On leaderless consensus of fractional-order nonlinear multi-agent systems via event-triggered control

The consensus problem of fractional-order multi-agent systems is investigated by eventtriggered control in this paper. Based on the graph theory and the Lyapunov functional approach, the conditions for guaranteeing the consensus are derived. Then, according to some basic theories of fractional-order differential equation and some properties of Mittag–Leffler function, the Zeno behavior could be excluded. Finally, a simulation example is given to check the effectiveness of the theoretical result

Output feedback consensus control for fractional-order nonlinear multi-agent systems with directed topologies

Abstract(#br)This paper is devoted to the output feedback consensus control problem for a class of nonlinear fractional-order multi-agent systems (MASs) with general directed topologies. It is worth noting that the considered fractional-order MASs including the second-order MASs as special cases. By introducing a distributed filter for each agent, a control algorithm uses only relative position measurements is proposed to guarantee the global leaderless consensus can be achieved. Also the derived results are further extended to consensus tracking problem with a leader whose input is unknown and bounded. Finally, two simulation examples are provided to verify the performance of the control design

Mathematical problems for complex networks

Copyright @ 2012 Zidong Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is made available through the Brunel Open Access Publishing Fund.Complex networks do exist in our lives. The brain is a neural network. The global economy is a network of national economies. Computer viruses routinely spread through the Internet. Food-webs, ecosystems, and metabolic pathways can be represented by networks. Energy is distributed through transportation networks in living organisms, man-made infrastructures, and other physical systems. Dynamic behaviors of complex networks, such as stability, periodic oscillation, bifurcation, or even chaos, are ubiquitous in the real world and often reconfigurable. Networks have been studied in the context of dynamical systems in a range of disciplines. However, until recently there has been relatively little work that treats dynamics as a function of network structure, where the states of both the nodes and the edges can change, and the topology of the network itself often evolves in time. Some major problems have not been fully investigated, such as the behavior of stability, synchronization and chaos control for complex networks, as well as their applications in, for example, communication and bioinformatics

Consensus Tracking for Multiagent Systems Under Bounded Unknown External Disturbances Using Sliding-PID Control

This paper is devoted to the study of consensus tracking for multiagent systems under unknown but bounded external disturbances. A consensus tracking protocol which is a combination between the conventional PID controller and sliding mode controller named sliding-PID protocol is proposed. The protocol is applied to the consensus tracking of multiagent system under bounded external disturbances where results showed high effectiveness and robustness

Finite-time and fixed-time sliding mode control for second-order nonlinear multiagent systems with external disturbances

In this paper, the leader-following consensus of second-order nonlinear multiagent systems (SONMASs) with external disturbances is studied. Firstly, based on terminal sliding model control method, a distributed control protocol is proposed over undirected networks, which can not only suppress the external disturbances, but also make the SONMASs achieve consensus in finite time. Secondly, to make the settling time independent of the initial values of systems, we improve the protocol and ensure that the SONMASs can reach the sliding surface and achieve consensus in fixed time if the control parameters satisfy some conditions. Moreover, for general directed networks, we design a new fixed-time control protocol and prove that both the sliding mode surface and consensus for SONMASs can be reached in fixed time. Finally, several numerical simulations are given to show the effectiveness of the proposed protocols

Distributed Fault-Tolerant Consensus Tracking Control of Multi-Agent Systems under Fixed and Switching Topologies

This paper proposes a novel distributed fault-tolerant consensus tracking control design for multi-agent systems with abrupt and incipient actuator faults under fixed and switching topologies. The fault and state information of each individual agent is estimated by merging unknown input observer in the decentralized fault estimation hierarchy. Then, two kinds of distributed fault-tolerant consensus tracking control schemes with average dwelling time technique are developed to guarantee the mean-square exponential consensus convergence of multi-agent systems, respectively, on the basis of the relative neighboring output information as well as the estimated information in fault estimation. Simulation results demonstrate the effectiveness of the proposed fault-tolerant consensus tracking control algorithm

Bipartite consensus of nonlinear agents in the presence of communication noise

In this paper, a Distributed Nonlinear Dynamic Inversion (DNDI)-based consensus protocol is designed to achieve the bipartite consensus of nonlinear agents over a signed graph. DNDI inherits the advantage of nonlinear dynamic inversion theory, and the application to the bipartite problem is a new idea. Moreover, communication noise is considered to make the scenario more realistic. The convergence study provides a solid theoretical base, and a realistic simulation study shows the effectiveness of the proposed protocol.Engineering and Physical Sciences Research Council (EPSRC): EP/R009953/

Data-Driven Architecture to Increase Resilience In Multi-Agent Coordinated Missions

The rise in the use of Multi-Agent Systems (MASs) in unpredictable and changing environments has created the need for intelligent algorithms to increase their autonomy, safety and performance in the event of disturbances and threats. MASs are attractive for their flexibility, which also makes them prone to threats that may result from hardware failures (actuators, sensors, onboard computer, power source) and operational abnormal conditions (weather, GPS denied location, cyber-attacks). This dissertation presents research on a bio-inspired approach for resilience augmentation in MASs in the presence of disturbances and threats such as communication link and stealthy zero-dynamics attacks. An adaptive bio-inspired architecture is developed for distributed consensus algorithms to increase fault-tolerance in a network of multiple high-order nonlinear systems under directed fixed topologies. In similarity with the natural organisms’ ability to recognize and remember specific pathogens to generate its immunity, the immunity-based architecture consists of a Distributed Model-Reference Adaptive Control (DMRAC) with an Artificial Immune System (AIS) adaptation law integrated within a consensus protocol. Feedback linearization is used to modify the high-order nonlinear model into four decoupled linear subsystems. A stability proof of the adaptation law is conducted using Lyapunov methods and Jordan decomposition. The DMRAC is proven to be stable in the presence of external time-varying bounded disturbances and the tracking error trajectories are shown to be bounded. The effectiveness of the proposed architecture is examined through numerical simulations. The proposed controller successfully ensures that consensus is achieved among all agents while the adaptive law v simultaneously rejects the disturbances in the agent and its neighbors. The architecture also includes a health management system to detect faulty agents within the global network. Further numerical simulations successfully test and show that the Global Health Monitoring (GHM) does effectively detect faults within the network