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Based on an adaptive neural control scheme, this paper investigates the consensus problem of random Markov jump multi-agent systems with full state constraints. Each agent is described by the fractional-order random nonlinear uncertain system driven by random differential equations, where the random noise is the second-order stationary stochastic process. First, in order to deal with the unknown functions with Markov jump parameters, a radial basis function neural network (RBFNN) structure is introduced to achieve approximation. Second, for the purpose of keeping the agents' states from violating the constraint boundary, the tan-type barrier Lyapunov function is employed. By using the stochastic stability theory and adopting the backstepping technique, a novel adaptive neural control design method is presented. Furthermore, to cope with the differential explosion problem in the design course, the extended state observer (ESO) is developed instead of neural network (NN) approximation or command filtering techniques. Finally, the exponentially noise-to-state stability in the mean square is analyzed rigorously by the Lyapunov method, which guarantees the consensus of the considered multi-agent systems and all the agents' outputs are bounded in probability. Two simulation examples are provided to verify the effectiveness of the suggested control strategy. [ABSTRACT FROM AUTHOR]

This paper probes into the problem of predefined-time consensus tracking for a class of second-order multi-agent systems (MASs) subject to external disturbances based on a predefined-time observer. A predefined-time control strategy based on the use of terminal sliding mode control method is proposed, which can achieve consensus tracking in a predefined time. Firstly, the observer is designed so that observed states and leader states reach consensus. Secondly, according to the designed controller, states of each agent and observed states achieve consensus, namely, leader-following consensus is realized. By employing Lyapunov stability theory, some sufficient criteria are obtained to achieve predefined-time consensus tracking for second-order MASs with disturbances. Finally, some numerical examples are presented to prove the validity of our designs. [ABSTRACT FROM AUTHOR]

In this paper, a distributed adaptive finite-time consensus (FTC) control protocol for a high-order multi-agent system (MAS) with intermittent communications under switching topologies is proposed. Meanwhile, considering the problem of heterogeneous unknown nonlinearities and other uncertain disturbances, the adaptive neural network and the sliding mode control method are used to compensate the nonlinearity of each agent separately. The agents are homogeneous, so the system has symmetry. The switching topologies considered in this paper are asymmetric. Compared with consensus protocol for asymptotic convergence, simulation results show that the proposed method can effectively solve the presence of the nonlinear and accelerate the convergence speed of the system so that an FTC can be reached. [ABSTRACT FROM AUTHOR]

In this paper, a consensus tracking protocol for nonlinear agents is presented, which is based on the Nonlinear Dynamic Inversion (NDI) technique. Implementation of such a technique is new in the context of the consensus tracking problem. The tracking capability of nonlinear dynamic inversion (NDI) is exploited for a leader-follower multi-agent scenario. We have provided all the mathematical details to establish its theoretical foundation. Additionally, a convergence study is provided to show the efficiency of the proposed controller. The performance of the proposed controller is evaluated in the presence of both (a) random switching topology among the agents and (b) random switching of leader–follower connections, which is realistic and not reported in the literature. The follower agents track various trajectories generated by a dynamic leader, which describes the tracking capability of the proposed controller. The results obtained from the simulation study show how efficiently this controller can handle the switching topology and switching leader-follower connections. [ABSTRACT FROM AUTHOR]

This paper considers fixed-time consensus tracking of second-order multiagent systems (MASs) under directed interaction topology. A novel distributed observer is presented to estimate the leader’s states within a fixed time, which overcomes the difficulties caused by the asymmetry of the Laplacian matrix. A sliding surface is designed and a nonsingular terminal sliding mode consensus protocol is developed to achieve fixed-time convergence of the tracking error to the origin. It is shown that each follower can track the leader’s trajectory within a fixed time. Particularly, the gain of the presented consensus protocol is directly related to the prescribed time, which makes it convenient to determine and tune the gain according to the requirement of convergence time. Moreover, the presented control protocol reduces the conservativeness of the convergence time estimation for sliding motion. The simulation results validate the effectiveness of the proposed consensus scheme. [ABSTRACT FROM AUTHOR]

In this paper, the predefined-time consensus tracking problem of second-order multiagent systems (MASs) is investigated. A distributed observer is presented to estimate the tracking error for each follower within predefined time. A novel sliding surface is constructed to ensure predefined-time system convergence along the sliding surface and a terminal sliding mode consensus protocol is presented to overcome singularity problem and achieve leader-following consensus within predefined time. It is mathematically proved that the followers’ states can track the leader’s trajectory within predefined time. In particular, the settling time bound is directly related to tunable parameters, which facilitates the control protocol design to meet the desired convergence time requirement. Besides, the estimation bound for convergence time is less conservative than some existing fixed-time consensus protocols. The effectiveness of the proposed method is verified by the consensus tracking control for networked single-link robotic manipulators. [ABSTRACT FROM AUTHOR]

In this paper, the flocking behavior and targets consensus tracking problems of heterogeneous multiple inertial agents with limited communication ranges are investigated. Consider the inertial effect of real agents, a distributed control protocol is designed such that the agents can achieve stable group behaviors. Using the decomposition approach, the stability of a multiple inertial agents system is proved. Combining with the flocking behavior of multiple inertial agents, agents themselves are in charge of searching and choosing the target in an autonomous and individual way according to the relationship between velocities of agents and targets. An augmented distributed multiflocking method is proposed to guarantee that the multitarget consensus tracking can be reached for heterogeneous multiagent systems. It shows that the proposed control approach can not only ensure local flocking with pursuing agents, but also make heterogeneous agents consistently track the multitarget. [ABSTRACT FROM AUTHOR]

This paper studies the fuzzy adaptive distributed event-based control scheme for a class of uncertain nonlinear multiagent systems in strict feedback form. A novel distributed adaptive event-trigger condition and event-triggered controller are designed simultaneously. The main advantage with respect to event-sampling states is that the controllers were updated in an aperiodic manner at the event sampled instants, saving the computation resource and transmission load. Simulation results have shown satisfactory tracking performance of the developed control scheme. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed model free adaptive iterative learning control (MFAILC) method for a class of unknown nonlinear multiagent systems to perform consensus tracking. Here, both fixed and iteration-varying topologies are considered and only a subset of followers can access the desired trajectory in each topology. To design the control protocol, the agent’s dynamic is first transformed into a dynamic linearization model along the iteration axis, and then a distributed MFAILC scheme is constructed to guarantee that all agents can track the desired trajectory. Through rigorous analysis, it is shown that under this novel distributed MFAILC scheme, the tracking errors of all agents are convergent along the iteration axis. The main merit of this design is that consensus tracking task can be achieved only utilizing the input/output data of the multiagent system. Three examples are given to validate the effectiveness of the proposed design. [ABSTRACT FROM AUTHOR]

By employing the finite-time control method, the consensus control algorithm for higher-order multiagent systems is designed in this paper. Under a neighbor-based rule, a higher-order finite-time consensus algorithm is explicitly constructed, which only uses local information. The finite-time consensus control algorithm can guarantee that the state consensus is achieved in a finite time. In addition, for multiagent systems having a leader-following structure, the consensus algorithm is also designed. Finally, two examples are presented to show the effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, time-domain (Lyapunov theorems) and frequency-domain (the Nyquist stability criterion) approaches are used to study leaderless and leader-following consensus algorithms with communication and input delays under a directed network topology. We consider both the first-order and second-order cases and present stability or boundedness conditions. Several interesting phenomena are analyzed and explained. Simulation results are presented to support the theoretical results. [ABSTRACT FROM AUTHOR]

This paper deals with the consensus tracking problem of heterogeneous linear multiagent systems under the repeatable operation environment, and adopts a proportional differential (PD)-type iterative learning control (ILC) algorithm based on the fractional-power tracking error. According to graph theory and operator theory, convergence condition is obtained for the systems under the interconnection topology that contains a spanning tree rooted at the reference trajectory named as the leader. Our algorithm based on fractional-power tracking error achieves a faster convergence rate than the usual PD-type ILC algorithm based on the integer-order tracking error. Simulation examples illustrate the correctness of our proposed algorithm. [ABSTRACT FROM AUTHOR]