Fixed-time leader-follower quantized output consensus of high-order multi-agent systems over digraph

Collision-Free Formation Control for Heterogeneous Multiagent Systems Under DoS Attacks

A safe time-varying formation (TVF) control framework is proposed in this article for heterogeneous multiagent systems under the constraints of denial of service (DoS) attacks, noncooperative dynamic obstacles, and input saturation. The framework integrates both the cyber-layer and physical-layer components to address the challenges posed by these adverse conditions. In the cyber-layer, a distributed resilient observer is provided based on a control Lyapunov function (CLF)-quadratic program (QP). This observer estimates a reference exosystem, effectively decoupling heterogeneous dynamics from unsafe networks and optimizing the system resilience against DoS attacks. At the physical-layer, for the first time, a collision-free TVF controller is presented based on the CLF-exponential control barrier function-QP. The controller guarantees high-order heterogeneous agents' operation safety under noncooperative obstacles and input saturation. The effectiveness and advantages of the proposed algorithms are verified through the comparative simulations and experiments conducted on a physical system comprising unmanned aerial vehicles and unmanned ground vehicles.

A hierarchical framework for distributed resilient control of islanded AC microgrids under false data injection attacks

In this paper, we propose a control scheme to ensure the microgrid control layers are resilient to cyberattacks. The studied microgrid consists of several distributed generation (DG) units and we consider the hierarchical control structure that is common for microgrids. The use of communication channels among DGs has made microgrids more vulnerable and this is where cybersecurity issues arise. In this work we added three algorithms, reputation-based, Weighted Mean Subsequence Reduced (W-MSR) and Resilient Consensus Algorithm with Trusted Nodes (RCA-T), to the secondary control layer of the microgrid and made them resilient to false data injection (FDI) attacks. In reputation-based control, some procedures are used for detecting the attacked DGs and isolating them from the others. W-MSR and RCA-T are Mean Subsequence Reduced (MSR)-based algorithms that fade the effect of attacks without finding them. These algorithms use a simple strategy that ignores some extreme values of neighboring agents, so an attacker can simply get ignored. Our analysis of the reputation-based algorithm is based on scrambling matrices, so the communication graph can switch in a prescribed set. In each of the above cases, to evaluate the performance of the designed controllers, in addition to theoretical analysis, we evaluated and compared the controllers using simulation.

A novel framework of prescribed time/fixed time/finite time stochastic synchronization control of neural networks and its application in image encryption

In this paper, we investigate a novel framework for achieving prescribed-time (PAT), fixed-time (FXT) and finite-time (FNT) stochastic synchronization control of semi-Markov switching quaternion-valued neural networks (SMS-QVNNs), where the setting time (ST) of PAT/FXT/FNT stochastic synchronization control is effectively preassigned beforehand and estimated. Different from the existing frameworks of PAT/FXT/FNT control and PAT/FXT control (where PAT control is deeply dependent on FXT control, meaning that if the FXT control task is removed, it is impossible to implement the PAT control task), and different from the existing frameworks of PAT control (where a time-varying control gain such as μ(t)=T/(T-t) with t∈[0,T) was employed, leading to an unbounded control gain as t→T- from the initial time to prescribed time T), the investigated framework is only built on a control strategy, which can accomplish its three control tasks (PAT/FXT/FNT control), and the control gains are bounded even though time t tends to the prescribed time T. Four numerical examples and an application of image encryption/decryption are given to illustrate the feasibility of our proposed framework.

Consensus of Fractional-Order Double-Integral Multi-Agent System in a Bounded Fluctuating Potential

At present, the consensus problem of fractional complex systems has received more attention. However, there is little literature on the consensus problem of fractional-order complex systems under noise disturbance. In this paper, we present a fractional-order double-integral multi-agent system affected by a common bounded fluctuating potential, where the protocol term consists of both the relative position and velocity information of neighboring agents. The consensus conditions of the presented system in the absence of noise are analytically given and verified by a numerical simulation algorithm. Then, the influences of the system order and other system parameters on the consensus of the presented system in the presence of bounded noise are also analyzed. It is found that when compared with the classical integer-order system, the presented fractional-order system has a larger range of consensus parameters and has more rich dynamic characteristics under the action of random noise. Especially, the bounded noise has a promoting effect on the consensus of the presented fractional-order system, while there is no similar phenomenon in the corresponding integer-order system.