This brief considers the existence of periodic behaviors for discrete-time second-order multiagent systems with input saturation constraints. We first consider the case where the agent dynamics is a double integrator and then establish conditions on the feedback gains of the linear consensus control law for achieving periodic behaviors. This, in turn, shows that the previously established sufficient condition for reaching global consensus has a necessary aspect since these two conditions are exclusive. We further consider all other second-order agent dynamics and show that these multiagent systems under the linear consensus law exhibit periodic solutions provided the feedback gains satisfy certain conditions. Simulation results are used to validate the theoretical findings.

In this paper, we consider the recovery of piecewise sparse signals from incomplete noisy measurements via a greedy algorithm. Here piecewise sparse means that the signal can be approximated in certain domain with known number of nonzero entries in each piece/segment. This paper makes a two-fold contribution to this problem: 1) formulating a piecewise sparse model in the framework of compressed sensing and providing the theoretical analysis of corresponding sensing matrices; 2) developing a greedy algorithm called piecewise orthogonal matching pursuit (POMP) for the recovery of piecewise sparse signals. Experimental simulations verify the effectiveness of the proposed algorithms.

This brief considers the synchronization problem of coupled nonlinear dynamical systems over time-varying interaction graphs. We first show that infinite joint connectivity is necessary for achieving globally asymptotic synchronization. We then show that the commonly used Lipschitz condition on the nonlinear self-dynamics is not sufficient to ensure synchronization even for an arbitrarily large coupling strength. A sufficient synchronization condition is established in terms of the times of connectivity, the integral of the Lipschitz gain, and the network parameters.

In this paper, we construct a framework to describe and study the coordinated output regulation problem for multiple heterogeneous linear systems. Each agent is modeled as a general linear multiple-input multiple-output system with an autonomous exosystem which represents the individual offset from the group reference for the agent. The multi-agent system as a whole has a group exogenous state which represents the tracking reference for the whole group. Under the constraints that the group exogenous output is only locally available to each agent and that the agents have only access to their neighbors' information, we propose observer-based feedback controllers to solve the coordinated output regulation problem using output feedback information. A high-gain approach is used and the information interactions are allowed to be switching over a finite set of networks containing both graphs that have a directed spanning tree and graphs that do not. Simulations are shown to validate the theoretical results.

Most algorithms for distributed averaging only guarantee asymptotic convergence. This paper introduces a distributed protocol that allows nodes to find the exact average of the initial values in a finite and minimum number of steps on interconnection topologies described by strongly connected directed graphs (digraphs). More specifically, under the assumption that each component has knowledge of the number of its outgoing links (i.e., the number of components to which it sends information), we show that the average value can be computed based on local observations over a finite time interval. The average can be obtained in a finite number of steps even when the information exchange is subject to delays. The proposed algorithm is the first in the literature that allows for distributed computation of the exact average in digraphs in finite time, with and without delays.

An anti-windup compensate algorithm for active disturbance rejection mechanism is proposed in this paper. This paradigm extends the traditional anti-windup scheme to the Active Disturbance Rejection Control (ADRC) mechanism, to deal with the input saturation nonlinearity and meanwhile reject the disturbance automatically by using Extended State Observer (ESO). The output of anti-windup compensator is treated as a part of unknown disturbances and is introduced into the ESO, which can online observe both internal and external disturbances (parameter uncertainties and model mismatches). The controller input is yielded by using a nonlinear feedback combination, and it is used to compensate the integrator windup caused by the saturation nonlinearity element. On the other hand, in order to determine the parameters of the ESO and the anti-windup compensator feedback gain, the L2 gain is adopted. The effectiveness and the robustness against model and parameter uncertainties of the proposed method is verified by an example of the seeker platform.

Given a platoon of vehicles traveling uphill, this paper considers the finite-time road grade computation problem. We propose a decentralized algorithm for an arbitrarily chosen vehicle to compute the road grade in a finite number of time-steps by using only its own successive velocity measurements. Simulations then illustrate the theoretical results. These new results can be applied to real-world vehicle platooning problems to reduce fuel consumption and carbon dioxide emissions.

In this paper, we consider the global consensus problem for discrete-time multi-agent systems with input saturation constraints under fixed undirected topologies. We first give necessary conditions for achieving global consensus via a distributed protocol based on relative state measurements of the agent itself and its neighboring agents. We then focus on two special cases, where the agent model is either neutrally stable or a double integrator. For the neutrally stable case, any linear protocol of a particular form, which solves the consensus problem for the case without input saturation constraints, also solves the global consensus problem for the case with input saturation constraints. For the double integrator case, we show that a subset of linear protocols, which solve the consensus problem for the case without saturation constraints, also solve the global consensus problem for the case with input saturation constraints. The results are illustrated by numerical simulations.

In this paper, we consider the output synchronization problem for heterogeneous networks of right-invertible linear agents. We assume that all the agents are introspective, meaning that they have access to their own local measurements. Under this assumption, we then propose a decentralized control scheme for solving the output synchronization problem for a set of network topologies. The proposed scheme can also be applied to solve the output formation problem with arbitrary formation vectors. We also consider the regulation of output synchronization problem, where the output of each agent has to track an a priori specified reference trajectory, generated by an exosystem. In this case, we assume that the root agent has access to its own output relative to the reference trajectory.

In this paper, we consider the semi-global regulation of output synchronization problem for heterogeneous networks of invertible linear agents subject to actuator saturation. That is, we regulate the output of each agent according to an a priori specified reference model. The network communication infrastructure provides each agent with a linear combination of its own output relative to that of neighboring agents, and it allows the agents to exchange information about their own internal observer estimates while some agents have access to their own outputs relative to the reference trajectory.