On 3D simultaneous attack against manoeuvring target with communication delays

This article investigates the simultaneous attack problem of multiple missiles against a manoeuvring target with delayed information transmission in three-dimensional space. Based on the kinetic model of the missiles, the problem is divided into three demands: the velocity components normal to line-of-sight converge to zero in finite time, the component of motion states along line-of-sight should achieve consensus and converge to zero. The guidance law is designed for each demand and by theoretical proof, the upper bound of delay which can tolerate is presented and the consensus error of the relative distances can converge to a small neighbourhood of zero. And simulation example presented also demonstrates the validity of the theoretical result

Cooperative Control of Multi-Channel Linear Systems with Self-Organizing Private Agents

Cooperative behavior design for multi-agent systems with collective tasks is a critical issue to promote swarm intelligence. This paper investigates cooperative control for a multi-channel system, where each channel is managed by an agent that can communicate with neighbors in a network. Each agent is expected to self-organize a controller based only on local information and local interaction to stabilize the multi-channel system collaboratively. A novel cooperative control strategy is designed for each agent by leveraging a decomposing technique and a fusion approach. Then, a privacy-preserving mechanism is incorporated into this strategy to shield all private information from eavesdropping. Moreover, a fully distributed designing method for the strategy parameters is developed. As a result, agents can self-design and self-perform their controllers with private information preserved. It is proved that the multi-channel system stability can be ensured by the proposed strategy with finite fusion steps during each control interval. In addition, the cost of introducing the privacy-preserving mechanism and the effect of adding more channels on the system performance are quantitatively analyzed, which benefits mechanism design and channel placement. Finally, several comparative simulation examples are provided to demonstrate the effectiveness of the theoretical results

Solving specified-time distributed optimization problem via sampled-data-based algorithm

Despite significant advances on distributed continuous-time optimization of multi-agent networks, there is still lack of an efficient algorithm to achieve the goal of distributed optimization at a pre-specified time. Herein, we design a specified-time distributed optimization algorithm for connected agents with directed topologies to collectively minimize the sum of individual objective functions subject to an equality constraint. With the designed algorithm, the settling time of distributed optimization can be exactly predefined. The specified selection of such a settling time is independent of not only the initial conditions of agents, but also the algorithm parameters and the communication topologies. Furthermore, the proposed algorithm can realize specified-time optimization by exchanging information among neighbours only at discrete sampling instants and thus reduces the communication burden. In addition, the equality constraint is always satisfied during the whole process, which makes the proposed algorithm applicable to online solving distributed optimization problems such as economic dispatch. For the special case of undirected communication topologies, a reduced-order algorithm is also designed. Finally, the effectiveness of the theoretical analysis is justified by numerical simulations

On bipartite consensus of linear MASs with input saturation over directed signed graphs: Fully distributed adaptive approach

Abstract This paper studies the bipartite consensus problem with input saturation for general linear represents multi‐agent systems (MASs) with signed digraphs. Based on relative state information among neighbour agents, distributed adaptive protocols and a compensation observer are proposed, wherein both leaderless bipartite consensus and tracking bipartite consensus problems are addressed. For the case only relative output information is available, observer‐based distributed adaptive protocols are also designed, where for each agent, a local observer is given to estimate signed consensus error and a distributed observer is presented to achieve bipartite consensus and generate control input and a compensation observer is designed to handle input saturation. Simulation illustrations are given to explain the feasibility. The control protocols presented in this article depend on only local relative state or output information, without any eigenvalue information of Laplacian matrices associated with signed digraphs, which can be practically used for each agent in a fully distributed way

Complex network dynamics of multiscroll chaotic attractors and their output-feedback pinning synchronization

The saturated function series have been successfully used to generate multiscroll chaotic attractors. In this paper, we revisit multiscroll chaotic attractors via saturated function series. We find that with a small constant drift acting on the saturated function, the number of scrolls will greatly decrease. This phenomenon brings extra difficulty in pinning synchronization of networked multiscroll chaotic attractors. A new output-feedback pinning controller is designed based on the unknown-input distributed observer to estimate the synchronization error, which has the advantage of saving the communication cost as the transmission of the observer information is not needed