Consensus Error Research Articles

Adaptive Leader-Follower Consensus Control of Multiple Flexible Manipulators With Actuator Failures and Parameter Uncertainties

In this paper, the leader-follower consensus problem for a multiple flexible manipulator network with actuator failures, parameter uncertainties, and unknown time-varying boundary disturbances is addressed. The purpose of this study is to develop distributed controllers utilizing local interactive protocols that not only suppress the vibration of each flexible manipulator but also achieve consensus on joint angle position between actual followers and the virtual leader. Following the accomplishment of the reconstruction of the fault terms and parameter uncertainties, the adaptive neural network method and parameter estimation technique are employed to compensate for unknown items and bounded disturbances. Furthermore, the Lyapunov stability theory is used to demonstrate that followers' angle consensus errors and vibration deflections in closed-loop systems are uniformly ultimately bounded. Finally, the numerical simulation results confirm the efficacy of the proposed controllers.

An Operator-Theoretic Approach to Robust Event-Triggered Control of Network Systems With Frequency-Domain Uncertainties

In this paper, we study the robustness of the event-triggered consensus algorithms against frequency- domain uncertainties. It is revealed that the sampling errors resulted by event triggering are essentially images of linear finite-gain L2-stable operators acting on the consensus errors of the sampled states and the event-triggered mechanism is equivalent to a negative feedback loop introduced additionally to the feedback system. In virtue of this, the robust consensus problem of the event-triggered network systems subject to additive dynamic uncertainties and network multiplicative uncertainties are considered, respectively. In both cases, quantitative relationships among the parameters of the controllers, the Laplacian matrix of the network topology, and the robustness against aperiodic event triggering and frequency-domain uncertainties are unveiled. Furthermore, the event-triggered dynamic average consensus (DAC) problem is also investigated, wherein the sampling errors are shown to be images of nonlinear finite-gain operators. The robust performance of the proposed DAC algorithm is analyzed, which indicates that the robustness and the performance are negative

Leader-following consensus of semi-Markov jump nonlinear multi-agent systems under hybrid cyber-attacks

In this paper, the leader-following consensus issue is investigated for a class of nonlinear multi-agent systems with semi-Markov parameters subject to hybrid cyber-attacks. A semi-Markov chain is adopted to describe the variation of switching topologies caused by the complexity of the environment and makes the studied problem more general. Hybrid cyber-attacks consisting of denial-of-service attacks and deception attacks are described with the help of two groups of Bernoulli sequences which are assumed to be independent of each other. On this basis, a sufficient condition for the stability of the consensus error system is established by using linear matrix inequality techniques. Finally, the validity of the results obtained is verified by two numerical examples.

Event-Triggered Sliding Mode Neural Network Controller Design for Heterogeneous Multi-Agent Systems

A class of heterogeneous second-order multi-agent consensus problems is studied, in which an event-triggered method is used to improve the feasibility of the control protocol. The sliding mode control method is used to achieve the robustness of the system. A special type of general radial basis function neural network is applied to estimate the uncertainties. The event-triggered mechanism is introduced to reduce the update frequency of the controller and the communication frequency among the agents. Zeno behavior is avoided by ensuring a lower bound between two adjacent trigger instants. Finally, the simulation results are provided to demonstrate that the time evolution of consensus errors eventually approaches zero. The consensus of multi-agent systems is achieved.

Fixed-time connectivity-preserving consensus of periodically disturbed nonlinear multi-agent systems with limited communication ranges

This paper concentrates on the fixed-time consensus control problem with preserved connectivity for periodically disturbed nonlinear multi-agent systems with limited communication ranges. The dynamics model of the considered multi-agent systems is general, in which the periodically time-varying disturbance appears in the unknown system function in a nonlinear fashion. The Fourier series expansion-radial basis function neural network-based approximator is incorporated to describe the unknown disturbed functions. In consideration of the limited communication ranges, a unified error transformation is utilized to preserve the initial connectivity. Then, via the backstepping method, a consensus control scheme is recursively constructed to guarantee that the consensus errors fall into a small region around the origin in fixed time, and the connectivity preservation is ensured simultaneously. In simulation part, the consensus trajectories, consensus errors and the results of connectivity preservation are provided. The simulation results demonstrate the capability of the proposed control strategy in achieving connectivity-preserving consensus in fixed time.

Accurate Post-Calibration Predictions for Noninvasive Glucose Measurements in People Using Confocal Raman Spectroscopy.

In diabetes prevention and care, invasiveness of glucose measurement impedes efficient therapy and hampers the identification of people at risk. Lack of calibration stability in non-invasive technology has confined the field to short-term proof of principle. Addressing this challenge, we demonstrate the first practical use of a Raman-based and portable non-invasive glucose monitoring device used for at least 15 days following calibration. In a home-based clinical study involving 160 subjects with diabetes, the largest of its kind to our knowledge, we find that the measurement accuracy is insensitive to age, sex, and skin color. A subset of subjects with type 2 diabetes highlights promising real-life results with 99.8% of measurements within A + B zones in the consensus error grid and a mean absolute relative difference of 14.3%. By overcoming the problem of calibration stability, we remove the lingering uncertainty about the practical use of non-invasive glucose monitoring, boding a new, non-invasive era in diabetes monitoring.

Numerical and clinical precision in hypoglycemia of the intermittent FreeStyle Libre glucose monitoring through an NFC-Bluetooth transmitter associated with the xDrip+ algorithm in diabetic patients under insulin therapy

IntroductionThere are data capture devices that attach to the FreeStyle Libre sensor and convert its communication from NFC (Near-field communication) to Bluetooth technology, generating real-time continuous glucose monitoring. The accuracy of hypoglycemia measurements displayed by smartphone apps using this device has not been established. MethodsStudy of diagnostic tests. Numerical accuracy was evaluated, utilizing the absolute difference with respect to capillary glucometry (ISO 15197:2015 standard) and clinical accuracy, using the Clarke and Parkes (Consensus) error grids, for glucose measurements less than 70mg/dL performed with the FreeStyle Libre system and with the digital estimation xDrip+ app, in diabetic patients managed with insulin therapy. ResultsTwenty-seven patients were included (TIR 73.4%, TBR70 5.6%), who contributed 83 hypoglycemic events. Numerical accuracy was adequate in similar proportions with the FreeStyle Libre system compared to the xDrip+ app (81.92% vs. 68.67%, p=0.0630). The clinical accuracy evaluation showed that 92.8% of the measurements for xDrip+ and 98.8% for FreeStyle libre met the criteria according to the Parkes (Consensus) grid (p=0.0535); and 79.5% and 91.6% of the measurements met the criteria according to the Clarke grid (p=0.0273), being higher with FreeStyle libre. ConclusionsThe use of the NFC-Bluetooth transmitter (Miao-Miao) associated with the xDrip+ app does not improve numerical or clinical accuracy for detecting hypoglycemic events in diabetic patients managed with insulin therapy, compared to the FreeStyle Libre device.

Prescribed-Time Performance Recovery Fault Tolerant Control of Platoon With Nominal Constraints Guarantee

The specific restrictions are breached in the case of vehicle platoon faults and result in unacceptable system performance degradation. This paper proposed a novel prescribed time performance recovery fault tolerant control method to ensure nominal platoon performance under multiple faults, including actuator faults with deferred backup actuator switching and leader-follower link faults in consideration. A novel barrier function based prescribed time sliding mode controller is devised to assure platoon consensus errors and convergence time within prescribed constraints under normal conditions at first. Under multiple faults conditions, to tackle with leader-follower link faults problem, a novel distributed recursive estimator is proposed to estimate the leader’s states and recover the previous leader-follower platooning control protocol in a prescribed time. Besides, in the presence of actuator failures, the nominal constraints violated problem under faults is put into consideration. Owing to the unavoidable deferred actuator replacement time, the previous platoon consensus error constraints are violated and cause platoon performance degradation. Under such circumstances, by exploiting one novel barrier function-based sliding mode controller with an error shifting function, the unfavorable exceeding platoon consensus errors can be recovered into the nominal constraints domains within a prescribed time. Numerical simulations and hardware-in-loop (HIL) experiments are demonstrated to validate the effectiveness and superiority of our performance recovery fault tolerant control algorithms.

Distributed Adaptive Attitude Takeover Control of Failed Spacecraft With Parameters Identification

The attitude takeover control and parameter identification for reclaiming a spacecraft with a failed attitude control system (ACS) by multiple small satellites are investigated in this brief. A distributed adaptive control law based on the concurrent learning method is proposed, which can generate the attitude control command and identify the inertia matrix of the combined spacecraft in a distributed way. In this method, each small satellite calculates its own command torque and estimates the total torque applied to the combined spacecraft to identify the inertia matrix. To reduce consensus errors of inertia matrix identifications and the torque estimation errors, a compensation term based on parameter interaction is introduced in the adaptive law. Finally, numerical simulations are carried out to illustrate the effectiveness of the distributed adaptive control law.

Distributed Observer-Based Adaptive Fuzzy Consensus of Nonlinear Multiagent Systems Under DoS Attacks and Output Disturbance.

This article studies the adaptive output-feedback consensus control problem of nonlinear multiagent systems (MASs) against denial-of-service (DoS) attacks. The attacks on the edges instead of nodes are considered, where we allow different attack intensities but at least one edge is connected in each attacking interval. Affected by output disturbance, the sensor feedback signal of every agent is inaccurate, which will reduce the approximation accuracy of the observer. Then, we design a signal to revise the sensor feedback signal subject to disturbance. Meanwhile, a prescribed performance function is used to ensure the transient and steady-state performance of error. Leveraging the Lyapunov stability theory and the backstepping technique, a distributed output-feedback control scheme subject to asymmetric saturation nonlinearity is designed. For the asymmetric input saturation, an auxiliary signal is designed to simplify the designed progress of controller input. To deal with the inherent problem of "explosion of complexity" emerging with backstepping, dynamic surface control is utilized. It is proved that the consensus errors converge to small neighborhoods of the origin, and all signals within the closed-loop system are bounded. Finally, simulation results are offered to demonstrate the effectiveness of the proposed method.

Fuzzy Observer-Based Consensus Tracking Control for Fractional-Order Multi-Agent Systems Under Cyber-Attacks and Its Application to Electronic Circuits

Consensus control of multi-agent systems (MASs) has applications in various domains. As MASs work in networked environments, their security control becomes critically desirable in response to cyber-attacks. In this paper, the observer-based consensus tracking control problem is investigated for a class of Takagi-Sugeno fuzzy fractional-order multi-agent systems (FOMASs) under cyber-attacks. The malicious cyber attacks can impact the security of topologies of the communication networks of both controllers and observers. To estimate unmeasurable system states, a fuzzy observer is built. It is found that the topology of contact for observer states may be different from that of the feedback signals. A novel mathematical model for T-S fuzzy FOMASs with cyber-attacks is proposed. By using algebraic graph theory, Lyapunov functional, and fractional calculus theory, a distributed feed-back controller is developed for each agent, which guarantee the secure performance of tracking consensus error and observer error. Finally, two numerical examples demonstrate the effectiveness of the suggested control scheme, and the controller design for electronic network circuits shows the applicability of the proposed theoretical results. Simulations results for different differential-orders and coupling strength scenarios are given.

Reset Event-Triggered Adaptive Fuzzy Consensus for Nonlinear Fractional-Order Multiagent Systems With Actuator Faults.

This article studies the problem of event-triggered adaptive fault-tolerant fuzzy output feedback consensus tracking control for nonlinear fractional-order multiagent systems with actuator failures under a directed graph. Considering the fact that the actual system works near the equilibrium point most of the time, a novel dynamic event-triggering strategy with the reset mechanism is proposed, where the dynamic threshold can be actively adjusted according to the preset conditions, so that the resource utilization can be further reduced. Based on an improved event-based consensus error, the state estimator about the derivative of reference trajectory and the adaptive law about the information of graph are constructed, which makes distributed consensus tracking control achieved without obtaining global information. Then, by introducing two adaptive compensating terms to deal with actuator failures and event-triggered measurement errors, it is shown in the sense of fractional-order stability criterion that tracking errors can converge to a compact set even if the fault parameters and modes are completely unknown. Finally, the correctness of the presented method is verified by a simulation example.

Three-dimensional event-triggered fixed-time cooperative guidance law against maneuvering target with the constraint of relative impact angles

In order to improve the flexibility and reduce the energy consumption of cooperative guidance laws considering the impact angle constraint, this paper proposes a three-dimensional event-triggered fixed-time cooperative guidance law with the constraint of relative impact angles. First, for the purpose of avoiding the precision degradation due to the estimation error of time-to-go especially facing a maneuvering target, the range-to-go and velocity along the line-of-sight (LOS) are taken as the coordination variables for achieving time-cooperative guidance. Secondly, instead of assigning specific desired impact angles for each missile, only the consensus errors of relative impact angles are utilized as the coordination variables for achieving space-cooperative guidance, which can avoid continually maneuvering for maintaining the constant desired impact angles, thus reducing the fuel consumption. Next, the guidance laws along the LOS and perpendicular to the LOS are developed, and the event-triggering mechanisms are designed to reduce the update frequency of cooperative guidance commands, thus further reducing the energy consumption. To guarantee the convergence rate, the fixed-time control theory is adopted and the stability of proposed event-triggered cooperative guidance laws are rigorously proved. In addition, it is also proved that there is no Zeno behavior when implementing the proposed event-triggered cooperative guidance laws. Finally, numerical simulations indicate that the strictly simultaneous attack is achieved and the constraint of relative impact angles is satisfied. Comparative studies demonstrate that the computation burden of cooperative guidance commands is relaxed and the fuel consumption is reduced by the proposed event-triggered cooperative guidance laws with the constraint of relative impact angles.

Adaptive event-triggered fault-tolerant consensus of linear heterogeneous multiagent systems via hierarchical approach

This article investigates the event-triggered fault-tolerant consensus problem for heterogeneous linear multiagent systems (MASs) with actuator failures. By introducing the hierarchical control scheme, a distributed adaptive event-triggered fault-tolerant control method is proposed. The upper layer and the lower layer comprise the hierarchical control structure. The upper layer is made up of a virtual reference system and a distributed cooperative controller with event-triggered mechanism, while the lower layer is composed of an actual system and a fault-tolerant tracking controller. The main contribution of this work is that the phenomena of fault propagation could be prevented employing presented control method when compared to the most commonly used distributed fault-tolerant control methods. And continuous transmission between agents can be eliminated due to the event-triggered mechanism. It is shown that the consensus error converges to zero asymptotically. Finally, the effectiveness of the theoretical result is illustrated by a simulation example.

Novel Control Theoretic Consensus-Based Time Synchronization Algorithm for WSN in Industrial Applications: Convergence Analysis and Performance Characterization

Fourth Industrial Revolution (IR4.0) depends heavily on the Internet of Things (IoT) and wireless sensor networks (WSNs). Through WSN, data in an industrial environment can be captured. Time synchronization is an important issue in WSN to ensure the correct sequence of the data collected. Besides, gauging on a common perceived time reference, local clocks on each node within any interconnected WSN should be able to initiate message exchanges. Referencing to an unsynchronized value of virtual global reference clock will render the nodes’ communication and applications in WSN useless. In this work, a newly improved control theoretic consensus-based time synchronization algorithm for WSN known as time synchronization using sliding-mode control and proportional, integral, and derivative (TSMPID) is proposed. The novel algorithm uses an augmented sliding-mode control (SMC) in the skew and relative skew estimation schemes, which is a useful switching action, to provide a salient feature in guaranteeing finite-time convergence in synchronized virtual time clock estimation. A proportional, integral, and derivative (PID) term has been introduced in the offset estimation to improve the estimation performance. The main purpose is to achieve global clock synchronization with lower computational effort and reduced synchronization error. TSMPID has the characteristics of being totally distributed, asynchronous, scalable across different network topological structures and robust to ad hoc nodes deployment. Ad hoc communication link node deployment scenarios are simulated comprising five, seven, and nine WSN nodes. TSMPID requires low energy and exhibits a much lesser consensus error spike in comparison to other recent prior-art time synchronization schemes.

Iterative learning consensus control of nonlinear impulsive distributed parameter multi-agent systems

This paper studies the consensus control of nonlinear impulsive distributed parameter multi-agent systems (IDPMASs), whose dynamic behavior depends on time and space. First, to achieve the complete consensus for nonlinear parabolic IDPMAS, a distributed P-type iterative learning consensus control protocol is proposed that includes network topologies information and nearest neighbor knowledge. Using impulsive Gronwall inequality and mild solution formula based on operator semigroup, the rigorous convergence analysis of consensus errors is provided, and convergence conditions are established as well. Furthermore, the consensus control of nonlinear second-order hyperbolic IDPMAS is investigated that employ an open-closed-loop P-type consensus control protocol, which uses both currents iterative consensus error and last iterative consensus error. The theoretical result of this paper shows the consensus errors between any 2 agents can converge to 0 with the increase in iterations under given conditions. Finally, two numerical simulations are given to demonstrate the effectiveness of the proposed methods.

Distributed Adaptive Tracking Control for High-Order Nonlinear Multiagent Systems Over Event-Triggered Communication

In this article, we investigate the consensus problem for high-order nonlinear multiagent systems (MASs) with an uncertain leader under event-triggered communication. Compared with the existing consensus results for nonlinear MASs under event-triggered communication, the class of systems considered is more general, while achieving better performance in term of asymptotic tracking. To estimate the unknown parameters of the uncertain leader, distributed intermediate parameter estimators based on event-triggered communication mechanism are first introduced. To guarantee that high-order derivatives exist when applying the backstepping method, such estimators are further modified to obtain final estimators having a polynomial form by using the Hermite interpolation method. Moreover, novel high-order filters are proposed to generate local reference signals and to ensure the existence of high-order derivatives of the filter states. Based on the developed filters, a backstepping-based decentralized adaptive controller is developed. It is proved that consensus errors are asymptotically convergent with the developed method. Finally, simulation examples are provided to show the effectiveness of the proposed method.

Finite-Time Distributed Control of Nonlinear Multiagent Systems via Funnel Technique

This article investigates the finite-time distributed adaptive consensus for nonlinear uncertain multiagent systems (MASs). The performance of the consensus errors can be prespecified in a funnel sense. Three achievements make this work depart from available results on prespecified performance and funnel control: first, a novel error transformation is constructed to prespecify the performance, which avoids the singularity problem pointed out in the literature in the differentiation of the control law; second, the funnel control method is extended in a MAS setting by suitably modifying the backstepping technique in a power integrator sense; and third, it is shown that finite-time stability notions can be attained without extra complexity being involved in the design. Stability analysis and comparative simulations demonstrate the method.

Prescribed Performance-Based Finite-Time Consensus Technology of Nonlinear Multiagent Systems and Application to FDPs

This brief focuses on an adaptive bipartite consensus issue for nonlinear multi-agent systems (MASs) over signed digraphs from a new way. A new distributed control algorithm, named finite-time prescribed performance control is designed by applying prescribed performance function (PPF) and a novel first-order filter, which not only guarantees that the bipartite consensus errors converge to a prescribed compact set at a finite time, as well as enables the system to achieve the prescribed performance and fast finite time convergence. Furthermore, the neural networks (NNs) are introduced to deal with the continuous unknown nonlinearity and the effect of non-strict feedback structure that exist in the system, and the dynamic surface control (DSC) mechanism applying a novel first-order filter is used to overcome the “explosion of complexity” problem during a controller design process. Simulation experiment of forced damped pendulums (FDPs) is included to show the feasibility of the theoretical works.

An event-triggered distributed cooperative guidance law for simultaneous attack with autopilot lag consideration

This article proposes an event-triggered distributed cooperative guidance law for multiple missiles to simultaneously attack a stationary target with consideration of autopilot lag and unknown disturbances. In order to achieve a consensus on each missile’s impact time and save communication costs, the guidance law is designed on the basis of an auxiliary variable consisting of the time-to-go expression and its time derivative. Driven by the properly designed event-triggered mechanism, the information interaction among missiles performs in a need-based scheme and there is no need to continuously monitor the consensus errors between neighbor missiles. By this means, the communication burden is significantly reduced while satisfactory guidance performance is still guaranteed. The proposed guidance law can be extended to a communication failure case where one of the missiles suddenly cannot receive information from its neighbors. An integral sliding mode controller is integrated with the nominal guidance law to eliminate the adverse effects caused by unknown disturbances. Numerical simulations are carried out to illustrate the effectiveness of the proposed guidance design.