752 research outputs found

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

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    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

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

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    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

    Bipartite Consensus for a Class of Nonlinear Multi-agent Systems Under Switching Topologies:A Disturbance Observer-Based Approach

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    This paper considers the leader-following bipartite consensus for a class of nonlinear multi-agent systems (MASs) subject to exogenous disturbances under directed fixed and switching topologies, respectively. Firstly, two new output feedback control protocols involving signs of link weights are introduced based on relative output measurements of neighboring agents. In order to estimate the disturbances produced by an exogenous system, a disturbance observer-based approach is developed. Then, sufficient conditions for leader-following bipartite consensus with directed fixed topologies are derived. Furthermore, by assuming that each switching topology contains a directed spanning tree, it is proved that the leader-following bipartite consensus can be realized with the designed output feedback control protocol if the dwell time is larger than a non-negative threshold. Finally, numerical simulations inspired by a real-world DC motors are provided to illustrate the effectiveness of the proposed controllers

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

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    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

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

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    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

    Leader-following Consensus Control of a Distributed Linear Multi-agent System using a Sliding Mode Strategy

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    A distributed leader-following consensus control framework is proposed for a linear system. The linear system is first transformed into a regular form. Then a linear sliding mode is designed to provide high robustness, and the corresponding consensus protocol is proposed in a fully distributed fashion. When matched disturbances are present, it can be demonstrated that the system states reach the sliding mode in finite time and consensus can be achieved asymptotically using Lyapunov theory and the invariant set theorem. Simulation results validate the effectiveness of the proposed algorithm

    Leader-following Consensus Control of a Distributed Linear Multi-agent System using a Sliding Mode Strategy

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    A distributed leader-following consensus control framework is proposed for a linear system. The linear system is first transformed into a regular form. Then a linear sliding mode is designed to provide high robustness, and the corresponding consensus protocol is proposed in a fully distributed fashion. When matched disturbances are present, it can be demonstrated that the system states reach the sliding mode in finite time and consensus can be achieved asymptotically using Lyapunov theory and the invariant set theorem. Simulation results validate the effectiveness of the proposed algorithm

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

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    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
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