-based distributed consensus protocol for the time-varying topology case to deal with the inconsistency between the internal state of each agent's encoder and the output of its neighbors’ decoder. It is shown that if the communication graph is directed, balanced and periodically connected, then exponential average consensus can be achieved by using merely one bit information exchange between each pair of adjacent agents at each time step.

Advanced digital self-triggering of radio emission of cosmic rays

Radio detection provides information about the electromagnetic part of an air shower in the atmosphere complementary to that obtained by water-Cherenkov detectors predominantly sensitive to the muonic content of an air shower at ground. For the measurement of ultra-high-energy cosmic rays (UHECR) by the detection of their coherent radio emission, several test setups have been developed and deployed at the Pierre Auger Observatory in Argentina. However, these UHECR radio pulses are significantly polluted by man-made radio frequency interferences (RFI). This requires a special design of antennas, analog, data acquisition (DAQ), and communication electronics, which are under investigation at the Pierre Auger Observatory. In large-scale detector arrays sophisticated self-triggering methods are necessary, to use the limited available communication data rate efficiently. This paper gives an overview of the electronics and self-triggering methods used in the test setups at the Pierre Auger Observatory and describes the experiences gained so far.

Average Consensus with Limited Data Rate and Switching Topologies

This paper is concerned with discrete-time distributed average-consensus with limited communication data-rate and switching communication topologies. We design a distributed encoding-decoding scheme based on difference quantization with dynamic scaling and a control protocol based on a symmetric compensation method. We develop an adaptive scheme to select the numbers of quantization levels. The number of quantization levels of each quantizer is tuned on-line according to whether the associated communication channel is active or not at the last step. We prove that if the network is jointly connected, then under the protocol designed, average-consensus can be asymptotically achieved without steady-state error, and the convergence rate is quantified. Especially, if the duration of link failures of all communication channels is bounded, then the control gain and the scaling function can be selected properly such that 5-level quantizers suffice for asymptotic average-consensus with an exponential convergence rate.