This article investigates the event-triggered (ET) consensus issue of Lipschitz nonlinear multiagent systems (MASs) with a positive minimum inter-event time (MIET) in the presence of unmeasurable state. To handle this issue, we design a fully distributed control scheme by virtue of asynchronous event-triggered mechanism (ETM) and available local measurement output, in which the knowledge of global information is no longer required by introducing adaptive parameters. It is shown that under the proposed control scheme, the consensus is asymptotically realized, in which the local state observer is proposed to remove the requirement of full-state information. Besides, a dynamic variable is introduced to obtain a positive MIET in the proposed ETM, where each agent asynchronously sends its observer value to its neighbors based on intermittent communication. In light of consensus analysis and MASs dynamics, a novel estimator of the observer is designed to ensure the asymptotic consensus. Note that based on the reformulated Lipschitz property, the linear matrix inequality (LMI) conditions of the control design are less restrictive as compared with the exist results. A practice simulation example is presented to verify the theoretical results. Note to Practitioners —Some practical (such as manipulator and pendulum) control systems can be modeled as Lipschitz nonlinear MASs. If the information exchange determined by ETM is high-frequency, it is unsuitable for physical implementation because each agent has limited communication resource. Thus, it is significant to design ETM with a positive MIET guarantees. Besides, the asynchronous communication among neighbors is more distributed compared with the synchronous communication, which might significantly save the communication resource. The reformulated Lipschitz property is introduced to reduce conservatism of the LMI conditions in the existing results. It might be difficult to measure the full-state information of each agent in some situations owing to physical limitations. Therefore, an observer-based adaptive asynchronous ET control scheme is proposed for Lipschitz nonlinear MASs with unmeasurable state, which can guarantee asymptotic convergence and a positive MIET. Finally, a one-link manipulator with revolute joints is considered to demonstrate the effectiveness of the proposed algorithm.

The output consensus or tracking problem for heterogeneous multiagent systems (MASs) under jointly observable condition (JOC) is investigated in the presence of unknown system matrix of the leader and unknown faults on communication link and actuator. Unlike the recent works, where neighbors of the leader have access to the state information of the leader, only part output information of the leader can be measured by its neighbors under JOC in this article. In addition, the system matrix of the leader only is known to neighbors of the leader. The problem of unknown leader’s state and unknown leader’s system matrix, unknown communication link faults (CLFs) is transformed into constructing the fully distributed state and system matrix observers by virtue of adaptive control technique and JOC. In light of the developed distributed observer, a distributed adaptive fault-tolerant controller against actuator faults is designed. Here, compared with the existing ideas, actuator faults of an agent will not affect the dynamics of its neighbors over the communication graph in this article. It is shown that the output of each follower asymptotically converges to the output of the leader. Finally, the developed control scheme is illustrated by a simulation example.

This paper focuses on the tracking control problem of Magnetic Levitation System (MLS). MLS is highly unstable nonlinear system, in the process of operation, MLS needs to have strong robustness and anti-interference ability. Due to disturbance and parameter uncertainties in MLS, it is complex to obtain the exact dynamics of MLS, and it is difficult to design a suitable controller. The dynamic equation of the system is established by Lagrange equation, and then we propose an adaptive Sliding Mode Control (SMC) based on Radial Basis Function Neural Network (RBFNN). Because of the parameter uncertainties and disturbance in MLS, RBFNN is used to approximate the unknown dynamics in MLS. The stability of the closed-loop system is strictly proved by using the Lyapunov stability theory, which can achieve the uniform ultimate boundedness (UUB) of the signals of the closed-loop MLS. MATLAB environment is used to verify the performance of the proposed controller. Considering disturbance, parameter change, or unmodeled dynamics in MLS, proposed controller is compared with other nonlinear controllers, simulation results verify the effectiveness of the proposed approach.

This article addresses the output consensus problem of heterogeneous multiagent systems (MASs) via a distributed modified dynamic event-triggered control design. First, a fully distributed asynchronous event-triggered compensator for each agent is proposed to act as a virtual reference generator without using global information. Second, based on this compensator, a distributed event-triggered controller for each heterogeneous agent is developed to reach output consensus. Specifically, to save resources and guarantee asymptotic consensus, a modified dynamic event-triggered mechanism (DETM) is proposed, in which a time-triggered mechanism (TTM) is introduced to ensure the existence of a positive minimum interevent time and a DETM is designed to further avoid redundant triggering actions. Besides, the triggering condition of the DETM does not require continuous detection, it is only detected when the timer variable in the TTM deceases from maximum value to zero. These features of the developed control scheme are presented analytically and verified numerically.

This article studies the asymptotic tracking control problem for strict-feedback nonlinear systems affected by asymmetric state and input constraints, nonparametric uncertainties, actuator faults, and unknown virtual control coefficients (VCCs). Different from the previous tracking control for strict-feedback systems results, the class of systems considered is more general, while can achieve better tracking performance in term of asymptotic tracking. A nonlinear state-dependent function (NSDF) is introduced to handle full-state constraints without requiring feasibility conditions imposed on virtual controls. To deal with the “explosion of complexity”, a novel filter is developed, which can also guarantee that the boundary errors asymptotically converge to zero. To cope with unknown VCCs, a Lyapunov function is developed based on the lower bounds of unknown VCCs skillfully. By introducing the Nussbaum function and a novel smooth function, the obstacle jointly caused by input constraint and actuator faults is circumvented well. It is proved that the asymptotic convergence of tracking error is successfully ensured. Finally, simulation verification is provided to illustrate the effectiveness of theoretical results.

The passivity-based control (PBC) is a new direction of nonlinear control, but the method is basically a qualitative method. A quantifiable design method in combination with PBC is provided in this paper. To solve the partial differential equation (PDE) for PBC, the nonlinear system must first be transformed into a Hamiltonian model. The PDE for the Hamiltonian system is then quantifiably solved with an electromagnetic levitation example. The resulting control law is presented and discussed. The proposed method provides a practical design tool for nonlinear control.