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This article aims to realize a precise position and attitude tracking control for the quadrotor using a proposed fuzzy approximator-based compound adaptive fuzzy quantized control scheme. In the control scheme, a quantized output-feedback control for position tracking and a state-feedback quantized control for attitude trajectory tracking are combined to deal with the underactuated and strong coupling problems of the quadrotor. The main contributions are: 1) the adaptive fuzzy quantized control is realized, then the strong nonlinearities caused by the quantizer are effectively mitigated, which implies that the control precision can be improved when a low communication rate is required in the real-time control system of quadrotor; 2) by applying the adaptive fuzzy dynamic surface control (DSC) technique to the underactuated quadrotor control system, the “explosion of complexity” problem in the backstepping method is overcome and the $ {L}_{\infty }$ tracking performance is achieved with the proposed initializing technique inspired by Zhang et al. This guarantees that the attitude signals promptly converge to the desired trajectories, then the underactuated problem of the quadrotor is overcome by solving the designed adaptive fuzzy-quantized control equations; and 3) the experiments on the platform of the Quanser Qball-X4 quadrotor are conducted and the effectiveness of the proposed control scheme is validated. [ABSTRACT FROM AUTHOR]

In this paper, a novel adaptive neural network (NN) control scheme is proposed for a class of nonlinear systems with unknown control direction. By introducing some differentiable functions and high-order Lyapunov functions, the obstacle caused by unknown control direction in NN control is successfully circumvented and all closed-loop signals are shown to be uniformly bounded up to infinite time. Meanwhile, by introducing an error transformation technique, it is rigorously proved that the argument of the unknown nonlinearities remains within a compact set which can be explicitly calculated a priori, making the NN approximation always valid. Moreover, with the aid of a bound estimation approach, we effectively compress the impact of approximation errors and external disturbances and steer the tracking error into a predefined small residual set. Simulation results illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, a novel adaptive fault-tolerant control (FTC) scheme is proposed for a class of hypersonic flight vehicles (HFVs) with input constraints and unknown inertial and aerodynamic parameters. As an advantage beyond existing adaptive FTC schemes for HFVs, we investigate a more practical and more challenging case that both the elevator and the throttle may suffer from unknown and time-varying faults. By introducing some smooth functions and a linear time-varying model and estimating the bounds of those time-varying uncertainties, the impact of the faults and the input constraints is effectively compensated for and stable altitude and velocity tracking is successfully achieved. Besides, with the aid of the dynamic surface control technique, the proposed scheme is free of the problem of explosion of complexity inherent in traditional backstepping design. Such features result in a simple flight control scheme that can be easily implemented with less computational burden and higher reliability. Simulation results are presented to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, a decentralized output-feedback adaptive control scheme is proposed for a class of interconnected nonlinear systems with input quantization. Both logarithmic quantizers and improved hysteretic quantizers are studied, and a linear time-varying model is introduced to handle the difficulty caused by quantization. The proposed scheme allows the parameters of the quantizers to be freely changed during operation, and can guarantee global stability of the overall closed-loop system regardless of the coarseness of the quantizers and the existence of interactions among subsystems. Moreover, with the aid of a kind of high-gain K-filters, it is shown that all tracking errors converge to a residual set which can be made arbitrarily small by adjusting some design parameters. Simulation results are presented to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, a decentralized output-feedback adaptive backstepping control scheme is proposed for a class of interconnected nonlinear systems with unknown actuator failures. By introducing a kind of high-gain K -filters, a bound estimation approach and some smooth functions, the effect of actuator failures and interactions among subsystems is successfully compensated for and the actuators are allowed to change among the normal operation case and different failure cases infinitely many times. The proposed scheme is able to guarantee the global stability of the overall closed-loop system, regardless of the possibly infinite number of unknown actuator failures. An initialization technique is also introduced so that the L ∞ performance of tracking errors can be adjusted no matter if there exist unknown actuator failures. Simulation results performed on double inverted pendulums are presented to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

SUMMARY This paper is devoted to output-feedback adaptive control for a class of multivariable nonlinear systems with both unknown parameters and unknown nonlinear functions. Under the Hurwitz condition for the high-frequency gain matrix, a robust adaptive backstepping control scheme is proposed, which is able to guarantee the [ABSTRACT FROM AUTHOR]

Multivariable adaptive control with less prior information of the high-frequency gain matrix (HFGM) is a longstanding problem of both theoretical and practical importance. In this paper, a solution is presented by proposing a novel output-feedback adaptive backstepping control scheme. Our scheme only requires the leading principal minors of the HFGM to be nonzero and allows their signs to be unknown, which significantly relaxes the assumptions on the HFGM in conventional multivariable adaptive control schemes. To cope with the unknown signs, we propose novel Nussbaum functions with some nice properties and construct periodical intervals in which the effects of the multiple Nussbaum functions reinforce rather than counteract each other. With these efforts, global stability of the closed-loop system and asymptotical convergence to zero of the tracking error are successfully achieved. Simulation results illustrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]