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An adaptive approximated inverse control scheme for a class of high-order nonlinear multi-agent systems with unknown control directions is proposed in this paper. The adaptive control problem under the case it is not required to be identical for the unknown control directions is solved by some novel Nussbaum functions and a monotonously increasing sequence, leading our multiple Nussbaum functions reinforce rather than counteract each other. Also, it is introduced in the design and analysis like some integrable auxiliary signals and a novel contradiction argument. Moreover, hysteresis nonlinearity is counteracted by constructing its approximated inverse compensator. With these efforts, stability analysis ensures that all the closed-loop system signals are uniformly bounded, and it is successfully achieved the asymptotic convergence of tracking error to zero, circumventing the obstacle caused by the unknown control directions. Experiment results illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive dynamic surface control scheme is proposed for a class of hypersonic flight vehicles with unknown elevator faults. By estimating the bounds of the fault uncertainties, the effect of the faults is successfully compensated for and each elevator is allowed to change among the healthy case and different faulty cases infinitely many times. The proposed scheme is free of the problem of explosion of complexity and is able to steer tracking errors into predefined arbitrarily small residual sets with prescribed convergence rates and maximum overshoots. Such features result in a simple flight control scheme which can be easily implemented with less computational burden, satisfactory tracking performance and high reliability. Simulation results illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, a novel robust adaptive neural control scheme is proposed for a class of uncertain multi-input multi-output nonlinear systems. The proposed scheme has the following main features: (1) a kind of Hurwitz condition is introduced to handle the state-dependent control gain matrix and some assumptions in existing schemes are relaxed; (2) by introducing a novel matrix normalisation technique, it is shown that all bound restrictions imposed on the control gain matrix in existing schemes can be removed; (3) the singularity problem is avoided without any extra effort, which makes the control law quite simple. Besides, with the aid of the minimal learning parameter technique, only one parameter needs to be updated online regardless of the system input–output dimension and the number of neural network nodes. Simulation results are presented to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive dynamic surface control scheme is proposed for a class of multi-input multi-output (MIMO) nonlinear time-varying systems. By fusing a bound estimation approach, a smooth function and a time-varying matrix factorisation, the obstacle caused by unknown time-varying parameters is circumvented. The proposed scheme is free of the problem of explosion of complexity and needs only one updated parameter at each design step. Moreover, all tracking errors can converge to predefined arbitrarily small residual sets with a prescribed convergence rate and maximum overshoot. Such features result in a simple adaptive controller which can be easily implemented in applications with less computational burden and satisfactory tracking performance. Simulation results are presented to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM PUBLISHER]

In this article, a novel output-feedback adaptive dynamic surface control scheme is proposed for linear time-invariant multivariable plants based on the norm estimation of unknown parameter matrices. Besides avoiding the explosion of complexity problem in traditional multivariable backstepping design, the proposed scheme has the following features: (1) only one parameter needs to be updated on-line regardless of the plant order and input–output dimension, (2) only the Hurwitz condition is required for the high-frequency gain matrix and (3) the ℒ∞ performance of the tracking error can be guaranteed. It is shown that all signals of the closed-loop system are semi-globally uniformly bounded. Simulation results are given to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]