Distributed consensus algorithm for networked Euler-Lagrange systems with self-delays and uncertainties

A distributed coordinated consensus problem for multiple networked Euler-Lagrange systems is studied. The communication between agents is subject to time delays, unknown parameters and nonlinear inputs, but only with their states available for measurement. When the communication topology of the system is connected, an adaptive control algorithm with selfdelays and uncertainties is suggested to guarantee global full-state synchro-nization that the difference between the agent＇s positions and ve-locities asymptotically converges to zero. Moreover, the distributed sliding-mode law is given for chaotic systems with nonlinear inputs to compensate for the effects of nonlinearity. Finally, simulation results show the effectiveness of the proposed control algorithm.

Controller-based observer design for distributed consensus of multi-agent systems with fault and delay

The object of this article is to study the consequences of occurrence both fault in input and multiple time-varying delays simultaneously while designing observer to estimate the states of agents and also unknown nonlinear fault of system.Two delay dependent criteria are established to show the states of observer reach to states of MAS and also states of observer reach to consensus.From two obtained criteria,it can be deduced,by constructing a distributed controller-based observer design,MAS reach to consensus exponentially.Finally,the advantages of the obtained results are shown by solving an illustrative example.

Self-Triggered Consensus Filtering over Asynchronous Communication Sensor Networks

In this paper,a self-triggered consensus filtering is developed for a class of discrete-time distributed filtering systems.Different from existing event-triggered filtering,the self-triggered one does not require to continuously judge the trigger condition at each sampling instant and can save computational burden while achieving good state estimation.The triggering policy is presented for pre-computing the next execution time for measurements according to the filter’s own data and the latest released data of its neighbors at the current time.However,a challenging problem is that data will be asynchronously transmitted within the filtering network because each node self-triggers independently.Therefore,a co-design of the self-triggered policy and asynchronous distributed filter is developed to ensure consensus of the state estimates.Finally,a numerical example is given to illustrate the effectiveness of the consensus filtering approach.

Distributed cooperative control of autonomous multi-agent UAV systems using smooth control

This paper addresses the cooperative control problem of multiple unmanned aerial vehicles(multi-UAV)systems.First,a new distributed consensus algorithm for second-order nonlinear multi-agent systems(MAS)is formulated under the leader-following approach.The algorithm provides smooth input signals to the agents’control channels,which avoids the chattering effect generated by the conventional sliding mode-based control protocols.Second,a new formation control scheme is developed by integrating smooth distributed consensus control protocols into the geometric pattern model to achieve three-dimensional formation tracking.The Lyapunov theory is used to prove the stability and convergence of both distributed consensus and formation controllers.The effectiveness of the proposed algorithms is demonstrated through simulation results.

Microcontroller Design Based on Dynamic Heterogeneous Redundancy Architecture

Redundancy control can effectively enhance the stability and robustness of a system.Based on the conventional redundancy control switchover and majority arbitration strategy,this paper introduces the concept of heterogeneity and dynamics,constructs a dynamic heterogeneous redundancy-based microcontroller architecture DHR-MCU,and designs a fixed-leader distributed consensus algorithm that satisfies the program running state control of this architecture.The theoretical analysis and actual measurement of the prototype system prove that this architecture has good anti-attack and self-recovery capabilities under normal functions and performances and meets the general robust features in terms of safety and security.

Excellent Practical Byzantine Fault Tolerance

With the rapid development of blockchain technology,more and more people are paying attention to the consensus mechanism of blockchain.Practical Byzantine Fault Tolerance(PBFT),as the first efficient consensus algorithm solving the Byzantine Generals Problem,plays an important role.But PBFT also has its problems.First,it runs in a completely closed environment,and any node can't join or exit without rebooting the system.Second,the communication complexity in the network is as high as O(n2),which makes the algorithm only applicable to small-scale networks.For these problems,this paper proposes an Optimized consensus algorithm,Excellent Practical Byzantine Fault Tolerance(EPBFT),in which nodes can dynamically participate in the network by combining a view change protocol with a node's add or quit request.Besides,in each round of consensus,the algorithm will randomly select a coordination node.Through the cooperation of the primary and the coordination node,we reduce the network communication complexity to O(n).Besides,we have added a reputation credit mechanism and a wrong node removal protocol to the algorithm for clearing the faulty nodes in time and improving the robustness of the system.Finally,we design experiments to compare the performance of the PBFT and EPBFT algorithms.Through experimental,we found that compared with the PBFT algorithm,the EPBFT algorithm has a lower delay,communication complexity,better scalability,and more practical.

Vulnerability Assessment of Distributed Load Shedding Algorithm for Active Distribution Power System Under Denial of Service Attack

In order to deal with frequency deviation andsupply-demand imbalance in active distribution power system, inthis paper a distributed under frequency load shedding (UFLS)strategy is proposed. Different from conventional centralizedUFLS schemes, no centralized master station gathering all thebuses’ information is required. Instead, each bus decides itsown load shedding amount by only relying on limited peer-topeer communication. However, such UFLS strategy may sufferfrom some unexpected cyber-attacks such as integrity attacksand denial of service (DoS) attack. The latter DoS attack aimsto degrade the system performance by jamming or breakingthe communication, which is of high probability to happen inpractical power system. To assess the vulnerability of proposeddistributed UFLS algorithm, the effect of DoS attack on distributed average consensus algorithm is theoretically derived,which indicates that the final consensus value can be estimatedby a given attack probability. It is also investigated that such DoSattack does harm to the load shedding amount and finally affectsthe system frequency performance in the active distributionpower system. Several case studies implemented on an IEEE33-bus active distribution power system are conducted to verifythe effectiveness of the theoretical findings and investigate thevulnerability of the considered power system.

Distributed Event-triggered Secondary Control for Average Bus Voltage Regulation and Proportional Load Sharing of DC Microgrid

This paper proposes a novel distributed event-triggered secondary control method to overcome the drawbacks of primary control for direct current(DC)microgrids.With eventtriggered distributed communication,the proposed control method can achieve system-wide control of parallel distrubted generators(DGs)with two main control objectives:①estimate the average bus voltage and regulate it at the nominal value;②achieve accurate current sharing among the DGs in proportion to their power output ratings.Furthermore,the proposed control strategy can be implemented in a distributed way that shares the required tasks among the DGs.Thus,it shows the advantages of being flexible and scalable.Furthermore,this paper proposes a simple event-triggered condition that does not need extra state estimator.Thus,limited communication among neighbors is required only when the event-triggered condition is satisfied,which significantly reduces the communication burden at the cyber layer.

Freshness constraints of an age of information based event-triggered Kalman consensus filter algorithm over a wireless sensor network

This paper presents the design of a new event-triggered Kalman consensus filter(ET-KCF)algorithm for use over a wireless sensor network(WSN).This algorithm is based on information freshness,which is calculated as the age of information(Aol)of the sampled data.The proposed algorithm integrates the traditional event-triggered mechanism,information freshness calculation method,and Kalman consensus filter(KCF)algorithm to estimate the concentrations of pollutants in the aircraft more efficiently.The proposed method also considers the influence of data packet loss and the aircraft's loss of communication path over the WSN,and presents an Aol-freshness-based threshold selection method for the ET-KCF algorithm,which compares the packet Aol to the minimum average Aol of the system.This method can obviously reduce the energy consumption because the transmission of expired information is reduced.Finally,the convergence of the algorithm is proved using the Lyapunov stability theory and matrix theory.Simulation results show that this algorithm has better fault tolerance compared to the existing KCF and lower power consumption than other ET-KCFs.