Fault-tolerant Control Scheme Research Articles

Performance-Based Hierarchical Fault-Tolerant Control for Closed-Loop Systems With Multiplicative Faults: A Data-Driven Design Method.

Fault-tolerant control (FTC) is vital for the safety and reliability of automatic systems. Most of the existing FTC methods are developed for open-loop systems subject to additive faults, regardless of the widely present control loops and multiplicative faults within systems. In this article, a performance-based FTC strategy is proposed for the closed-loop systems with multiplicative faults. Considering the high efforts in modeling complex systems, the proposed FTC strategy is realized in the data-driven context. Specifically, a nominal feedback-feedforward controller is first established for the fault-free systems. By selecting the system stability and reference tracking behavior as the key performance indices, two performance evaluators are constructed to detect and classify the occurred multiplicative faults based on the fault-induced effects on the system performance. Then, with the aid of the coprime factorization technique, the multiplicative faults, in the form of additive perturbations to the system coprime factors, are estimated utilizing the closed-loop process data. Furthermore, based on the fault knowledge, a hierarchical fault-tolerant tracking controller is developed according to the levels of system performance degradations, where the functional controller parameters are reconfigured with different priorities. Finally, case studies are provided to validate the effectiveness of the proposed method.

Integral terminal sliding mode fault tolerant control of quadcopter UAV systems

The article presents an active fault-tolerant control scheme with an integral terminal sliding mode controller for the UAV systems. This scheme effectively addresses saturation issues, disturbances, and sensor and actuator faults. Initially, the quadcopter UAV's model is represented in state space form. Subsequently, an augmented system incorporating auxiliary states from sensor faults is developed. An adaptive sliding mode observer is proposed for estimating the actuator and sensor faults. The integral terminal sliding mode fault-tolerant control, designed for altitude and attitude regulation, relies on fault estimation data. In contrast, a cascade proportional-integral-derivative (PID) controller is employed for position control. Simulation results demonstrate the superiority of the proposed method over existing control algorithms.

Robust Fixed-Time Fault-Tolerant Control for USV with Prescribed Tracking Performance

The unmanned surface vessel (USV) is an emerging marine tool with its advantages of automation and intelligence in recent years; the good trajectory tracking performance is an important capability. This paper proposes a novel prescribed performance fixed-time fault-tolerant control scheme for an USV with model parameter uncertainties, unknown external disturbances, and actuator faults, based on an improved fixed-time disturbances observer. Firstly, the proposed observer can not only accurately and quickly estimate and compensate the lumped nonlinearity, including actuator faults, but also reduce the chattering phenomenon by introducing the hyperbolic tangent function. Then, under the framework of prescribed performance control, a prescribed performance fault-tolerant controller is designed based on a nonsingular fixed-time sliding mode surface, which guarantees the transient and steady-state performance of an USV under actuator faults and meets the prescribed tracking performance requirements. In addition, it is proved that the closed-loop control system has fixed-time stability according to Lyapunov’s theory. Finally, upon conducting numerical simulations and comparing the proposed control scheme with the SMC and the finite-time NFTSMC scheme, it is evident that the absolute error tracking performance index of the proposed control scheme is significantly lower, thus indicating its superior accuracy.

Fault-Tolerant Control of Autonomous Underwater Vehicle Actuators Based on Takagi and Sugeno Fuzzy and Pseudo-Inverse Quadratic Programming under Constraints.

Autonomous Underwater Vehicles (AUVs) play a significant role in ocean-related research fields as tools for human exploration and the development of marine resources. However, the uncertainty of the underwater environment and the complexity of underwater motion pose significant challenges to the fault-tolerant control of AUV actuators. This paper presents a fault-tolerant control strategy for AUV actuators based onTakagi and Sugeno (T-S) fuzzy logic and pseudo-inverse quadratic programming under control constraints, aimed at addressing potential actuator faults. Firstly, considering the steady-state performance and dynamic performance of the control system, a T-S fuzzy controller is designed. Next, based on the redundant configuration of the actuators, the propulsion system is normalized, and the fault-tolerant control of AUV actuators is achieved using the pseudo-inverse method under thrust allocation. When control is constrained, a quadratic programming approach is used to compensate for the input control quantity. Finally, the effectiveness of the fuzzy control and fault-tolerant control allocation methods studied in this paper is validated through mathematical simulation. The experimental results indicate that in various fault scenarios, the pseudo-inverse combined with a nonlinear quadratic programming algorithm can compensate for the missing control inputs due to control constraints, ensuring the normal thrust of AUV actuators and achieving the expected fault-tolerant effect.

Prescribed-time fault-tolerant tracking control for Markov jump nonlinear systems based on saturation dynamics filters

This paper investigates the problem of prescribed-time fault-tolerant tracking control for a class of Markov jump nonlinear systems affected by actuator faults and input saturation. First, a new time-varying constraint function and an error transformation are invoked to transform the original prescribed-time tracking control problem into a tracking control problem with deferred constraint for tracking error. Furthermore, the parameter correction terms are designed, on which a novel Markov jump saturation dynamic filter is constructed to handle the unfavorable effect of input saturation. Meanwhile, the projection operator technique and the norm estimation methodology are integrated to devise adaptive laws to estimate the unknown actuator faults evolving in accordance with the Markov chain. A new prescribed-time fault-tolerant tracking control scheme is put forward that realizes the deferred constraint on the tracking error, which in turn ensures that the tracking error of the system converges to a prescribed accuracy within a prescribed-time. Finally, two simulation examples, one of which implements a prescribed-time fault-tolerant tracking control for rotary steerable drilling tool system, are presented to illustrate the effectiveness and practicality of the developed scheme.

Multiple model fault diagnosis and fault tolerant control for the launch vehicle’s attitude control system

Abstract For the launch vehicle attitude control problem, traditional methods can seldom accurately identify the fault types, making the control method lack of pertinence, which largely affects the effect of attitude control. This paper proposes an active fault tolerant control strategy, which mainly includes fault diagnosis and fault tolerant control. In the fault diagnosis part, a small deviation attitude dynamics model of the launch vehicle is established, Kalman filters with different structures are designed to detect and isolate faults through residual changes, and the fault quantity of the actuator is further estimated. In the fault tolerant control part, the following control scheme is adopted according to the above diagnostic information: when the sensor fault is detected, the sensor measurement data is reconstructed; when the actuator fault is identified, the control allocation matrix is reconstructed. Simulation results show that the proposed method can effectively diagnose sensor fault and actuator faults, and significantly improve attitude tracking accuracy and control adjustment time.

Interference fading suppression with fault-tolerant Kalman filter in phase-sensitive OTDR

A multi-sensor information fusion algorithm based on fault-tolerant Kalman filter is proposed in phase-sensitive optical time-domain reflectometer (Φ-OTDR) system, for achieving fading-free distributed vibration sensing. Firstly, a fault-tolerant dual-core complementary array model is designed. The Rayleigh scattering signal denoising, and vibration existence judgment of localization points are carried out to obtain the differentiated frequency demodulation results of the sensing points of the dual-core fiber array. Then a fault-tolerant control strategy is used to determine the sensor weight coefficients and vibration judgment coefficients during data fusion processing, and array data fusion is carried out based on time series data using Kalman filter to realize error value identification and filling. The advantage of this method is the combination of redundant data in a complementary way to improve the system stability. The frequency response ranges from 10 Hz to 2400 Hz and the localization accuracy is 98.33%. The influence of key parameters on the frequency demodulation performance of fault-tolerant Kalman filter is discussed, and a standard deviation of 14.6 Hz and an average error of 7.6 Hz are obtained. The demodulation frequency data matrix obtained by the classical demodulation method has a demodulation error probability of 89.18%, which proves the widespread existence of demodulation errors in vibration signals. The fusion error of demodulation frequency is reduced to 0.25 Hz, the frequency demodulation accuracy reaches 100%, and the demodulation error caused by interference attenuation can be completely eliminated. This system based on fault-tolerant Kalman filter has the characteristics of simple multiplexing structure, interference fading resistance and stable demodulation performance.

A Simple Online Fault Location and Tolerant Control Strategy for Power Electronic Transformers With a Single IGBT Open-Circuit Fault

A Simple Online Fault Location and Tolerant Control Strategy for Power Electronic Transformers With a Single IGBT Open-Circuit Fault

Neural-Network-Based Adaptive Fault-Tolerant Cooperative Control of Heterogeneous Multiagent Systems With Multiple Faults and DoS Attacks.

In this article, the issue of adaptive fault-tolerant cooperative control is addressed for heterogeneous multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults and sensor faults under denial-of-service (DoS) attacks. First, a unified control model with actuator faults and sensor faults is developed based on the dynamic models of the UAVs and UGVs. To handle the difficulty introduced by the nonlinear term, a neural-network-based switching-type observer is established to obtain the unmeasured state variables when DoS attacks are active. Then, the fault-tolerant cooperative control scheme is presented by utilizing an adaptive backstepping control algorithm under DoS attacks. According to Lyapunov stability theory and improved average dwell time method by integrating the duration and frequency characteristics of DoS attacks, the stability of the closed-loop system is proved. In addition, all vehicles can track their individual references, while the synchronized tracking errors among vehicles are uniformly ultimately bounded. Finally, simulation studies are given to demonstrate the effectiveness of the proposed method.

Distributed predefined-time estimator-based affine formation target-enclosing maneuver control for cooperative underactuated quadrotor UAVs with fault-tolerant capabilities

The paper presents a two-layer, disturbance-resistant, and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles (QUAVs). This scheme mainly consists of predefined-time estimators and fixed-time tracking controllers, with a hybrid Laplacian matrix describing the communication among these QUAVs. At the first layer, we devise predefined time estimators for leading and following QUAVs, enabling accurate estimation of desired information. In the second layer, we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults. Fixed-time translational tracking controllers are then proposed, and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers. We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly. The paper includes a demonstration of the control system stability through mathematical proof, as well as the presentation of simulation results and comparative simulations.

Nonlinear adaptive fault-tolerant control for full-car active suspension with velocity measurement errors and full-state constraints

This work concentrates on the vibration suppression problem for full-car active suspension in the presence of multiple actuator faults, velocity measurement errors, full-state constraints and external disturbances, simultaneously. Herein, a novel nonlinear fault-tolerant control (FTC) strategy is developed by the aid of the online estimation of fault parameters, and it can accommodate multiple actuator faults without the information obtained from costly fault detection and isolation mechanism. Then, the violation of full-state constraints can be prevented by introducing the log-type barrier Lyapunov function (BLF) into the adaptive backstepping method, and the problems related to car body velocity measurement errors and external disturbances are handled under the robust control framework, so the complexity caused by state constraints, actuator faults and velocity measurement errors can thus be taken into consideration. The stability analysis is subsequently conducted with the assistance of Lyapunov theory, the boundness of all signals is confirmed, and the non-violation of the displacement and velocity constraints for car body motions is guaranteed. In the end, the performance of the proposed controller is evaluated under sinusoidal and random road surfaces. Importantly, the simulation results are presented to indicate the validity and advantages of the developed approach despite the existence of multiple actuator faults, velocity measurement errors and external disturbances.

Concurrent Learning Robust Adaptive Fault Tolerant Boundary Regulation of Hyperbolic Distributed Parameter Systems.

This article develops a robust adaptive boundary output regulation approach for a class of complex anticollocated hyperbolic partial differential equations subjected to multiplicative unknown faults in both the boundary sensor and actuator. The regulator design is based on the internal model principle, which amounts to stabilize a coupled cascade system, which consists of a finite-dimensional internal model driven by a hyperbolic distributed parameter system (DPS). To this end, a systematic sliding mode equipped with a backstepping approach is developed such that the robust state feedback control can be realized. Moreover, since the available information is a faulty boundary measurement at the right side point, state estimation is required. However, due to the presence of boundary unknown faults, we need to solve an issue of joint fault-state estimation. Restrictive persistent excitation conditions are usually required to guarantee the exact estimation of faults but are unrealistic in practice. To this end, a novel concurrent learning (CL) adaptive observer is proposed so that exponential convergence is obtained. It is the first time that the spirit of CL is introduced to the field of DPSs. Consequently, the observer-based adaptive boundary fault tolerant control scheme is developed, and rigorous theoretical analysis is given such that the exponential output regulation can be achieved. Finally, the effectiveness of the proposed methodology is demonstrated via comparative simulations.

Confidence Weighted Learning Entropy for Fault-Tolerant Control of a PMSM With a High-Resolution Hall Encoder

There are several non-idealities that can degrade magnetic Hall-effect sensors performance and impact related applications. Thus, a confidence weighted learning entropy (CWLE) is proposed as a fault-tolerant control strategy for field-oriented control (FOC) of permanent magnet synchronous machines (PMSM). It combines sensorless and sensor-based control, while capitalizing on their major advantages, such as operation from standstill and at lower speeds, fast dynamic response, and fault tolerance to encoder errors. Encoder fault detection is based on learning entropy, that monitors weights increments of two predictive filters of angular displacement. If the two observed systems behave similarly, the variance of the weights increments is similar. A higher variance, on the other hand, reflects unforeseen misbehavior of a particular system, leading to a decrease in its confidence. A voting mechanism based on confidence weighted average then decides which of the two systems should be used for FOC of PMSM. The method has been experimentally verified on a high-speed PMSM, achieving more reliable control performance with fast response to encoder failures.

DFIG in Wind Energy Applications with High Order Sliding Mode Observer-based Fault-Tolerant Control Scheme using Sea Gull Optimization

This paper describes a new method for maximizing power extraction from a wind energy conversion system (WECS) by using a doubly fed induction generator (DFIG) that operates below nominal wind speed. To maximize the collected power of a wind turbine (WTG) exposed to actuator failure, a fault-tolerant high-order sliding mode observer (HOSMO) and Seagull Optimization Algorithm with a model predictive controller (MPC) technique is proposed. Evaluate both the real state and the sensor error simultaneously using a higher-order sliding-mode observer. Active fault tolerant controllers are designed to regulate wind turbine rotor speed and power in the presence of actuator defects and uncertainty. With the growing interest in employing wind turbines (WTGs) as the primary generators of electrical energy, fault tolerance has been seen as essential to improving efficiency and reliability. This research focuses on optimal fault-tolerant pitch control, which is used to modify the pitch angle of wind turbine blades in the event of sensor, actuator, and system failures. A Seagull Optimization Algorithm (SOA) is proposed to tune controller parameters to improve the performance of WT. The proposed method has achieved 92% of power tracking performance when compared to existing method.

Integrated sensor FTC using integral sliding mode control

In this paper, a sliding mode sensor fault tolerant control scheme which involves a first order sliding mode observer, fault compensation logic and an integral sliding mode controller, is proposed for a class of uncertain linear parameter-varying systems. The proposed scheme has the capability to retain near nominal fault-free performance in the face of a class of sensor faults/failures. In particular, the closed-loop stability of the sensor fault tolerant scheme involving the sliding mode observer and the sliding mode controller in the presence of faults and uncertainty, is rigorously analysed. Furthermore, the paper proposes an algorithm to simultaneously synthesize the design freedom associated with the observer gains and control law despite the lack of a separation principle in the closed loop system overall caused by the uncertainty. The proposed scheme is validated using a commercial aircraft model. Good simulation results show the efficacy of the scheme.

A unified SVPWM fault tolerant control algorithm for single leg fault reconstruction topology of two-level inverter

To improve the reliability of Two-level three phase voltage source inverters, a uniform fault tolerant strategy based on space vector pulse width modulation is proposed for different leg faults. The reconstructed topologies of inverters with different bridge arm faults are different, which makes the basic voltage vector phase of each reconstructed topology inconsistent, resulting in different calculations. Therefore, the coordinate transformation is applied to place the basic voltage vectors of each reconstructed topology on the synchronous stationary αβ coordinate system so that the calculations of the reconstructed topology under different bridge arm faults are unified, thus reducing the complexity of fault-tolerant control. Aiming at the three-phase current asymmetry caused by the neutral point voltage oscillation in inverter topology reconstruction, a transient compensation method of neutral point voltage offset for the α-axis component of the reference voltage vector is introduced to suppress the adverse effects. The compensation method directly offers a neutral point voltage offset value after Clarke transformation and corrects the α-axis component of the reference voltage vector, avoiding the integral calculation in the conventional voltage compensation algorithm. The correctness and effectiveness of the proposed fault-tolerant control strategy are verified experimentally.

Adaptive fault-tolerant optimal control for hypersonic vehicles with state constrains based on adaptive dynamic programming

This paper addresses a novel adaptive fault-tolerant control (FTC) design based on adaptive dynamic programming (ADP) technique for hypersonic vehicle (HSV) subject to actuator fault and state constrains. The total control input is constructed by the combination of backstepping-based adaptive FTC and the ADP-based adaptive optimal control to improve the tracking performance and fault-tolerant capacity. By introducing a barrier Lyapunov function (BLF) to deal with the state constraints, a backstepping-based FTC scheme is designed to transform the tracking control problem into an equivalent optimal control problem. Subsequently, an adaptive optimal control strategy is developed by using the ADP technique to provide a supplementary control action. A critic network is constructed to solve the Hamilton–Jacobi–Bellman (HJB) equation online. The convergence properties of the closed-loop system are developed by utilizing the Lyapunov stability theory. Finally, simulation results are carried out to illustrate the effectiveness and efficiency of the proposed adaptive ADP-based FTC strategy.

Reduced-order fault estimation observer based fault-tolerant control for switched systems

This paper studies the fault-tolerant control (FTC) problem for switched systems with actuator fault. The reduced-order observers based method is proposed to reconstruct the system state and fault, simultaneously, where the fault can be large and fast time-varying. If the disturbance is ignored, the exponentially stable estimation result can be achieved. Furthermore, the FTC strategy is considered to stabilize the systems. Under any switched law, the root-mean-square (RMS) gain is considered to realize the robustness of the discussed technique to the disturbance. Compared with the traditional H∞ performance, it not only relaxes the limitation of disturbance being with bounded energy, but also removes the requirement of zero initial condition. In the fault estimation process, the zero initial condition requires the state and fault initial values should be known, which is not needed in this paper. At last, the effectiveness of the considered technique is verified by two examples.

Fault-tolerant control of automatic carrier landing using direct lift control based on nonsingular terminal sliding mode and active disturbance rejection control

This paper presents a fault-tolerant control scheme, combining nonsingular terminal sliding mode and active disturbance rejection control (NTSM-ADRC) to address actuator failure and external disturbances during the automatic carrier landing process of a carrier-based aircraft using direct lift control (DLC). First, the carrier-based aircraft model, the carrier air-wake model, and the actuator fault model were established. Second, the NTSM-ADRC controller is designed, The unmodeled dynamics of the system, the air-wake disturbance, and the fault term are treated as total disturbances and estimated accurately by extended state observer (ESO). To improve the response characteristics of the controller, the nonlinear error feedback control law is designed by combining the NTSMC. The Lyapunov function is constructed to prove the stability of the closed-loop system. The controller is applied to the aircraft DLC channel, attitude auxiliary channel, and approach power compensation system. The DLC improves the performance of fixed-wing aircraft by directly generating high lift through the flaps to change the aircraft trajectory. Finally, the method is tested by introducing various types of actuator failures. Simulation results demonstrate that the designed longitudinal fault-tolerant carrier landing system exhibits strong robustness and fault tolerance, thereby improving the accuracy of aircraft landing trajectory tracking.

Neural network-based robust adaptive super-twisting sliding mode fault-tolerant control for a class of tilt tri-rotor UAVs with unmodeled dynamics

Abstract Aiming at alleviating the adverse influence of coupling unmodeled dynamics, actuator faults and external disturbances in the attitude tracking control system of tilt tri-rotor unmanned aerial vehicle (UAVs), a neural network (NN)-based robust adaptive super-twisting sliding mode fault-tolerant control scheme is designed in this paper. Firstly, in order to suppress the unmodeled dynamics coupled with the system states, a dynamic auxiliary signal, exponentially input-to-state practically stability and some special mathematical tools are used. Secondly, benefiting from adaptive control and super-twisting sliding mode control (STSMC), the influence of the unexpected chattering phenomenon of sliding mode control (SMC) and the unknown system parameters can be handled well. Moreover, NNs are employed to estimate and compensate some unknown nonlinear terms decomposed from the system model. Based on a decomposed quadratic Lyapunov function, both the bounded convergence of all signals of the closed-loop system and the stability of the system are proved. Numerical simulations are conducted to demonstrate the effectiveness of the proposed control method for the tilt tri-rotor UAVs.