Simplified reinforcement learning-based distributed consensus neural network control for second-order uncertain nonlinear multi-agent systems

This paper studies the event-triggered consensus problem of second-order uncertain nonlinear multi-agent systems (MASs). Based on the local sampled measurement information, we propose an adaptive event-triggered consensus algorithm. The adaptive algorithm estimates not only the uncertain parameters of agent dynamics but also the global topology information. Hence, our consensus algorithm does not rely on global topology information, that is, the proposed consensus algorithm is full distributed. Moreover, we prove that Zeno behavior is ruled out. Finally, a simulation is given to verify the effectiveness of the proposed algorithm.

A novel decentralized control approach for second-order uncertain nonlinear multi-agent systems is presented. The communication topology of the multi-agent system that describes completely unknown nonlinear dynamics and unmeasured states is described by a directed graph. The proposed decentralized control algorithm is developed based on high-gain observer theory and fuzzy adaptive control algorithm. The high-gain observer is introduced to estimate the agents' unmeasured states. The fuzzy logic systems are used as the approximator to deal with the nonlinear unknown dynamics. By the Lyapunov theory and consensus analysis, we can prove the consensus errors and the observer errors can be reduced as small as desired by choosing the appropriate design parameters. Finally, the effectiveness of the proposed approach is illustrated by the simulation example.

Adaptive Learning Control for Second-Order Nonlinear Multi-Agent Systems with Iteration-Switching Topologies

ABSTRACTThis article investigates the containment control problem for a class of second-order multi-agent systems with inherent nonlinear dynamics, under the common assumption that each agent can only obtain the relative information of its neighbours intermittently. A kind of distributed protocol based only on the relative local intermittent measurements of neighbouring agents is designed for containment control under fixed directed topology. In the absence of delays, based on the Lyapunov function technology and the intermittent control method, some sufficient conditions are presented to guarantee the intermittent containment control of second-order nonlinear multi-agent systems. In the presence of delays, some containment conditions are also obtained for a second-order multi-agent systems with inherent delayed nonlinear dynamics and intermittent communications. Moreover, the similar results are obtained for second-order nonlinear multi-agent systems under switching directed topology. Finally, simulation examples are given to illustrate the correctness and effectiveness of the theoretical analysis.

In this paper, we study the cooperative global robust practical output regulation problem for a class of second-order uncertain nonlinear multiagent systems via a distributed event-triggered state feedback control strategy. Compared with the existing work, one of the main challenges is that we need to design two distributed internal models to learn both the desired steady-state state and steady-state input for each agent. Moreover, to obtain a directly implementable digital control law, the two distributed internal models of each agent only depend on the sampled states of the neighboring agents and itself. As a result, the resulting augmented system is more complicated, and the control law needs to be recursively designed. To overcome the difficulty, we propose a novel distributed event-triggered control law and a novel distributed event-triggered mechanism to deal with our problem. By adjusting a design parameter in the proposed event-triggered mechanism, we show that the Zeno behavior does not happen and the ultimate bound of the tracking error can be made arbitrarily small. Our design will be illustrated by two examples.

In this paper, we investigate the robust output consensus problem of a class of heterogeneous second-order nonlinear uncertain multi-agent systems. In comparison with existing results, the communication constraints are taken into consideration. In particular, different agents cooperate through a time-varying communication network which can be disconnected at any time and communication among them is subject to heterogeneous time-varying delays. A distributed control law is designed by employing the distributed output regulation approach. Under a very mild connectivity condi­tion, we show that the robust output consensus problem of heterogeneous second-order nonlinear uncertain multi-agent systems can be solved.

This paper studies the cooperative global robust output regulation problem for a class of heterogeneous second-order nonlinear uncertain multi-agent systems with jointly connected switching network. We first generalize the result of the adaptive distributed observer from undirected switching networks to directed switching networks, and then solve the problem by a dynamic distributed state feedback control law based on an integration of the adaptive distributed observer method and the distributed internal model design approach. Our result is illustrated by the leader-following consensus problem for a group of Van der Pol oscillators.

In this paper, the leader-following consensus of second-order nonlinear multiagent systems (SONMASs) with external disturbances is studied. Firstly, based on terminal sliding model control method, a distributed control protocol is proposed over undirected networks, which can not only suppress the external disturbances, but also make the SONMASs achieve consensus in finite time. Secondly, to make the settling time independent of the initial values of systems, we improve the protocol and ensure that the SONMASs can reach the sliding surface and achieve consensus in fixed time if the control parameters satisfy some conditions. Moreover, for general directed networks, we design a new fixed-time control protocol and prove that both the sliding mode surface and consensus for SONMASs can be reached in fixed time. Finally, several numerical simulations are given to show the effectiveness of the proposed protocols.

Special issue on PID control in the information age: Theoretical advances and applications

This paper presents an adaptive fault-tolerant control (FTC) scheme for a class of nonlinear uncertain second-order multi-agent systems. A local FTC component is designed for each agent in the distributed system by using local measurements and suitable information exchanged between neighboring agents. Each local FTC component consists of a fault diagnosis module and a reconfigurable controller module comprised of a baseline controller and two adaptive faulttolerant controllers activated after fault detection and after fault
\nisolation, respectively. Under suitable assumptions, the closedloop stability and leader-follower formation properties of the distributed system are rigorously established under different operating modes of the FTC system, including the time-period before possible fault detection, between fault detection and possible isolation, and after fault isolation.

This article deals with the event-triggered leader-following guaranteed cost consensus control problem for second-order nonlinear multiagent systems, in which the guaranteed cost function is proposed to facilitate to enhance the consensus tracking regulation performance. To reduce the frequency of information transmission, a distributed event-triggered mechanism, which broadcasts the triggered states to its neighbours for each agent, is designed, and the triggering condition is then constructed for leader-following second-order nonlinear multiagent systems. By employing Lyapunov–Krasovskii method and Barbalat’s lemma, some sufficient conditions are derived to ensure the leader-following consensus and guaranteed cost performance for second-order nonlinear multiagent systems. It is also exhibited that the constructed triggering condition can efficaciously exclude the Zeno behavior. To testify the efficacy of the proposed theoretical methodology, a simulation example is offered.

Bounded consensus in second-order uncertain nonlinear multiagent systems: A distributed neural network control approach

Completely distributed neuro-learning consensus with position constraints and partially unknown control directions

The consensus problem of heterogeneous second-order nonlinear uncertain multiagent systems under switching networks is addressed by a distributed control approach. The network communication of all systems is subject to arbitrarily bounded and nonuniform time-varying delays. Based on the internal model principle, a nonlinear distributed dynamic controller is developed to solve the problem. By means of Lyapunov analysis, consensus of heterogeneous second-order nonlinear multiagent systems is achieved in the presence of system uncertainties, disturbances, and uniformly connected topologies as well as arbitrarily bounded and nonuniform time-varying communication delays.

Distributed finite-time containment control for second-order nonlinear multi-agent systems