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This article proposes a fractional-order intelligent fault-tolerant synchronization tracking control (FO-I-FTSTC) scheme for multiple unmanned airships (UAs) against actuator faults. Within the developed control architecture, fixed-time prescribed performance functions (PPFs) are first designed to transform the synchronization tracking errors into a new set of error variables, such that the original errors are strictly confined within the prescribed bounds. Then, fractional calculus and sliding mode surface are sequentially introduced to construct the FO errors. Moreover, to handle the unknown terms and bias faults in the FO sliding-mode error dynamics, fuzzy neural networks with recurrent loops are artfully constructed to act as the intelligent learning units. Furthermore, the norm of the loss-of-effectiveness fault factors is introduced for each UA to reduce the number of adaptive parameters. The distinct feature of the proposed method is that the FO-I-FTSTC performance is significantly enhanced by integrating recurrent fuzzy neural networks, fractional calculus, and fixed-time PPFs into a unified framework, leading to a high-precision control scheme. It is shown by Lyapunov analysis that all UAs can track their desired references in a synchronized manner, and the synchronization tracking errors are bounded and strictly confined within the prescribed error bounds. Comparative hardware-in-the-loop experiments are presented to show the effectiveness of the proposed FO-I-FTSTC scheme. [ABSTRACT FROM AUTHOR]

This article investigates a distributed fractional-order fault-tolerant formation-containment control (FOFTFCC) scheme for networked unmanned airships (UAs) to achieve safe observation of a smart city. In the proposed control method, an interval type-2 fuzzy neural network (IT2FNN) is first developed for each UA to approximate the unknown term associated with the loss-of-effectiveness faults in the distributed error dynamics, and then a disturbance observer (DO) is proposed to compensate for the approximation error and bias fault encountered by each UA, such that the composite learning strategy composed of the IT2FNN and the DO is obtained for each UA. Moreover, fractional-order (FO) calculus is incorporated into the control scheme to provide an extra degree of freedom for the parameter adjustments. The salient feature of the proposed control scheme is that the composite learning algorithm and FO calculus are integrated to achieve a satisfactory fault-tolerant formation-containment control performance even when a portion of leader/follower UAs is subjected to the actuator faults in a distributed communication network. Furthermore, it is shown by Lyapunov stability analysis that all leader UAs can track the virtual leader UA with time-varying offset vectors, and all follower UAs can converge into the convex hull spanned by the leader UAs. Finally, comparative hardware-in-the-loop (HIL) experimental results are presented to show the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

This article considers the decentralized fractional-order fault-tolerant control problem for unmanned aerial vehicles (UAVs) against wind disturbances and actuator faults in a directed communication network. A new composite adaptive disturbance observer-based decentralized fractional-order fault-tolerant control (CADOB-DFO-FTC) scheme, which incorporates fractional-order (FO) sliding-mode surfaces, nonlinear disturbance observers (NDOs), fuzzy wavelet neural networks (FWNNs), and robust controllers, is developed to achieve the attitude tracking control of networked UAVs in a decentralized way. Based on the FO sliding-mode surfaces, the NDOs are first developed to estimate the lumped uncertainties due to the aerodynamic parameter perturbations, wind disturbances, and actuator faults. Then, adaptive FWNNs with updating weighting matrices, mean vectors, and deviation vectors are constructed to effectively attenuate the adverse effects induced by the NDO estimation errors. Furthermore, to compensate the FWNN approximation errors, robust controllers are integrated into the developed control scheme to enhance the approximation abilities. It is shown that by using Lyapunov methods, all UAVs can track their attitude references. Finally, comparative simulation results are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents an average dwell-time method for fault-tolerant control of a class of uncertain switched linear time-delay systems and also designs an algorithm to determine the parameters pertaining to the dwell-time condition. Compared to the literature results, this paper features the following: 1) the proposed method is independent of switching polices if switchings are slow enough in the average sense; 2) the proposed control design guarantees exponential stabilization of this class of time-delay linear systems with actuator faults; and 3) this method treats all actuators in a unified manner without a need to identify which are faulty or healthy actuators. The proposed method is applied to the water pollution control problem, for the first time, to deal with different ratios of stream flow rates to effluent flow rates. [ABSTRACT FROM AUTHOR]

Many studies have demonstrated the utility of surface dielectric barrier discharge (SDBD) plasma actuators driven by different voltage waveforms for airflow control. In this paper, a new dual-power supply voltage consisting of ac high voltage with a superimposed positive or negative pulse bias voltage is applied to a two-electrode structure SDBD actuator to compare the actuator performance with that driven by a single ac voltage waveform. The ionic wind velocity, the thrust force, and the schlieren visualization images are studied under three types of voltage waveforms: single ac voltage, ac voltage superimposed with a positive pulse bias voltage (ACPP), and ac voltage superimposed with a negative pulse bias voltage (ACNP). The influences of different pulse parameters including pulse voltage, pulse repetition frequency (PRF), and pulsewidth on the actuator performance are studied in detail. Experimental results show that pulse voltage and PRF have more notable influence on the actuator performance when the actuator is driven by ACPP, while the pulsewidth has little effect on the actuator performance. In contrast, the actuator performance is little changed when the actuator is driven by ACNP. The positive and negative pulse discharges have different effects on the actuator performance, the reason is positive pulse discharge increases the discharge of glow-like region while negative pulse discharge increases the discharge of streamer region in the following ac cycle. The schlieren images further indicate pulse discharge exerts its effects on the SDBD actuator performance by affecting the electric field of ac discharge. [ABSTRACT FROM PUBLISHER]

This paper studies a robust fault tolerant control of a class of nonlinear switched systems with strong structural uncertainties and actuator faults. This paper presents a new robust fault tolerant state feedback method, by using the average dwell time technique to stabilize the switched nonlinear systems exponentially under an arbitrary switching law. Comparing with the existing results, the method of this paper has three features: (1) this method is applicable to the switched nonlinear systems with strong structural uncertainties and faulty actuators and also the nominal case of the considered systems, there is no need to change any structures and/or parameters of the controller. (2) The switching law is arbitrary provided that the average switching is slow enough in the average sense. (3) This method treats all actuators in the same way, no need to separate faulty actuators from the healthy ones. The simulation result verifies the effectiveness of this method. [ABSTRACT FROM AUTHOR]

This brief considers fault-tolerant control of a class of uncertain switched nonlinear systems against partial actuator failures. This brief first presents a fault-tolerant control method by using the common Lyapunov function technique and then applies it to haptic display systems. Compared to the relevant literature results, this proposed method is: 1) invariant to actuator fault modes, in the sense that the proposed controllers are completely independent from the fault modes, and 2) independent of switching policies under certain conditions. Simulation studies on a practical haptic display system with switched virtual environments are carried out to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

Abstract: This paper presents a robust fault-tolerant control method for a class of uncertain switched systems with strong structural uncertainties and applied it to haptic display systems. The proposed controller can stabilize the switched systems containing strong uncertainties with actuator faults and its nominal systems (i.e., without actuator faults) without necessarily changing any structures and/or parameters of the proposed controllers, and treats faulty and healthy actuators in a unified way. The proposed method is independent of arbitrary switching laws. A practical haptic display system with switched virtual environments shows the effectiveness of the proposed method. [Copyright &y& Elsevier]

This paper proposes an adaptive fault-tolerant cooperative control (FTCC) scheme for networked unmanned aerial vehicles (UAVs) in the presence of actuator faults and wind effects by artfully introducing fractional order calculus, proportional–integral–derivative (PID), and recurrent neural networks. Fractional order sliding-mode surface and PID-type error mapping are first utilized to transform the synchronization tracking errors of all UAVs into a new set of errors. Then, based on these newly constructed errors, an FTCC scheme is developed to synchronously track their references. Moreover, Butterworth low-pass filter (BLF) and recurrent neural network (RNN) learning strategies are assimilated to handle the unknown terms induced by the actuator faults and wind effects. Finally, theoretical analysis and comparative hardware-in-the-loop experimental demonstrations have shown the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates a new finite-time fault-tolerant control (FTC) using a fractional-order backstepping iterative design strategy for a fixed-wing unmanned aerial vehicle (UAV) in the presence of actuator faults and input saturation. To compensate for the lumped disturbance induced by the actuator faults, a neural network disturbance observer (NNDO) with finite-time observation capability is first developed as the fault diagnostic unit. Then, based on the diagnosed fault information, fractional-order (FO) calculus is artfully utilized to enhance the FTC performance within the backstepping design architecture. The salient feature of the developed control scheme is that the finite-time NNDO and FO calculus are simultaneously used to significantly increase the FTC performance against unexpected actuator faults. Moreover, to address the input saturation problem, the faulty UAV dynamics is augmented by a new auxiliary system. Furthermore, a Nussbaum function is incorporated into the FTC scheme to further avoid the calculation of the inverse gain matrix involved within the auxiliary system. It is shown by Lyapunov analysis that the tracking errors are convergent in finite time. Finally, comparative simulations are conducted to show the effectiveness of the developed FTC scheme. Some hardware-in-the-loop (HIL) experimental results are illustrated to further demonstrate the feasibility of the proposed finite-time fractional-order fault-tolerant control (FTFOFTC) method. [ABSTRACT FROM AUTHOR]

Concurrent occurrences of actuator faults and wind effects can significantly threaten the flight safety of multiple unmanned aerial vehicles (multi-UAVs). To address this difficult control problem against actuator faults and wind effects, a composite decentralized fractional-order (FO) backstepping adaptive neural fault-tolerant control (FTC) method is presented for the attitude synchronization tracking of multi-UAVs, which is integrated with neural networks (NNs), disturbance observers (DOs), FO calculus, and high-order sliding-mode differentiators (HOSMDs). The distinctive feature of this work is addressing the attitude synchronization tracking control problem with actuator faults and wind effects in a decentralized framework and proposing a composite approximation method for multi-UAVs. It is shown that by using Lyapunov methods the synchronization tracking control is achieved even when multi-UAVs simultaneously encounter wind effects and actuator faults. Comparative simulation results illustrate the theoretical feasibility. [ABSTRACT FROM AUTHOR]