Adaptive Consensus Tracking Research Articles

Observer‐based adaptive consensus tracking for linear multi‐agent systems with input saturation

This study considers the observer-based consensus tracking problem of linear multi-agent systems with input saturation. Existing observer-based consensus protocols are designed based on an undirected graph, and need global information, such as the network size or eigenvalue information of the Laplacian matrix. In this study, based on only the agent dynamics and the relative outputs of neighbouring agents, an adaptive consensus protocol is proposed by assigning a time-varying coupling weight to each node, and this protocol is independent of any global information and hence is fully distributed. Under the assumptions that each agent is asymptotically null controllable with bounded controls and detectable, and the topological graph has a directed spanning tree with the leader as the root node, semi-global observer-based consensus tracking of multi-agent systems can be reached despite actuator saturation occurring. The results are applied to consensus tracking control of two-mass-spring systems, which are well-known models for vibration in many mechanical systems.

Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems.

Combined with backstepping techniques, an observer-based adaptive consensus tracking control strategy is developed for a class of high-order nonlinear multiagent systems, of which each follower agent is modeled in a semi-strict-feedback form. By constructing the neural network-based state observer for each follower, the proposed consensus control method solves the unmeasurable state problem of high-order nonlinear multiagent systems. The control algorithm can guarantee that all signals of the multiagent system are semi-globally uniformly ultimately bounded and all outputs can synchronously track a reference signal to a desired accuracy. A simulation example is carried out to further demonstrate the effectiveness of the proposed consensus control method.

Robust adaptive consensus tracking for higher‐order multi‐agent uncertain systems with nonlinear dynamics via distributed intermittent communication protocol

SummaryThis paper considers the robust adaptive consensus tracking for higher‐order multi‐agent uncertain systems with nonlinear dynamics via distributed intermittent communication protocol. The main contribution of this work is solving the robust consensus tracking problem without the assumption that the topology among followers is strongly connected and fixed. The focus is the problem of actuator with occasional failure inputs and communication resources constraints. A novel distributed intermittent communication framework is proposed via adaptive approach. In this framework, the underlying communication topologies switch among several directed graphs with a limited directed spanning tree rooted at a leader agent. Furthermore, by introducing a strategy of actuator fault compensation inputs, a combination of robust consensus tracking protocol is designed by the different adaptive feedback controllers. It is proved that the robust adaptive consensus tracking can be achieved by using local states information of neighboring agents if the communication retention rate condition is satisfied. Two examples are presented to demonstrate the effectiveness of the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd.

Distributed adaptive consensus and output tracking of unknown linear systems on directed graphs

This paper considers both the distributed consensus control and output tracking problems of a group of unknown linear subsystems using the relative output information of neighboring subsystems. Each system is a minimum-phase SISO system with relative degree one and unknown parameters, and the interaction graph among the subsystems is directed. For the case where the directed graph is strongly connected, a distributed adaptive protocol is designed to achieve consensus. For the case where there exists an arbitrary constant reference signal, a distributed adaptive controller together with an internal model are presented to achieve output tracking in the sense that the subsystem outputs asymptotically follow a reference constant. The proposed adaptive protocols are independent of the parameters of the subsystems, only use the relative outputs of neighboring subsystems, and hence are fully distributed.

Adaptive output consensus tracking of uncertain multi-agent systems

In this paper, we consider the adaptive output consensus tracking of a class of nonlinear systems in their higherorder strict-feedback form with mismatched parametric uncertainties. The networked group of nonlinear systems has a time-varying reference as a virtual leader, whose output is available to partial agents in the network. The proposed approach features in a design procedure including distributed estimation of group reference and backstepping-based robust consensus tracking control. In the proposed consensus tracking design, each agent estimates the consensus reference through local communications with its neighbours, and makes distributed control decision based on the estimated consensus reference. The proposed approach allows robust consensus tracking in the presence of mismatched model uncertainties, and the tracking performance is characterised by an index showing the effect of the unavailable reference for part of the networked agents. Sufficient conditions are given to ensure bounded output consensus tracking. Simulation results show satisfactory performances.

Adaptive consensus tracking for linear multi‐agent systems with heterogeneous unknown nonlinear dynamics

SummaryThis paper considers the consensus tracking control problem for general linear multi‐agent systems with unknown dynamics in both the leader and all followers. Based on parameterizations of the unknown dynamics of all agents, two decentralized adaptive consensus tracking protocols, respectively, with dynamic and static coupling gains, are proposed to guarantee that the states of all followers converge to the state of the leader. Furthermore, this result is extended to the robust adaptive consensus tracking problem in which there exist parameter uncertainties and Lipschitz‐type disturbances in the network. It is also shown that the parameter estimation errors converge to zero based on contradiction method and Lyapunov function approach. Finally, a simulation example is provided to illustrate the theoretical results. Copyright © 2015 John Wiley & Sons, Ltd.

Adaptive NN consensus tracking control of a class of nonlinear multi-agent systems

This paper proposes a novel robust adaptive consensus tracking control approach for a class of nonlinear multi-agent systems with modeling uncertainties and external disturbances. Radial Basis Function Neural Networks (RBFNNs) are used to approximate the unknown nonlinear function of agent׳s dynamic. Compared with existing NN consensus algorithms of nonlinear multi-agent systems, the proposed consensus control method only needs a small number of adjustable parameters, thus the online computation burden is greatly alleviated. In addition, by online updating the estimation of the NN approximation errors, the proposed consensus control approach can enhance the system robustness against modeling uncertainties. It is proven that all the signals of the multi-agent system are uniformly bounded and the consensus tracking errors converge to a small neighborhood of zero. A simulation is carried out to demonstrate the effectiveness of the proposed control method.

Neural network-based adaptive consensus tracking control for multi-agent systems under actuator faults

In this paper, a distributed output feedback consensus tracking control scheme is proposed for second-order multi-agent systems in the presence of uncertain nonlinear dynamics, external disturbances, input constraints, and partial loss of control effectiveness. The proposed controllers incorporate reduced-order filters to account for the unmeasured states, and the neural networks technique is implemented to approximate the uncertain nonlinear dynamics in the synthesis of control algorithms. In order to compensate the partial loss of actuator effectiveness faults, fault-tolerant parts are included in controllers. Using the Lyapunov approach and graph theory, it is proved that the controllers guarantee a group of agents that simultaneously track a common time-varying state of leader, even when the state of leader is available only to a subset of the members of a group. Simulation results are provided to demonstrate the effectiveness of the proposed consensus tracking method.

Adaptive consensus tracking of high-order nonlinear multi-agent systems with directed communication graphs

This paper studies the adaptive consensus tracking problem for multi-agent systems modeled as high-order integrators with uncertain nonlinear dynamics under directed communication graphs. By parameterizing the unknown dynamics of the agents and the unknown input of the leader, two decentralized tracking control laws are designed using the state information and only the output information, respectively. With state information, globally uniformly ultimately bounded consensus tracking with arbitrarily small tracking errors can be achieved and when only output information is available, based on high-gain observers, semi-global result can be obtained. Numerical examples are provided to illustrate the effectiveness of the controllers.

Distributed consensus tracking of multi-agent systems with nonlinear dynamics under a reference leader

This paper investigates the distributed consensus tracking problem for multi-agent systems with Lipschitz-type dynamics under a reference leader. It is assumed that the leader state information is only available to a subset of followers, while the bounded reference input of the leader’s is unavailable to any follower. To achieve consensus tracking, a class of discontinuous protocols based on the relative information between the neighbouring agents are proposed. Furthermore, as extensions of the former result, the robust and adaptive consensus tracking problems are studied for the case where there exist parameter uncertainties and external disturbances in the network. Finally, the effectiveness of the theoretical result is demonstrated through a network of single-link manipulators.

Robust consensus tracking of multi‐agent systems with uncertain Lur'e‐type non‐linear dynamics

This study addresses the robust consensus tracking problem of multi-agent systems with uncertain Lur'e-type non-linear dynamics under a fixed topology. To achieve consensus tracking, a class of discontinuous control protocols are first proposed, which rely on the relative information among the neighbouring agents. Theoretical analysis indicates that the robust consensus tracking of uncertain Lur'e network can be achieved if the coupling strength and the control gain are both larger than the thresholds depending on some global information of the network. Then, an adaptive consensus tracking protocol is further designed to solve the robust consensus tracking problem as a modification of a fully distributed version without the need of any global information of the multi-agent systems. Furthermore, as an expansion of the discontinuous protocols, a new class of continuous control laws are developed based on the boundary layer concept. Finally, a couple of examples are given to illustrate the effectiveness of the theoretical results.

Distributed adaptive consensus tracking of a class of networked non‐linear systems with parametric uncertainties

This study investigates a distributed adaptive consensus tracking problem for multiple non-linear strict-feedback systems with parametric uncertainties under a directed communication graph topology. It is assumed that the information of a leader is available for only a limited subset of followers. The distributed adaptive dynamic surface design approach is presented to design the local controller of each follower to guarantee that all networked followers with unmatched parametric uncertainties synchronise to the leader regardless of a lack of the shared information on the communication links. From the Lyapunov stability theorem, it is shown that the consensus tracking errors are cooperatively semiglobally uniformly ultimately bounded and converge to an adjustable neighbourhood of the origin.