Effects Of Actuator Faults Research Articles

Robust dynamic output feedback predictive fault‐tolerant control for discrete uncertain systems

AbstractA robust predictive fault‐tolerance control method integrating dynamic output feedback is proposed for discrete industrial processes with unmeasurable states, actuator faults, uncertainties, and external disturbances. First, a new iterative error model is developed, which extends the output tracking error to increase the freedom of controller regulation and ensure the tracking performance of the system. Second, a robust dynamic output feedback predictive fault‐tolerant controller is designed based on the preceding model. According to the Lyapunov stability theory, the robust stability criterion of the system is performed in the case of actuator faults, and the stability conditions of the system in the form of linear matrix inequality are given. The real‐time optimal control law gains are obtained by solving the stability conditions online. This method can effectively suppress the effects of actuator faults, uncertainties and external disturbances on the system with unmeasurable states, which can guarantee the tracking performance and stability of the system. The effectiveness of the proposed method is finally verified by using an injection molding process as an example.

Neuroadaptive Cooperative Fault-Tolerant Control of Heterogeneous Multiagent Systems Based on Fully Actuated System Approaches.

The leader-following cooperative problem in heterogeneous multiagent systems (HMASs) with unmodeled dynamics and actuator faults is investigated in this article. The HMASs, which include unmanned ground vehicles and unmanned aerial vehicles, are first described using a fully actuated system model (FASM). The FASM, as opposed to the first-order state-space model, preserves the physical significance of original systems and makes it feasible to apply the control rule entirely. In order to approximate unknown system dynamics, novel neuroadaptive laws with few learning parameters are then suggested. To counteract the negative effects of actuator faults, the Nussbaum function and adaptive approach are utilized. In addition, a cooperative fault-tolerant protocol is suggested, wherein consensus errors are uniformly ultimately bounded. The lack of virtual control variables in the proposed protocol reduces its complexity. The theoretical results are then validated by numerical simulations.

Observer‐based optimal fault‐tolerant tracking control for input‐constrained interconnected nonlinear systems with mismatched disturbances

SummaryThis paper investigates an observer‐based optimal fault‐tolerant tracking control problem for interconnected nonlinear systems with input constraints and mismatched disturbances via adaptive dynamic programming (ADP). Firstly, an augmented system consisting of tracking error and the reference trajectory is constructed, and then the original optimal tracking control problem is transformed into the optimal regulation control problem of the augmented system. An integral sliding‐mode‐based optimal fault‐tolerant control scheme is developed to eliminate the effect of actuator faults and guarantee the optimal control performance. Furthermore, a neural network‐based observer is designed to identify the completely unknown system dynamics based on the input‐output data, thereby relaxing the restriction on system dynamics. Subsequently, the modified Hamilton‐Jacobi‐Bellman equations are solved by using the ADP algorithm under a critic network framework. According to the Lyapunov approach, all signals in the closed‐loop augmented system are uniformly ultimately bounded. Finally, the effectiveness of the developed control scheme is demonstrated via simulation results.

H ∞-based truncated predictive control for switched nonlinear cyber physical systems subjected to actuator faults and deception attacks

ABSTRACT This paper emphasises the study of switched nonlinear cyber-physical systems (CPSs) subjected to input delay, actuator faults and deception attacks by a H ∞ -based truncated predictive control design. Particularly, the predictive controller uses delayed state information in addition to the traditional feedback control to estimate the present state for the feedback. Furthermore, the proposed control design is modelled with a truncated predictive approach which is also used to compensate the effects of actuator faults and attacks that also satisfy a predefined H ∞ index simultaneously. With the assistance of the Lyapunov stability theory, a novel set of adequate criteria are acquired in terms of LMIs which assure the asymptotical stability of the switched nonlinear CPS under prescribed predefined H ∞ performance levels. Eventually, the proposed theoretical results are validated through two numerical examples.

Reliable [formula omitted] fuzzy control for fault-tolerant actuator failures of active suspension system

A new methodology for fault tolerant control (FTC) is proposed to compensate actuator failures using Takagi–Sugeno systems. This makes possible to design the controller that represents actuator failures using a scaling factor by solving a family of linear matrix inequalities (LMIs). The resulting control system guarantees asymptotic stability, compensates the effect of actuator faults and ensures certain an H∞ performance level. This methodology is applied to the active suspension systems that motivated this research, where in the context of active suspension (AS) systems, the guaranteed performance correspond to ride comfort in the presence of road disturbances. Thus, a controller is developed for a quarter-car model with active suspension. The simulated results illustrate the effectiveness of the proposed approach.

Adaptive fuzzy fault‐tolerant control of stochastic nonlinear multiagent systems with input quantization and state constraints

SummaryThis paper is dedicated to the problem of adaptive fuzzy fault‐tolerant control (FTC) for a class of stochastic nonstrict feedback nonlinear multi‐agent systems (MASs) with input quantization and full state constraints. Firstly, based on the backstepping technique and the bounded estimation method, the effect of actuator faults can be eliminated by the proposed adaptive updating laws. Secondly, the stochastic barrier Lyapunov functions (BLFs) are constructed to ensure that all state constraints are not violated. Meanwhile, the introduction of input quantization can effectively save network resources and reduce computational burden. It is further shown that all the closed‐loop signals are uniformly bounded, and the consensus tracking errors asymptotically tend to zero. The effectiveness of the proposed control scheme is illustrated by a numerical example.

Nussbaum-Based Adaptive Fault-Tolerant Control for Nonlinear CPSs With Deception Attacks: A New Coordinate Transformation Technology.

In this article, two novel adaptive fault-tolerant control schemes for a class of nonlinear strict-feedback cyber-physical systems (CPSs) with deception attacks are presented. Deception attacks, such as false data-injection attacks, which destroy sensor networks, make the outputs and states of the CPSs unavailable. It is very difficult and challenging for a designer to achieve the tracking control under the circumstance of cyberattacks. To realize the tracking control for the studied CPSs, we propose a new coordinate transformation technology without precedent, where it takes the attack gains into account and uses the compromised states to design the corresponding controllers. In the backstepping design process, Nussbaum functions are presented to alleviate the influence of the unknown attack gains. Furthermore, we consider the actuator faults problem, which includes the loss of effectiveness and the bias fault. By skillfully designing the adaptive laws, the effect of actuator faults is completely eliminated. It is theoretically proved that the first proposed tracking control scheme can guarantee all signals in the closed-loop system are bounded and the output can track the desired reference signal. In addition, the second adaptive control scheme is also developed for the CPSs under the actuator faults and a more general assumption on the deception attacks is proposed simultaneously. Finally, the feasibility of the new proposed methods is verified by MATLAB simulation analysis.

Effects of actuator faults on large-scale wind turbine dynamics with an industry-standard controller

The pitch actuator is a critical component of large-scale wind turbines with a high failure rate. Actuator faults significantly impact the dynamics of wind turbines, leading to increased loads on the turbine structure and reduced power output, thereby affecting wind turbine performance and reliability. This paper investigates the effects of actuator faults on a 5-MW reference wind turbine using the OpenFAST simulation software developed by NREL. The fault cases include dynamic changes in the actuator, performance reduction, and, finally, actuator seizing.

Robust adaptive backstepping neural networks fault tolerant control for mobile manipulator UAV with multiple uncertainties

The present study outlines the development of an Adaptive Backstepping Radial Basis Function Neural Networks Fault Tolerant Control (ABRBFNNFTC) methodology. The aforementioned methodology is employed to address the challenge of achieving trajectory following in the context of a Mobile Manipulator Unmanned Aerial Vehicle (MMUAV) when subjected to the effects of actuator faults and parametric uncertainties. The utilization of an adaptive radial basis function neural networks (RBFNNs) controller is employed for the purpose of approximating an unidentified nonlinear backstepping controller that relies on the precise model of the MMUAV. The Lyapunov direct method is utilized to establish the stability analysis of the entire system. The closed-loop system guarantees the Uniformly Ultimately Bounded (UUB) stability of all signals. The control methodology put forth ensures the achievement of a prescribed trajectory, and mitigates the impact of uncertainties and actuator faults. The efficiency of the proposed ABRBFNNFTC scheme is demonstrated through the presentation of extensive simulation studies.

Switched-type unknown input observer-based fault-tolerant control for cyber-physical systems in the presence of denial of service attack

The problem of security control for cyber-physical systems (CPSs) is gradually becoming a popular research topic. In the presence of the denial-of-service (DoS) attack, this paper investigates the switched-type unknown input observer-based fault-tolerant control problem for multi-channel CPSs. Firstly, based on the sampling mechanism, a switched-type unknown input observer (SUIO) which can discard the outdated information is designed to obtain state/fault estimations, and converting the estimation error system stability analysis under DoS attack into that under SUIO. Then, to compensate the effect of actuator fault, an SUIO-based fault-tolerant controller is designed. And the input-to-state stability of the CPSs is analyzed. In comparison with the existing UIO studies, this paper considers the case of DoS attack affecting the transmission channel, and the impact of DoS attack on estimation effect can be effectively reduced by introducing the switching mechanism. Finally, based on the simulation results of the given experiments, the effectiveness of the proposed method is illustrated.

Hybrid Attitude Saturation and Fault-Tolerant Control for Rigid Spacecraft without Unwinding

This paper tackles the saturation and fault-tolerant attitude tracking problem without unwinding for rigid spacecraft with external disturbances and partial loss of actuator effectiveness faults. A hybrid saturation and fault-tolerant attitude control (HSFC) is proposed. The Lyapunov method is employed to prove that the tracking errors of the spacecraft system tend to the equilibrium point asymptotically with HSFC. The advantages of the HSFC are that it is fault-tolerant, anti-unwinding and explicitly upper bounded a priori which means that both actuator saturation and the unwinding phenomenon can be avoided. Simulations verify the effectiveness of the proposed approach.

Event-triggered adaptive robust fault-tolerant control for a class of uncertain switched nonlinear systems

In this paper, the adaptive robust fault-tolerant control problem for a class of switched nonlinear systems with parameter uncertainty, disturbances and actuator failures is concerned based on event-triggered control strategy. The adaptive laws based on state-dependent switched strategy are designed to eliminate the effects of actuator faults and parameter uncertainties by using the estimations of the unknown upper bounds of uncertain parameters. Then, the robust fault-tolerant technique and multiple Lyapunov functions method are used, the designed controller can guarantee that all signals of the switched closed-loop systems are uniformly bounded. Meanwhile, the desired performance of the systems is promised. Finally, the simulation results are given to illustrate the effectiveness of the proposed design method.

Cooperative Fault-Estimation-Based Event-Triggered Fault-Tolerant Voltage Restoration in Islanded AC Microgrids

In this paper, the problem of secondary voltage restoration in an islanded microgrid (MG) is considered, in which the actuator of the distributed generators (DGs) may coexist with partial loss of effectiveness (PLOE) fault and bias fault. For each DG, an adaptive event-triggered fault-tolerant (ETFT) control protocol is designed to compensate for the effects of actuator faults in the DGs, thereby restoring the voltage to the reference value. The dependent event triggering mechanism saves the processor&#x2019;s computational resources. A desirable feature of the protocol proposed in this paper is that the control protocol relies only on relative information between neighboring DG&#x2019;s, independent of global information about the network graph, fault boundaries, and network scale. It means that the protocol is implemented in a fully distributed framework. The protocol fully applies to the common ETFT consensus control problem of linear multiagent systems (MASs) with actuator faults. Furthermore, comprehensive theoretical arguments for consensus stability and analysis of Zeno behavior ensure the approach&#x2019;s feasibility. The simulation results verify the effectiveness of the algorithm. <i>Note to Practitioners</i>&#x2014;This paper aims to propose a fully ETFT control protocol for secondary voltage restoration of an islanded MG. The control protocol consists of a linear term and a nonlinear time that compensates for the multiplicative and additive fault of the actuator. Moreover, DGs&#x2019; communication structure and global fault boundaries may be unknown in practice. Hence, adaptive coupling gains that depend only on the sampled relative information of DGs are introduced to estimate the controller gain, thus avoiding global information. A feasible strategy is provided for industrial applications.

Neural Network-Based Robust Bipartite Consensus Tracking Control of Multi-Agent System with Compound Uncertainties and Actuator Faults

This paper addresses the challenging problem of bipartite consensus tracking of multi-agent systems that are subject to compound uncertainties and actuator faults. Specifically, the study considers a leader agent with fractional-order nonlinear dynamics unknown to the followers. In addition, both cooperative and competitive interactions among agents are taken into account. To tackle these issues, the proposed approach employs a fully distributed robust bipartite consensus tracking controller, which integrates a neural network approximator to estimate the uncertainties of the leader and the followers. The adaptive laws of neural network parameters are continuously updated online based on the bipartite consensus tracking error. Furthermore, an adaptive control technique is utilized to generate the fault-tolerant component to mitigate the partial loss caused by actuator effectiveness faults. Compared with the existing works on nonlinear multi-agent systems, we consider the compound uncertainties, actuator faults and cooperative–competition interactions simultaneously. By implementing the proposed control scheme, the robustness of the closed-loop system can be significantly improved. Finally, numerical simulations are performed to validate the effectiveness of the control scheme.

Event-Triggered Prescribed Performance Fuzzy Fault-Tolerant Control for Unknown Euler–Lagrange Systems With Any Bounded Initial Values

This paper investigates the tracking problem of event-triggered prescribed performance fuzzy fault-tolerant control (FTC) for unknown Euler-Lagrange systems with actuator faults and external disturbances. Firstly, the barrier Lyapunov functions (BLFs) and prescribed performance functions are synthesized to guarantee that the tracking errors satisfy the preset transient performance. Different from existing prescribed performance control methods, which require the initial values of the tracking errors to be within the prescribed performance functions, an error transformation method is introduced to ensure that the tracking errors with any bounded initial values can enter the preset boundaries within a preset time. Then, considering the unavailability of system parameters, the fuzzy logic systems (FLSs) are used to approximate unknown parameters of the system. What's more, to solve the problem of limited communication and computing resources in practical systems, an improved event-triggered control (ETC) scheme is proposed, which can reduce the communication and computation burden without satisfying the input-to-state stability (ISS) assumption. Meanwhile, the Zeno phenomenon can be avoided. Furthermore, the effects of actuator faults and the event-triggered mechanism are handled by Nussbaum gain technology. Finally, the superiority of the proposed control algorithm is verified by simulation results.

Adaptive data-driven fault-tolerant control for nonlinear systems: Koopman-based virtual actuator approach

This paper proposes an adaptive data-driven fault-tolerant control scheme using the Koopman operator for unknown dynamics subjected to nonlinearities, time-varying loss of effectiveness, and additive actuator faults. The main objective of this method is to design a virtual actuator to hide actuator faults from the view of the system’s nominal controller without having any prior knowledge about the system’s underlying dynamics. The designed virtual actuator is placed between the faulty plant and the nominal controller of the system to keep the dynamical system’s performance consistent before and after the occurrence of actuator faults. Based on the Koopman operator theory, an equivalent Koopman predictor is first obtained using the process data only, without knowing the governing equations of the underlying dynamics. Koopman operator is an infinite-dimensional, linear operator which takes the nonlinear process data into an infinite-dimensional feature space where the dynamic data correlations have linear behavior. Next, based on the approximated system’s Koopman operator, a virtual actuator is designed and implemented without knowing the system’s nominal controller. Needless to use a separate fault detection, isolation, and identification module to perform fault-tolerant control, the current method leverages the adaptive framework to keep the system’s desired performance in facing time-varying additive and loss of effectiveness actuator faults. Finally, the approach’s efficacy is demonstrated using simulation on a two-link manipulator benchmark, and a comparison study is presented.

Dynamic event-triggered composite anti-disturbance fault-tolerant tracking control for ships with disturbances and actuator faults

This paper investigates the dynamic event-triggered composite anti-disturbance and fault-tolerant tracking problem of ships with external ocean disturbances and actuator fault effects. The dynamic event-triggered composite anti-disturbance and fault-disturbance tracking is achieved by combining the disturbance observer and the fault observer with the dynamic event-triggering and the vectorial backstepping control method. The nonlinear disturbance observer is constructed to obtain the online external disturbance estimations in the ocean time-varying environment and thus overcome the unexpected disturbances. The actuator fault observer is exploited to achieve the online fault estimations of actuator faults. The dynamic event-triggered mechanism reduces execution frequencies of control signals to mitigate the tear and wear of ship actuators. The dynamic event-triggered composite disturbance compensation fault-tolerant control ensures the globally uniformly ultimately stability of tracking control system and enables the ship to track the expected trajectory with the small errors. Simulations and comparisons with static event-triggered control on a full-scaled ship validate the dynamic event-triggered control.

Command filter-based adaptive fuzzy switching event-triggered control for non-affine nonlinear systems with actuator faults

This paper considers a problem of command filter-based adaptive fuzzy switching event-triggered control for non-affine nonlinear systems with actuator faults. First, a state observer is given to estimate unmeasurable state. Secondly, an error transformation equation is designed to constrain output tracking error, and the feasibility condition of tracking error is not required. Then, a finite time fault-tolerant control scheme is constructed based on command filter and backstepping technologies, which can compensate completely the effects of actuator faults and trigger errors, and there is no differential explosion, singularity phenomenon and Zeno behavior. Besides, a switching event-triggered algorithm is designed to reduce the triggering number under the premise of ensuring the tracking performance. Finally, the proposed algorithm is applied to an one-link manipulator to verify the availability.

Fully Distributed Fault-Tolerant Leaderless Consensus of Multi-Agent Systems Under Directed Communication Graph

This paper investigates a fault-tolerant leaderless consensus problem for general linear multi-agent systems (MASs) under a strongly connected directed communication graph. The influences of the actuator bias faults and loss of actuator effectiveness faults on MASs are considered in this paper. The designed fully distributed adaptive fault-tolerant consensus protocols (FTCPs) can make all agents' states achieve consensus, asymptotically. Using the features of the loss of actuator effectiveness faults and the strongly connected graph, novel positive definite Lyapunov functions are constructed skillfully to analyse the validity of the proposed protocols. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed protocols.

Implementation of adaptive fault‐tolerant tracking control for robot manipulators with integral sliding mode

AbstractThis article presents an adaptive fault‐tolerant tracking control for uncertain robot manipulators. By fully considering the effects of uncertainties and actuator effectiveness faults, an integral sliding manifold with a novel auxiliary function is first proposed for tracking control of robot manipulators. Then, a novel fault‐tolerant tracking control based on the proposed integral sliding manifold is developed to acquire robustness in both reaching and sliding phase. In order to further reduce the effects of uncertainties on tracking performance, an adaptive law is performed to estimate unknown parameters of the upper bounded uncertainties, which further reduces the control torque input in case of the similar tracking performance. The stability of the proposed approaches is accomplished by Lyapunov stable theory and homogeneous technique. The key contributions of the proposed approach are as follows: (i) the reaching phase of sliding mode control is removed completely in the control design and then the tracking system enters the sliding mode from the initial states; (ii) the nominal control term is eliminated in the design of integral sliding surface and then the algebraic loop problem is also avoided in the proposed approach for robot manipulators; (iii) the simple control structure with an adaptive law is obtained better tracking performance by utilizing lower control torque input and then the effects of time‐delay and computational burden are also restrained from the proposed approach. Simulation and experimental comparisons have been accomplished for verifying the effectiveness of the proposed approach.