Types Of Actuator Faults Research Articles

Adaptive fault tolerant control of unmanned underwater glider with predefined-time stability

Actuator faults of the underwater gliders (UGs) not only jeopardize the motion control performance but may also threaten the sailing safety. This paper proposes an adaptive sliding mode fault-tolerant controller with predefined-time stability for the UGs, considering the modeling uncertainties and the unknown disturbances. Three types of actuator faults are developed and incorporated in the fault model of the UGs, which are utilized for the fault tolerant controller design. Then, the adaptive terms are utilized to estimate the modeling uncertainties and the unknown disturbances. An adaptive sliding mode fault tolerant controller is thus designed with the theoretical proof that the global stability can be achieved within a predefined time. The hardware-in-the-loop simulations are conducted to verify the effectiveness of the proposed fault tolerant controller. The simulation results show that the UG can achieve the stability of the pitching attitude under three kinds of actuator fault conditions.

Addressing Actuator Saturation during Fault Compensation in Model-Based Underwater Vehicle Control

Robust control systems are a necessity for autonomous underwater vehicle (AUV) systems due to the challenges they face during operation. Many AUV control-design methods have been developed for different actuator configurations, with robustness against model parameter uncertainties, environmental disturbances, and system faults. Actuator faults can reduce the physical capabilities of a system, which can be compensated for through control re-allocation. However, the increased control allocation to the remaining actuators may cause actuator saturation and reduce controller performance. In this work, we present a depth-pitch model-based nonlinear control law that directly considers actuator saturation, and a fault-tolerant control allocation method for a hybrid AUV actuator configuration. Two types of actuator faults are considered for an underwater vehicle with a hybrid actuator configuration. The proposed controller is implemented in a simulated system, and its trajectory tracking performance is compared with a baseline system without fault or saturation tolerance. To determine the utility of the proposed saturation and fault tolerance control methods, the tracking performance in these simulations is quantified in terms of the settling time, post-fault peak values, and root mean square of the depth and pitch errors.

Adaptive Fault-Tolerant Control for a 2-Body Point Absorber Wave Energy Converter Against Actuator Faults: An Iterative Learning Control Approach

In this paper, the design issue of adaptive fault-tolerant control (FTC) is investigated for a class of continuous-time 2-body point absorber wave energy converter (WEC) systems against actuator faults based on the iterative learning approach. The actuator faults considered in this paper contain both the lock-in-place and the loss of effectiveness faults, simultaneously. The WEC dynamic equations, including two moving parts (i.e., the float and the spar), are firstly transformed into a state-space model. Then, a group of novel iterative learning based adaptive multiple controllers are developed to decrease the tracking error between the measurement output and the desired output, and two novel adaptive laws are designed to cope with two types of actuator faults. Based on the theories mentioned above, a novel algorithm is provided to present the operation flows of both adaptive laws and iterative learning. Furthermore, a sufficient condition is obtained with the aid of proper Lyapunov function, such that the related closed-loop faulty-WEC system is asymptotically stable with a guaranteed <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance index. Finally, an example with a set of physical parameters of a WEC dynamic model is worked out to verify the applicability and effectiveness of the proposed iterative learning based adaptive FTC strategy.

Robust adaptive fixed-time control for a class of nonlinear systems with actuator faults

This paper addresses the output tracking problem of adaptive fixed-time fault-tolerant control for a class of nonlinear systems. In particular, we focus on two types of actuator faults: lock-in-place and loss of effectiveness. Specifically, a robust adaptive fault-tolerant controller is designed to compensate for the effect of actuator faults. By applying the classical backstepping design algorithm and fixed-time control theory, an adaptive fixed-time controller is developed, ensuring that the tracking error converges into a small neighbourhood around the origin within a fixed time where the convergence time is independent of initial conditions. Theoretical analysis and simulation outcomes prove that the closed-loop system is fixed-time stable and all signals are bounded by choosing the parameters appropriately. The effectiveness and feasibility of the presented control scheme are verified through the simulation results.

Output‐feedback boundary adaptive fault‐tolerant control for scalar hyperbolic partial differential equation systems with actuator faults

SummaryThis article studies the output‐feedback adaptive fault‐tolerant boundary control problem for scalar hyperbolic partial differential equation systems with actuator faults. All the coefficients of the controlled plant are unknown, and two types of actuator faults, that is, multiplicative faults and additive faults, are considered simultaneously. For the state estimation problem, two filters are constructed, based on which an observer is obtained to estimate the system state. A parametric model is established for actuator faults, based on which the parameter updating laws of gradient type are then developed to identify actuator faults and to estimate the unknown system coefficients. With the observer and the parameter updating laws, an output‐feedback adaptive fault‐tolerant boundary control law is developed via infinite‐dimensional backstepping method. The boundness of all the signals involved in the control design is guaranteed and the convergence of system states is also confirmed. Finally, the simulation results are given to testify the effectiveness of the proposed control scheme.

TRACKING CONTROL AND STABILIZATION OF A FRACTIONAL FINANCIAL RISK SYSTEM USING NOVEL ACTIVE FINITE-TIME FAULT-TOLERANT CONTROLS

This paper introduces a fractional-order financial risk system for the first time. Employing well-known tools and analyses such as bifurcations diagrams and spectral entropy, the dynamical behaviors of the system associated with fractional derivative are investigated. The impacts of the fractional derivative on the system’s behavior and its dynamical feature are shown. Then, tracking control and stabilization of the systems are studied. As it is obvious, the existence of faults and failures in the process of control of financial and economic systems is undeniable — this issue necessitates applying proper control techniques for the systems. So as to achieve appropriate results in the control of fractional financial risk system, two finite-time fault-tolerant controllers are proposed, namely, finite-time active fault-tolerant control and finite-time passive fault-tolerant control. Not only do these techniques force the system to reach desired values in finite time, but also, the proposed techniques are robust against uncertainties, faults, and failures in actuators. Through finite-time observers, the effects of all uncertainties are taken to account in the active controller. Finally, numerical simulations of tracking control and stabilization are presented. For numerical simulations, the fractional financial risk system is considered to be in the presence of unknown disturbance as well as faults and failures in actuators. It is assumed that the system is in the presence of various types of actuator faults. Numerical results affirm the ability of the offered control techniques for pushing the states of the fractional-order risk system to the desired value in a short period of time.

Fault‐tolerant consensus for switched multiagent systems with input saturation

AbstractThis article investigates the fault‐tolerant consensus problem for switched multiagent systems with input saturation. Actuator faults including partial loss of effectiveness, outage, bias, and stuck are all considered in switched general linear systems. By utilizing the adaptive projection algorithm, low gain feedback theory, and average dwell time method, novel saturated consensus protocols are designed for both fixed and switching topologies with local information of neighboring agents. It is proven that the fault‐tolerant consensus problem can be solved with the proposed protocols in both leader‐following case and leaderless case. The innovation of this article lies not only in the fact that actuator faults, switched dynamics, and input saturation are simultaneously considered, but also in the fact that a novel modified low‐and‐high gain feedback approach is introduced to deal with various types of actuator faults. Finally, two numerical examples are given to validate the effectiveness of the theoretical results.

Improved disturbance-observer-based fault-tolerant control for the linear system subject to unknown actuator faults and multiple disturbances

The problem of fault-tolerant control for the time-invariant system subject to actuator faults and multiple disturbances is focused. The multiple disturbances are composed of two kinds: one is a norm-bounded vector; the other described by an exogenous system is viewed as a harmonic signal with known amplitude and unknown frequency and phase. An improved disturbance observer is designed to obtain the modelled disturbance with partially known information. Based on this, two novel fault-tolerant control algorithms are put forward to the analysis and compensate two different types of actuator faults (one is norm-bounded, and the other is with an unknown boundary). The effectiveness and robustness of control schemes can be exhibited through some numerical simulations with different cases.

Adaptive unknown input observer approach for multi-fault diagnosis of PEM fuel cell system with time-delays

An adaptive unknown input observer (AUIO) for polymer electrolyte membrane fuel cell system with time-delays is developed and applied to formulate a fault diagnosis algorithm for multiple actuator fault detection and isolation (MAFDI). In a scheme based on multiple-model, a group of observers are developed based on a model that describes the system in the presence of a specific actuator fault. The observers are used to generate fault-dependant residual signals. When a model matches the system, the residual signal is zero and becomes non-zero in case of a faulty scenario. Two types of actuator faults are considered namely stuck fault, where the inputs delivered by the faulty actuators are blocked to constant value, and loss of effectiveness fault. The effectiveness of the proposed AUIO and MAFDI algorithm is shown with simulation results.

Fault-tolerant control for commercial aircraft with actuator faults and constraints

In this paper, a constrained control scheme based on model reference adaptive control is investigated for the longitudinal motion of a commercial aircraft with actuator faults and saturation nonlinearities. Actuator faults and constraints are both important factors adversely affecting the stability and performance of flight control systems. An adaptive adjustment law based on Lyapunov function is utilized to adjust the fault-tolerant control law. Both additive and multiplicative faults are considered in the designed controller to deal with the three types of actuator faults: locked in place, loss of effectiveness, and bias. Moreover, different techniques are implemented in the basic and fault-tolerant controller to anti-windup. Proofs for the stability of the two modified controllers which improve the performance of control system operating in the presence of actuator faults and saturations are proposed. Finally, a numerical example of the anti-windup fault-tolerant controller for a commercial aircraft is demonstrated. The stability and performance improvements can be accrued with the presented fault-tolerant control scheme.

Online Identification of Aircraft Dynamics in the Presence of Actuator Faults

In this paper, a multiple model-based nonlinear identification approach is introduced for a conventional aircraft in the presence of different types of actuator faults. Occurrence of actuator faults can obviously reduce the validity of a predetermined dynamic model of nonlinear systems. In such cases, use of multi-model structures can be an effective choice. However, determining the optimal validity functions of the local models in a multi-model structure is still a challenging problem. This problem becomes even more challenging in case of unpredictable faults, which are not considered in training the local models. In this paper, two effective techniques are proposed for online determination of the validity functions of local models called the Error-based Gaussian validity functions (E-GVF) and the Online Sequential Extreme Learning Machine (OSELM)-based approach. Accordingly, there is no need to employ a separate Fault Detection and Isolation (FDI) block in the proposed identification approach. Also, due to great capabilities of neural networks for modeling complex nonlinear systems, recurrent neural networks are used as the local models of the proposed multi-model structure. The obtained simulation results indicate the capability of the proposed OSELM-based multi-model structure for nonlinear identification of complex dynamic systems in the presence of both predictable and unpredictable actuator faults.

Observer-Based Fault-Tolerant Controller for Uncertain Steer-by-Wire Systems Using the Delta Operator

A fault-tolerant control (FTC) for vehicle Steer-by-Wire (SbW) systems in the presence of actuator fault and bounded uncertainties is proposed. The minimax model predictive control (MPC) in the delta-domain is deployed to achieve the tracking performance under the actuator fault, system uncertainties, and disturbance. The feedback control action based on estimation error in parallel with the minimax MPC controller, ensures the system's robust asymptotic stability in the presence of estimation errors. A fault observer is developed to estimate both the fault information and the faulty SbW system. Both simulation and experimental results demonstrate that the proposed FTC strategy can handle various types of actuator faults. It has better robustness to system uncertainties and estimation errors compared to shift-operator-based MPC controller and PD controller, and maintains superior steering performance.

Robust observer based Fault Tolerant Tracking Control for T–S uncertain systems subject to sensor and actuator faults

This paper investigates the sensor and actuator fault (SAF) estimations and the fault tolerant tracking control (FTTC) problem for uncertain systems represented by Takagi–Sugeno (T–S) fuzzy model affected by Unknown Bounded Disturbance (UBD). A robust descriptor adaptive observer based FTTC is firstly designed to simultaneously estimate the unmeasurable system states and SAF vectors and then to track reference trajectories. Sufficient design conditions are developed in terms of Linear Matrix Inequalities (LMIs). The gains of both observer and fault tolerant controller are computed by solving a set of LMI constraints in single step. Robustness against external disturbances is analysed using the H∞ performance index to attenuate its effect on the tracking error for bounded reference inputs. Finally, simulation results are illustrated by considering three types of actuator faults. Moreover, two comparisons are presented to show the mentioned process effectiveness.

Delta Operator-Based Model Predictive Control With Fault Compensation for Steer-by-Wire Systems

In a Steer-by-Wire (SbW) system, the mechanical linkages which connect the steering wheel to front wheels are replaced by a digitally controlled steering system. In spite of improved vehicle safety due to better steering capability, the SbW system actuator failure may lead to unwanted steering performance or even instability. A fault tolerant model predictive control (MPC) with fault compensation for SbW systems based on delta operator for actuator faults is proposed. It deploys an observer to estimate both the fault information and the faulty SbW system states. At each sampling time, the MPC immediately compensates for the fault. The gains of the observer and the fault tolerant MPC controller are obtained by solving a linear matrix inequality derived from the Lyapunov theory. The simulation results illustrate that the proposed fault tolerant control strategy can counter the various types of actuator faults and maintain superior steering performance to shift operator-based MPC controller.

Fault Tolerant Control Scheme for Robotic Manipulators Affected by Torque Faults

A Fault Tolerant Control (FTC) scheme for robotic manipulators affected by actuator faults is proposed in this paper. The actuator fault consists in an unknown partial joint torque reduction, which causes a loss of the desired end-effector motion. The FTC scheme includes a Fault Detection and Diagnosis (FDD) system based on a first-order sliding mode observer, in order to detect and estimate the joint torque fault. The estimated fault is mapped into a kinematic deviation of the motion of the end effector from the desired one, and compensated at the level of the kinematic controller. Simulation results demonstrate the effectiveness of the proposed scheme for a planar manipulator affected by two types of actuator faults, namely bias fault and partial torque fault.

Adaptive Fuzzy Observer-Based Fault-Tolerant Control for Takagi–Sugeno Descriptor Nonlinear Systems with Time Delay

This paper investigates the problems of state/fault estimation and active fault-tolerant control (AFTC) design for time-delay descriptor fuzzy systems subject to external disturbances and actuator faults. Using Takagi–Sugeno fuzzy models, an adaptive fuzzy observer is proposed to achieve system state and actuator fault estimation simultaneously. According to Lyapunov functional method, design and analysis conditions of the resulting closed-loop delayed descriptor system are formulated in terms of linear matrices inequalities (LMIs). Observer and controller gains are computed by solving a set of LMIs in only one step and then used to both estimate the unmeasured states and actuator faults in AFTC context. Numerical examples are provided to show the merit and the conservativeness of the proposed approach in comparison with the existing methods by considering various types of actuator faults.

Distributed reconfigurable control strategies for switching topology networked multi-agent systems

In this paper, distributed control reconfiguration strategies for directed switching topology networked multi-agent systems are developed and investigated. The proposed control strategies are invoked when the agents are subject to actuator faults and while the available fault detection and isolation (FDI) modules provide inaccurate and unreliable information on the estimation of faults severities. Our proposed strategies will ensure that the agents reach a consensus while an upper bound on the team performance index is ensured and satisfied. Three types of actuator faults are considered, namely: the loss of effectiveness fault, the outage fault, and the stuck fault. By utilizing quadratic and convex hull (composite) Lyapunov functions, two cooperative and distributed recovery strategies are designed and provided to select the gains of the proposed control laws such that the team objectives are guaranteed. Our proposed reconfigurable control laws are applied to a team of autonomous underwater vehicles (AUVs) under directed switching topologies and subject to simultaneous actuator faults. Simulation results demonstrate the effectiveness of our proposed distributed reconfiguration control laws in compensating for the effects of sudden actuator faults and subject to fault diagnosis module uncertainties and unreliabilities.

Fault-Tolerant Economic Model Predictive Control Using Error-Triggered Online Model Identification

In this work, we present a data-driven methodology to overcome actuator faults in empirical model-based feedback control. More specifically, we introduce the use of a moving horizon error detector that quantifies prediction errors and triggers updating of the model used in the controller online when significant prediction errors occur due to the loss of one of the actuators. Model reidentification is conducted online using the most recent input/output data collected after the fault occurrence. The error-triggered online model identification approach can be applied to overcome various types of actuator faults, including the case where the value at which the actuator is stuck is known and the case where the value at which the actuator is stuck is unknown. The proposed methodology is applied in an economics-based feedback controller, termed economic model predictive control (EMPC), that uses a model obtained either from first-principles or from plant data to optimize plant economics online. Two different che...

A new global fuzzy fault-tolerant control for a double inverted pendulum based on time-delay replacement

In this paper, a delay replacement-based adaptive fault-tolerant control method is proposed for a double inverted pendulum connected by an unknown device. By combining fuzzy approximation and integer backstepping, a new time-delay assumption-independent state feedback decentralized control scheme is developed based on directly replacing the unbounded time-delay argument of fuzzy approximators with the bounded reference signals. Furthermore, all of the two typical types of actuator faults can be compensated for on-line. Compared with the existing results, the time-delay assumptions that need to be test and verify in applications are eliminated, and global bounded stability of the closed-loop system is guaranteed. Simulation results are provided to show the effectiveness of the control approach.

Robust Fault-Tolerant Control for a Class of Second-Order Nonlinear Systems Using an Adaptive Third-Order Sliding Mode Control

Due to the robustness against the uncertainties, conventional sliding mode control (SMC) has been extensively developed for fault-tolerant control (FTC) system. However, the FTCs based on conventional SMC provide several disadvantages such as large transient state error, less robustness, and large chattering, that limit its application for real application. In order to enhance the performance, a novel adaptive third-order SMC, which combines a novel third-order sliding mode surface, a continuous strategy and an adaptation law, is proposed. Compared with other innovation approaches, the proposed controller has an excellent capability to tackle several types of actuator faults with an enhancing on robustness, precision, chattering reduction, and time of convergence. The proposed method is then applied for an attitude control of a spacecraft and the results demonstrate the superior performance.