In this paper, an adaptive fault-tolerant control (FTC) scheme is proposed for a class of uncertain nonlinear systems with actuator failures, in which a backup actuator is available. Different from existing FTC methods applying dynamic redundant actuators, a situation of deferred actuator replacement is firstly taken into account, i.e., the backup one cannot connect to plant right after failure detection. To recover the tracking error into prescribed performance within a specified time, an error transformation is introduced to render Tangent Barrier Lyapunov Functions (TBLF) valid at the replacement instant, by which reconfigurable controller can be designed for the backup actuator. Simulation results on a flight control system are presented to illustrate the effectiveness of the FTC scheme.

In this article, an adaptive output feedback compensation scheme is proposed for a class of uncertain nonlinear systems with a set of redundant actuators and a sensor. The sensor output is the only information available for output feedback. Both the actuators and the sensor may suffer from failures during operation and, therefore, all the system states are not available. To estimate the unmeasured states, a modified high-gain observer is designed which can not only ensure the closed-loop system stability but also improve the tracking performance. In the adaptive controller design, to overcome the complexity due to the unknown actuator and sensor failures coupled with the nonlinear functions and unknown parameters, an upper bound estimation method is adopted, which greatly simplifies the design procedure. It is proved that with the proposed scheme, the actuator and sensor failures can be compensated simultaneously, the reconfiguration can be adaptively updated without fault detection and isolation, and the real-tracking error can converge to a residual set, that is, mainly proportional to the sensor gain variation and measurement error.

In this article, an adaptive quantized tracking control for a class of nonlinear systems with both input and state quantization is investigated. For the state quantization, instead of quantizing all the system states, only two signals need to be quantized and transmitted, which greatly reduces the communication burden. It is proved that with this proposed scheme, global stability of the closed-loop system can be achieved even with very coarse quantizers, and the tracking errors can be made arbitrarily small by choosing some design parameters appropriately.

In flight control systems, multiple actuator stuck (or hardover) failures would cause saturation of the remaining healthy actuators and result in system instability. In this article, a new adaptive actuator failure compensation control scheme is proposed for a class of nonlinear systems with multiple redundant inputs. Under a mild assumption on the time interval between two successive failures, an online fault detection and isolation (FDI) algorithm is introduced, with which an actuator failure can be exactly identified in a given finite time without using the persistent excitation (PE) condition. The main advantage of the proposed scheme is that with the help of the FDI algorithm, an actuator with stuck failure (SF) can be deactivated before a new failure occurs and therefore, the drawback of the current adaptive failure compensation control approach that may cause more control effort or even saturation with multiple actuators being stuck can be overcome.