Adaptive Output Consensus Research Articles

Output-Feedback-Based Adaptive Leaderless Consensus for Heterogenous Nonlinear Multiagent Systems With Switching Topologies.

This article investigates the leaderless output consensus control problem for a class of nonlinear multiagent systems with heterogenous system orders and unmatched unknown parameters via output-feedback control. The interaction topology among the agents is undirected and jointly connected. Due to the heterogenous system orders and switching topology among the agents, the classical distributed adaptive backstepping-based control technique cannot be applied to solve the problem considered in this article. To solve this issue, a novel distributed reference system is first proposed for each agent, by using only relative outputs of the neighboring agents. Subsequently, a fully distributed reference system-based adaptive leaderless output consensus control scheme is designed via output-feedback control. A remarkable merit of the proposed control scheme lies in that precisely known nonlinear dynamics, system states, distributed parameter estimates, and the states of virtual reference system are no longer needed to be shared with neighbors. This implies that the communication burden can be effectively alleviated, and even the communication network can be replaced by some perception sensors. Finally, two illustrative examples are provided to verify the effectiveness of the proposed control scheme.

Adaptive secure output consensus tracking of linear multi-agent systems via dynamic event-triggered impulsive control under DoS attack

Adaptive secure output consensus tracking of linear multi-agent systems via dynamic event-triggered impulsive control under DoS attack

Quantised adaptive consensus control of heterogeneous nonlinear multi-agent systems under external disturbance

This paper is primarily devoted to the distributed consensus tracking control for heterogeneous nonlinear multi-agent systems (MASs) with a directed communication topology. Taking the considered heterogeneous nonlinear MASs own unknown nonlinear term and quantised input signals, the adaptive radial basis function neural networks (RBFNNs)-based approximator is utilised to tackle these interesting challenges. Next, considering the boundness of disturbances, the upper bound of time-varying disturbance is utilised in the controller design. Then, a distributed dynamic compensator is developed to complete coordination task, which only requires to exchange output information via the communication network. In addition, the compensator transforms the adaptive output consensus problem into asymptotic tracking problem, without needing extra stability conditions. Finally, by means of the Lyapunov stability theory, the satisfying result of the consensus error converging to zero asymptotically can be obtained. Through simulations, the effectiveness of the developed protocol is illustrated.

Adaptive output consensus of heterogeneous nonlinear multi‐agent system under random link failures with partially unknown transition rates

AbstractConsidering the complexity of communication environment in reality, this paper investigates the adaptive output consensus problem for heterogeneous nonlinear multi‐agent system (MAS) under random link failures, in which connection of each link may suffer from link failure. The major challenge lies in dealing with the coupling among different nonlinearities and integrator orders of heterogeneous agents while the distributed communication may fail randomly. Hence, a two‐level distributed adaptive control scheme based on the virtual model‐reference strategy will be presented. In the first level, virtual reference models are constructed to deal with the uncertainties caused by the random link failures, and a distributed consensus control strategy is designed based on the established communication observer of each agent. In the second level, an adaptive backstepping tracking controller drives each agent's output to follow its virtual reference model and compensate for the agent's uncertainties. The mean square stability of the controlled MAS has been rigorously proved. An illustrative example is presented to demonstrate the effectiveness of the given control scheme.

Observer-Based Adaptive Output Consensus for Singular Heterogeneous Multiagent Systems With Input Saturation

Observer-Based Adaptive Output Consensus for Singular Heterogeneous Multiagent Systems With Input Saturation

Adaptive Output Consensus of Heterogeneous Nonlinear Multiagent Systems: A Distributed Dynamic Compensator Approach

Distributed dynamic compensators play a key role in the output consensus problem of heterogeneous nonlinear multi-agent systems. The existing distributed dynamic compensators require the compensators' information to be exchanged through communication networks, and to satisfy additional stability conditions in the controller design. This note proposes a distributed dynamic compensator to address the adaptive output consensus problem of heterogeneous nonlinear multi-agent systems with unknown parameters. The distributed dynamic compensator only requires the output information to be exchanged through communication networks. In addition, the distributed dynamic compensator converts the original consensus problem into asymptotic tracking problem of nonlinear systems, without requiring extra stability conditions in the literature. Then, well-established and standard control approaches are used to design tracking controllers and solve the standard tracking problems. The current work adopts the standard adaptive backstepping approach as an example to design an adaptive tracking controllers. It is further proved that all signals in the closed-loop system are globally uniformly bounded, and the proposed scheme enables the outputs of all agents to track the leader's signal asymptotically. A simulation is presented to illustrate the effectiveness of the design methodology.

Distributed Adaptive Output Consensus of Unknown Heterogeneous Non-Minimum Phase Multi-Agent Systems

This article addresses the leader-following output consensus problem of heterogeneous linear multi-agent systems with unknown agent parameters under directed graphs. The dynamics of followers are allowed to be non-minimum phase with unknown arbitrary individual relative degrees. This is contrary to many existing works on distributed adaptive control schemes where agent dynamics are required to be minimum phase and often of the same relative degree. A distributed adaptive pole placement control scheme is developed, which consists of a distributed observer and an adaptive pole placement control law. It is shown that under the proposed distributed adaptive control scheme, all signals in the closed-loop system are bounded and the outputs of all the followers track the output of the leader asymptotically. The effectiveness of the proposed scheme is demonstrated by one practical example and one numerical example.

Adaptive output consensus of nonlinear fractional-order multi-agent systems: a fractional-order backstepping approach

This paper presents the distributed control design for a class of fractional-order strict-feedback nonlinear multi-agent systems in the presence of unknown dynamics by employing backstepping strategy. Considering that the information of followers’ states are not fully measurable for feedback design, the fractional-order infinite-dimension neural-network state observer is introduced to estimate the unavailable states. The infinite-dimension neuroadaptive laws are also proposed to eliminate the undesirable effects of the unknown nonlinear functions. Besides, based on the Lyapunov fractional-order stability approach and graph theory, unlike the existing results, a distributed neural adaptive observer-based control architecture is designed to ensure that all the closed-loop network signals are ultimately bounded. Finally, a simulation example is given to demonstrate the validity of the proposed control method.

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.

Semi-global Adaptive Bipartite Output Consensus of Multi-agent Systems Subject to Input Saturation and External Disturbance Under Switching Network

Semi-global Adaptive Bipartite Output Consensus of Multi-agent Systems Subject to Input Saturation and External Disturbance Under Switching Network

Adaptive bipartite output consensus for heterogeneous multi-agent systems with quantized information: A fixed-time approach

This paper researches the output consensus problem of heterogeneous linear multi-agent systems with cooperative and antagonistic interactions. Two fixed-time state compensator control approaches, one static dynamic and the other distributed adaptive dynamic, are considered for heterogeneous systems subject to logarithmic quantization. Then, a fixed-time output regulation control protocol is constructed to cope with the problem of bipartite output consensus and adaptive fixed-time output consensus of heterogeneous systems which is fully distributed without any global information. Besides, the fully distributed adaptive algorithm is employed to calculate the system matrix of leader and it’s also effectively eliminated the harmful chattering. Finally, two simulations are carried out to testify the feasibility of theoretical results.

Adaptive output consensus for heterogeneous nonlinear multi-agent systems with multi-type input constraints under switching-directed topologies

This study concentrates on solving the output consensus problem for a class of heterogeneous uncertain nonstrict-feedback nonlinear multi-agent systems under switching-directed communication topologies, in which all followers are subjected to multi-type input constraints such as unknown asymmetric saturation, unknown dead-zone and their integration. A unified representation is presented to overcome the difficulties originating from multi-agent input constraints. Moreover, the uncertain system functions in a non-lower triangular form and the interaction terms among agents are dealt with by exploiting the fuzzy logic systems and their special property. Furthermore, by introducing a nonlinear filter to alleviate the problem of “explosion of complexity” during the backstepping design, a distributed common adaptive control protocol is proposed to ensure that the synchronization errors converge to a small neighborhood of the origin despite the existence of multiple input constraints and arbitrary switching communication topologies. Both stability analysis and simulation results are conducted to show the effectiveness and performance of the proposed control methodology.

Distributed Adaptive Output Consensus for High-Order Multiagent Systems with Input Saturation and Uncertain Nonlinear Dynamics

This paper deals with the leader-following output consensus problem for a class of high-order affine nonlinear strict-feedback multiagent systems with unknown control gains and input saturation under a general directed graph. Nussbaum gain function technique is used to handle the unknown control gains, and the uncertain nonlinear dynamics of each agent is approximated by radial basis function neural networks. Distributed adaptive controllers are designed via the backstepping technique as well as the dynamic surface control approach. It is proved that the closed-loop multiagent systems are semiglobally uniformly ultimately bounded, and the output consensus error can converge to a small region around the origin. Finally, the theoretical results are supported by a numerical simulation.

Distributed Adaptive Consensus of Nonlinear Heterogeneous Agents With Delayed and Sampled Neighbor Measurements.

In this article, the adaptive output consensus problem of high-order nonlinear heterogeneous agents is addressed using only delayed, sampled neighbor output measurements. A class of auxiliary variables is introduced which are n -times differentiable functions and include the agent's output along with delayed, sampled output neighbor measurements. It is proven that if these variables are bounded and regulated to zero then asymptotic consensus among all agent outputs is ensured. In view of this property, an adaptive distributed backstepping design procedure is presented that guarantees boundedness and regulation of the proposed variables. This design procedure ensures not only the desired asymptotic output consensus but also the uniform boundedness of all closed-loop variables. The main feature of our approach is that, in the proposed control law for each agent, the entire state vector of the neighbors is not needed and only delayed sampled measurements of the neighbors' outputs are utilized. The simulation results are also presented that verify our theoretical analysis.

Distributed adaptive output consensus tracking for high-order nonlinear time-varying multi-agent systems with output constraints and actuator faults

This paper studies the problem of adaptive output consensus tracking for a class of high-order nonlinear time-varying multi-agent systems with output constraints, actuator faults and external disturbances. The upper bounds concerning the disturbances and the time-varying stuck faults, and the time-varying parameters are assumed to be unknown. Most importantly, the nonlinear state-dependent function (NSDF) is provided to solve the tracking problem with output constraints, and the dynamic surface control (DSC) technique is used to overcome the iterative derivative of virtual controllers caused by the backstepping design scheme. Next, by modeling the failure of the actuators for all nonlinear subsystems, the actuator faults of all nonlinear subsystems are properly handled. Furthermore, a distributed adaptive controller is proposed to guarantee that the tracking error converges to a small adjustable neighborhood of the origin, and the output constraints are not violated for any nonlinear subsystem. It is also shown that the signals of the closed-loop nonlinear subsystems are bounded. Finally, simulation results illustrate the effectiveness of the proposed control method.

Event-triggered adaptive fuzzy distributed tracking control for uncertain nonlinear multi-agent systems

This paper investigates the issue of distributed adaptive output consensus tracking control for uncertain nonlinear multi-agent systems with undirected graph. It should be mentioned that the reference leader signal is considered to be time-varying and may not be measured. Under the framework of Lyapunov stability theorem and backstepping technique, a novel distributed adaptive consensus control scheme is developed. Under the developed control scheme, each agent can follow the leader if the reference signal can be obtained directly, and the leader signal is estimated to be available if it can not be measured directly. In addition, the controller update is event-driven under well-established event-triggered mechanism, which decreases the communication burden between the agents and the controllers. Finally, with the help of the proposed control strategy, all closed-loop signals are ensured to be bounded and the output consensus tracking aim is achieved. Simulation example verifies the effectiveness of our proposed scheme.

Adaptive bipartite output consensus of heterogeneous linear multi-agent systems with antagonistic interactions

This paper addresses the problem of bipartite output consensus of heterogeneous linear multi-agent systems with antagonistic interactions. The signed graph is directed and structurally balanced. With the assumption that only the leader can access the output of exosystem, two fully distributed adaptive protocols without using the state information of exosystem are designed based on the states and the observers of states, respectively. Numerical simulation demonstrates the effectiveness of the proposed approach.

Distributed adaptive output consensus tracking of nonlinear multi-agent systems via state observer and command filtered backstepping

This paper investigates the adaptive fuzzy output consensus tracking control for nonlinear multi-agent systems in the presence of input saturation. The interaction among the agents is described by a directed graph. Firstly, a local fuzzy state estimator is proposed to reconstruct the unmeasured state of each agent. Then, a novel command filtered backstepping based distributed adaptive control law is designed, where theunknown nonlinear dynamics are approximated by using the fuzzy logic system. The proposed control law can guarantee that the output consensus tracking errors converge into a sufficiently small neighborhood of the origin and all signals in the closed-loop system are bounded although the input saturation exists. Simulation results show the effectiveness of the proposed design.

Command filter based adaptive fuzzy bipartite output consensus tracking of nonlinear coopetition multi-agent systems with input saturation

This paper is concerned with the adaptive bipartite output consensus tracking problem of high-order nonlinear coopetition multi-agent systems with input saturation under a signed directed graph. A distributed fuzzy-based command filtered backstepping scheme is proposed, where the unknown nonlinear dynamics are approximated by the fuzzy logic system (FLS). The errors compensation mechanism is constructed to eliminate the errors caused by filters. Under the proposed control scheme, we only need to design one adaptive law for each agent, and it is proved that the bipartite output tracking errors converge into the desired neighborhood and all the closed-loop signals are bounded although the input saturation exists. Two numerical examples are included to verify the effectiveness of given scheme.

Distributed adaptive output consensus control of a class of uncertain nonlinear multiagents systems

SummaryThis paper addresses the leader‐follower output consensus problem for a class of uncertain nonlinear multiagent systems in a directed communication topology. By employing the backstepping method, the dynamic surface control technique, neutral networks, and the graph theory, a distributed adaptive control scheme is developed recursively for each follower using its own and neighbors' information. The key features of this strategy are that it reduces the computational burden by introducing the dynamic surface control approach and there is no requirement for a priori knowledge about uncertain dynamics of the system. Moreover, in theory, it is proved that the designed control approach can steer the output signals of followers in a directed graph to track the desired trajectory of the leader and guarantee all signals in the closed‐loop system cooperatively semiglobally uniformly ultimately bounded. Furthermore, two examples are included, and the simulation results demonstrate the effectiveness of the proposed strategy.