Relative Output Information Research Articles

Distributed Adaptive Output Feedback Consensus of Parabolic PDE Agents on Undirected Networks.

In this article, we investigate the distributed adaptive consensus problem of parabolic partial differential equation (PDE) agents by output feedback on undirected communication networks, in which two cases of no leader and leader-follower with a leader are taken into account. For the leaderless case, a novel distributed adaptive protocol, namely, the vertex-based protocol, is designed to achieve consensus by taking advantage of the relative output information of itself and its neighbors for any given undirected connected communication graph. For the case of leader-follower, a distributed continuous adaptive controller is put forward to converge the tracking error to a bounded domain by using the Lyapunov function, graph theory, and PDE theory. Furthermore, a corollary that the tracking error tends to zero by replacing the continuous controller with the discontinuous controller is given. Finally, the relevant simulation results are further demonstrated to demonstrate the theoretical results obtained.

Cooperative output feedback consensus control of second-order nonlinear multi-agent systems under Markovian switching topologies

This paper deals with the leader-following consensus problem for a class of second-order nonlinear multi-agent systems by output feedback. The communication topology is characterized by a Markovian switching graph. Firstly, an input-driven observer is introduced to estimate the consensus error of each follower agent. Then, a cooperative nonlinear control law is constructed using the relative output information between neighboring agents by employing the backstepping methodology, which achieves leader-following consensus in mean square sense. Compared with the existing results, the nonlinear functions are required to satisfy polynomial growth condition rather than globally Lipschitz growth or Lipschitz-like growth condition. A numerical example is given to illustrate the theoretical results.

A Low Complexity Robust Output Synchronization Protocol With Prescribed Performance for High-Order Heterogeneous Uncertain MIMO Nonlinear Multiagent Systems

We consider the problem of synchronizing, with prescribed transient and steady-state performance guarantees, the output of high-order, nonlinear, multiagent systems in a leader–following scenario. The agent dynamics are MIMO in lower triangular form and uncertain, as all nonlinearities are unknown and moreover they are perturbed by external additive disturbances. Furthermore, no knowledge is provided regarding bounds or functions bounding the actual system nonlinearities. In addition, the dynamic orders of all agents may not be the same. Each agent utilizes only relative output information from its neighbors and its own state. The underlying communication graph is directed. The proposed control protocol is distributed and of low analytic and computational complexity; thus facilitating implementation. Simulation studies clarify the approach and highlight the theoretical findings.

Containment control of discrete‐time multi‐agent systems with application to escort control of multiple vehicles

AbstractThis article investigates the escort control problem for heterogeneous discrete‐time multi‐agent systems with multiple leaders. We develop a distributed output feedback control law such that the followers are secured within the convex hull spanned by the output of the leaders. First, the followers estimate the target convex hull and the system matrices of the leaders via a distributed observer. We then devise a distributed dynamic output feedback control protocol based on this observer to achieve the escort control by using only neighboring relative output information of leaders. The security of the followers is guaranteed by seeing that the output tracking errors converge to zero exponentially. In the numerical simulations, we discuss the potential deployment of the proposed method to a brand‐new escort control of mixed traffic consist of connected automated vehicles and partially automated vehicles. This vehicular escort control formulation can be regarded as a generalization of the conventional vehicular platoon control problem into both longitudinal and lateral dimensions. The numerical results validate the effectiveness and the computational feasibility of the proposed control protocols.

Distributed event-triggered for adaptive neural network containment control of uncertain Euler–Lagrange systems with external disturbances

This paper investigates the containment control problem for multiple Euler–Lagrange systems with unknown time-varying disturbances over directed graphs, in which the dynamics of leaders and followers are heterogeneous. First of all, the expected output signals of leaders can only be acquired by some subsystems owing to the limited communication conditions, and the output adjustment errors are obtained indirectly by other subsystems through the network connection. In consequence, a compensator based on relative output information is designed to estimate a trajectory inside the convex hull spanned by states of the leaders. Second, a fully distributed event-triggered adaptive control scheme is proposed, and a disturbance estimator is designed to achieve interference suppression. In addition, the design of the overall control protocol does not use the relative speed of the followers. Finally, a dual-axis manipulator is taken as an example to validate the effectiveness of the proposed control scheme.

Sampled-data observer based event-triggered leader-follower consensus for uncertain nonlinear multi-agent systems☆

This paper addresses the event-triggered output feedback consensus problem for feedforward nonlinear multi-agent systems with a directed topology graph. To avoid continuous monitoring and communication among agents, the periodic sampled-based output information is adopted to construct the observer. The observer-based controller for every agent updates under a newly designed triggering mechanism, which relies on its output and the relative output information of its neighbour agents at sampling points. With the designed event-triggered control protocol, the leader-follower consensus is achieved and the Zeno behavior is excluded effectively. Moreover, the sampling period and state delay of the considered system can be arbitrary positive numbers. Finally, the consensus result is extended to a class of feedforward multi-agent systems with the system nonlinearities satisfying the increment ratio of an unbounded time-varying function. A simulation example with two cases is given to demonstrate the proposed event-triggered control protocols.

Consensus tracking for singular multi‐agent systems with Lipschitz nonlinear dynamics and external disturbances

AbstractThe consensus tracking control problem for singular multi‐agent systems (SMASs) with Lipschitz nonlinearities and unknown disturbances is investigated. An extended state observer using only the relative output information is introduced and then a distributed consensus protocol is proposed, whose performance is analyzed using matrix analysis, singular system theory and Lyapunov stability theory. Sufficient conditions for ensuring consensus tracking with disturbance rejection of linear and Lipschitz nonlinear SMASs are, respectively, obtained under directed networks. Specifically, an equivalent formulation of achieving consensus tracking for SMASs is established, and the design procedures of gain matrices in the proposed consensus protocols are presented by the linear matrix inequality solver. Finally, simulation examples are provided to illustrate the theoretical results.

Event-Triggered Control for Consensus Tracking With Relative Output Information

This brief studies event-triggered control problem for consensus tracking based only on relative output information. First, with the sporadic relative outputs, an event-triggered observer is designed to estimate the relative states. Second, based on the intermittent estimate, an event-sampled controller is constructed to achieve the consensus tracking. Compared with the existing observer-based protocols that are designed with absolute outputs to reconstruct each agent’s states, the current protocol is born to have two fascinating features. First, the relative states rather than agent’s states are estimated, and meanwhile no observer information is inter-exchanged through network. This structure can not only save communication resources, but also reduce the possibility of encountering cyber attacks. Second, the triggering instants associated with observer and controller are independent, showing that the updates of observer and controller are asynchronous. Numerical simulation illustrates the proposed control approach.

Adaptive consensus control for a class of nonlinear multi-agent systems with unknown time delays and external disturbances

This paper investigates a class of unknown nonlinear multi-agent systems with unknown time delays and external disturbances. The external disturbance considered in this paper is completely unknown, and the accurate mathematical expression cannot be obtained. To eliminate the external disturbance, a disturbance observer is constructed by the Disturbance-Observer-Based-Control (DOBC) method. By utilizing Young’s inequality scaling technique, the problem of time delay is solved. By assuming that the communication graph among the agents is directed and connected, a novel distributed adaptive consensus control protocol is established based on the relative output information to achieve the goal of consensus control. Furthermore, the stability of the multi-agent system is analyzed by selecting an appropriate Lyapunov function; it is certified that with the proposed control protocol, all signals are guaranteed to be globally uniformly bounded, and the considered multi-agent systems can reach consensus even in the presence of time delay and external disturbance. Finally, two simulation examples are given to support the proposed control strategy.

Adaptive bipartite output consensus of nonlinear fractional-order multi-agent systems

A distributed control approach is proposed for a class of fractional-order multi-agent systems with unknown nonlinearities under signed bipartite digraphs. Unlike the existing results, the follower's dynamics are studied with strict-feedback fractional-order form as well as a general class of actuator faults with unknown magnitude, pattern and occurrence time is studied. To provide a simple and efficient control strategy, first a novel command fractional-order filter based on the backstepping design is proposed such that the difficulty of calculation of the fractional derivative order of the virtual control laws is removed, as well as improving the bipartite output consensus accuracy. Then, to cope with dynamic's uncertainties, the proposed method is integrated with adaptive neural approximator and minimal learning parameter scheme which reduces communication loads. Besides, a distributed fault compensation protocol based upon the proposed command fractional-order filter and relative output information of neighbours' agents is extended to ensure bipartite output consensus, without relying on any global information of the singed digraph as well as any explicit fault detection mechanism. Finally, it is guaranteed that all the error signals within the closed-loop network system are converged into adjustable compact sets around the origin. The simulation results verify the validity of the presented control approach.

Adaptive Active Disturbance Rejection Control for Rendezvous of a Swarm of Drones

This paper addresses the time-varying rendezvous problem of a swarm of drones with the leader-follower consensus hierarchy. Each drone in the swarm is under the influence of external disturbances in the form of wind gusts. To control the swarm of perturbed drones, this paper proposes a fully distributed adaptive leader-following time-varying disturbance rejection pinning control for the rendezvous of drones using the framework of the extended state observer that depends on the state estimates of the neighboring agents rather than the actual states. The communication topology within the swarm is modelled using algebraic graph theory. Unlike most of the literature in which the leader agent act as a virtual reference generator, an active leader agent with non-zero control input is considered. The states of the leader drone are only available to a subset of the graph. The communication topology between leader-follower is directed while that between follower-follower is undirected. Based on the relative output information between the neighboring drones, the extended state observer estimates the local states and disturbances of each drone and the adaptive control actively compensates for the external disturbances simultaneously. Finally, it is shown analytically as well as in simulations that the time-varying rendezvous can be achieved by the proposed algorithm effectively.

Robust Distributed Sensor Fault Detection and Diagnosis Within Formation Control of Multiagent Systems

This paper investigates the fault detection and diagnosis (FDD) problem for multiagent systems subject to sensor faults and disturbances. A distributed proportional integral derivative formation control protocol is constructed to achieve practical formation. A distributed FDD scheme, comprised of a fault detection module, a fault isolation module, and a fault estimation module, is designed within the formation control. For fault detection, the relationship between residuals and sensor faults in the multiagent systems is established such that each agent can detect the faults of all agents. For fault isolation, the distributed observer in each agent can determine whether the fault is in itself or its neighbors. Utilizing the absolute output information of each agent and the relative output information among neighboring agents, a distributed fault estimator is derived to provide the fault magnitude information. Simulation results are presented to demonstrate the effectiveness of the proposed FDD scheme.

Resilient observer design of sensor fault estimation for discrete‐time multi‐agent systems: A distributed approach

AbstractIn this article, the issue of distributed sensor fault estimation with resilient property is studied for a class of multi‐agent systems. Based on the relative output information, a novel fault estimation design is presented to estimate sensor fault and state vectors simultaneously. Meanwhile, the variation of observer gain is considered to improve the robustness of fault estimation observer. Furthermore, robust performance is used to suppress the influence of external interference on sensor fault estimation error. Finally, simulations are provided to present effectiveness of the developed approach.

Reset output feedback control of cluster linear multi-agent systems

In this study, the distributed output consensus control issue is investigated for a class of linear cluster multi-agent systems (CMASs) under the control strategy of the reset observer. We consider a communication network consisting of several clusters, each of which is directed and contains a leader. The interactions among agents include continuous-discrete hybrid communication. Specifically, an instantaneous connectivity only exists between the clusters at discrete moments, called the reset time sequence. At the reset time, an instantaneous fixed directed network is formed such that only the leaders will consider the available information of neighboring leaders to reset their own states. During non-reset intervals, only the intra-clusters are connected while the inter-clusters are equivalent to a disconnected network topology. Considering that in practice, the state information may be partially unavailable, only the relative output information is utilized to estimate the unavailable state and thus control protocols are developed with the help of the reset full-order and reduced-order observers, respectively. The stability of the closed-loop CMAS at both the reset time and non-reset intervals is studied based on Lyapunov analysis. The consensus value depends only on the initial conditions and the network topology involved, and not on the reset time sequence. Finally, numerical simulations are provided to illustrate the theoretical results.

Distributed Containment Control of MIMO Pure-Feedback Multiagent Systems Using Filter-Driven-Approximation Approach

This article addresses a filter-driven-approximation (FDA)-based design problem for the distributed containment control of multi-input-multi-output pure-feedback multiagent systems with completely unknown nonlinearities. Local filter-driven approximators are designed to compensate for unknown nonaffine nonlinear functions lumped in the local controller design procedure where the first-order filtered signals of the error surfaces, state variables, and control inputs are linearly combined for the design of the filter-driven approximators. A containment control scheme using the filter-driven function approximators is recursively constructed to ensure that the outputs of the followers converge to the convex hull spanned by multiple time-varying leaders. Compared with existing containment control results using adaptive neural-network-based or fuzzy-based approximators, the proposed FDA-based containment control scheme depends only on the relative output information among agents and does not require any adaptive techniques. Thus, the proposed control structure can be simplified. It is shown that the closed-loop signals, including approximation errors are semi-globally uniformly ultimately bounded. Simulation examples are provided to validate the effectiveness of the proposed theoretical strategy.

Output Feedback Predefined-Time Bipartite Consensus Control for High-Order Nonlinear Multiagent Systems

This paper concerns the predefined-time bipartite consensus control for uncertain nonlinear multiagent systems under a signed directed topology. All agents have high-order uncertain nonlinear dynamic characteristics satisfying a time-varying Lipschitz growth condition, and their partial state information is not available for measurement. In this case, we put forward a novel output-feedback-based predefined-time leader-following bipartite consensus control strategy. A predefined-time compensator for each follower is firstly constructed with a time-varying gain by utilizing its relative output information. Then, a novel linear-like output feedback predefined-time distributed control protocol is developed for each follower by means of the compensator. By making two artful state transitions, the bipartite consensus problem is reduced to a stabilization one of nonlinear systems. By means of the Lyapunov stability theorem, we strictly prove that the designed controllers can ensure that all agents realize bipartite consensus in predefined time. Finally, two simulation examples are given to validate the viability of the developed theoretical algorithm.

Distributed Adaptive Consensus of Parabolic PDE Agents on Switching Graphs With Relative Output Information

This article mainly solves the consensus issue of parabolic partial differential equation (PDE) agents with switching topology by output feedback. A novel edge-based adaptive control protocol is designed to reach consensus under the condition that the switching graphs are always connected at any switching instants. Different from the existing adaptive protocol associated with partial differential dynamics, the proposed adaptive observer-type law relies on the relative output information rather than relative state information. A proper Lyapunov functional is constructed and some important lemmas are used, then a sufficient condition is obtained for the consensus of parabolic PDE agents on switching graphs. Besides, a corollary about the distributed adaptive consensus of parabolic PDE agents on fixed undirected communication networks is given. Finally, the theoretical results are demonstrated by two numerical simulations.

Consensus of Linear MIMO Multiagent Systems: Appointed-Time Reduced-Order Observer-Based Protocols.

This article is devoted to designing distributed adaptive attack-free protocols for the consensus of linear multi-input multioutput multiagent systems under directed graphs, where the appointed-time reduced-order observers are proposed based only upon the relative output information among neighboring agents. One of the distinguishing features of the attack-free protocols lies in the prohibition on information transmission via the communication channel. By viewing the relative control input as the unknown input on the dynamics of each agent, a class of new unknown input observers is introduced with only the relative output measurement involved. The appointed-time estimation of the consensus error is achieved by utilizing jump discontinuity in the observer design and employing the property of the nilpotent matrix. Moreover, a linear transformation is made on the system of consensus error to realize the observer order reduction. Both theoretical analysis and simulation illustration are presented to reveal the effectiveness of the proposed attack-free 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.

Distributed Fault Detection for Linear Time-Varying Multi-Agent Systems With Relative Output Information

This paper investigates the distributed fault detection problem for linear discrete time-varying heterogeneous multi-agent systems under relative output information. Due to the lack of absolute outputs, an augmented model is built by stacking all local relative output information. Then, the fault detection problem consisting of residual-generation and residual-evaluation is handled using the H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> filtering framework. The residual-generation problem is actually a minimization problem of an indefinite quadratic form, and the Krein space-Kalman filtering theory is applied, which results in a low computational burden despite the time-varying characteristic. Using the Krein space theory, a necessary and sufficient condition for the minimum is derived, and a residual-generation algorithm is developed. Further, a residual-evaluation mechanism is designed by constructing an evaluation function and detecting faults by comparing it with a threshold. Finally, two illustrative examples are given to demonstrate the effectiveness of the proposed fault detection approach.