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This article investigates the consensus tracking problem with predefined transient and steady performance requirements for a class of nonstrict‐feedback nonlinear multi‐agent systems (MASs) with input quantization under a directed graph. Based on prescribed performance error transformation methods and command filtered backstepping techniques, a novel observer‐based adaptive control protocol is proposed, where neural observers are designed to estimate unmeasurable states and radial basis function neural networks are constructed to compensate command filter errors. The proposed protocol can be applied to a more general class of nonlinear MASs with nonstrict‐feedback nonlinear dynamics and unmeasurable states information. It is strictly proved that all signals in the whole MAS are semi‐globally uniformly ultimately bounded and both the transient and steady performances of the consensus tracking errors satisfy prescribed performance requirements. Finally, three numerical examples are presented to validate the effectiveness of the proposed protocol. [ABSTRACT FROM AUTHOR]

Summary: In this article, an adaptive neural fault‐tolerant decentralized tracking control problem is investigated for switched stochastic large‐scale uncertain nonlinear systems, in which time‐varying delay and unknown control coefficient are under consideration. By incorporating the quadratic Lyapunov function and Lyapunov Krasovskii function into the backstepping approach, an adaptive neural fault‐tolerant decentralized control strategy is proposed, which ensures that signals in the closed‐loop system are stable in probability and the tracking error converges to a small neighborhood of the origin under arbitrary switching. At last, to verify the presented strategy is feasible, a simulation example is given. [ABSTRACT FROM AUTHOR]

The contribution of this investigation lies in solving a sampled‐data output feedback stabilization problem for a class of upper‐triangular stochastic nonlinear systems in p$$ p $$‐normal structure with unavailable states and uncertain time‐varying input delay. A reduced‐order observer with the available sampled output detection is developed for the focused system to estimate its unavailable states, and under such observer, a sampled‐data output feedback stabilizer is constructed by combining the backstepping and adding a power integral techniques. Through selecting the appropriate Lyapunov–Krasovskii functionals, we can demonstrate that the adverse influences caused by the uncertain time‐varying delays in the resulting closed‐loop system can be restricted effectively by the constructed stabilizer, and further, by following the stochastic differential theories, the global stability of the considered resulting closed‐loop system can be analyzed under the suitable design parameters and allowable sampling period. Finally, two examples are given to verify the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

Summary: This article addresses the problem of global adaptive finite‐time control for a class of p‐normal nonlinear systems via an event‐triggered strategy. A state feedback controller is first designed for the nominal system by adding a power integrator method. Then, by the skillful design of adaptive dynamic gain mechanism, a novel event‐triggered controller is constructed for uncertain nonlinear system without homogeneous growth condition. It is proved that the global finite‐time stabilization of p‐normal nonlinear systems is guaranteed and the Zeno phenomenon is excluded. Finally, two examples are presented to indicate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the practical leader‐following consensus via the sampled‐data protocol is investigated for second‐order nonlinear multiagent systems with external disturbances, where the velocity information of all agents are assumed to be unmeasurable. The consensus problem of the multiagent system is first transformed to a stabilization problem of the constructed error system. Because of the unknown of the agents' velocities, an observer is then proposed for the constructed error system to estimate the velocity errors. By the backstepping approach, a new protocol is designed with only position measurements and sampled‐data information. Furthermore, the upper bound of the sampling period is given. It is proved that the practical leader‐following consensus can be achieved by the proposed sampled‐data protocol with a proper sampling period. The result is then extended to the multiagent systems with multiple leaders. Finally, two numerical examples are provided to illustrate the effectiveness of the designed protocols. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the stabilization problem of sampled‐data output feedback for a class of uncertain switched nonlinear systems in nonstrict‐feedback form. An observer is designed to estimate the unmeasured states, and a sampled‐data controller is obtained by discretizing the virtual controller that is constructed via the dynamic surface control method. It is proved that the designed sampled‐data controller can render all states of the resulting closed‐loop system to converge to a neighborhood of the origin for the arbitrary switching signal, and an allowable sampling period is also given. Finally, 2 examples are presented to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study investigates the adaptive finite‐time consensus protocols for a class of second‐order multi‐agent systems with unknown non‐linear dynamics. Mainly due to the presence of more general unknown non‐linearities, the finite‐time consensus of multi‐agent systems is rather difficult to reach. Radial basis function neural networks are used to approximate the unknown functions. Under some appropriate assumptions, distributed consensus protocols and adaptive laws are designed for all agents. It is proved that the position errors and the velocity errors between any two agents converge to a small neighbourhood of the origin in finite time. Finally, an example of finite‐time consensus control for multiple robot systems is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]