Actuator Faults Research Articles

Cloud-based time-varying formation active fault-tolerant predictive control of networked multi-agent systems with actuator and sensor faults

This paper addresses the time-varying formation control problem of second-order networked multi-agent systems consisting of a virtual leader and multiple followers, where random communication constraints in the forward and feedback channels as well as actuator and sensor faults are considered. A state observer is designed to estimate the system state and the potential faults, based on which a time-varying formation active fault-tolerant predictive control scheme is proposed. Then, a necessary and sufficient condition is derived to guarantee the stability of the closed-loop system and to achieve the time-varying formation, which is independent of random communication constraints as well as actuator and sensor faults. Finally, simulation results of three contrastive cases are presented to verify the effectiveness of the proposed control scheme.

Adaptive fault-tolerant control for a class of nonlinear multi-agent systems with multiple unknown time-varying control directions

In this paper, we investigate the consensus tracking control for a class of heterogeneous multi-agent systems with multiple unknown time-varying control directions and unknown direction actuator faults. Different from existing work, the directions of the multiple time-varying control coefficients are subject to fault-induced sign-switching. To address this challenge, a series of high-order Lyapunov functions and differentiable functions are introduced to avoid non-integrable terms. Then, a novel contradiction statement and some Nussbaum functions are used to handle the summation of multiple unknown control coefficients with time-varying amplitudes and directions. Meanwhile, a novel distributed observer with quantized communication is introduced to track a reference trajectory with unknown dynamics. It is shown that all closed-loop signals are globally uniformly bounded and the tracking errors converge to residual sets that can be made arbitrarily small. Simulation results illustrate the effectiveness of the proposed scheme.

Robust fault detection and adaptive fixed-time fault-tolerant control for quadrotor UAVs

This note scrutinizes an adaptive fault-tolerant control (FTC) approach tailored for unmanned aerial vehicles (UAVs), addressing the critical need for both fault accommodation and disturbance suppression. Departing from traditional reliance on robust discontinuous control strategies prone to chattering and demanding precise uncertainty bounds, our FTC method ensures fixed-time stability, guaranteeing the convergence of attitude tracking errors to zero. Central to our approach is an adaptive algorithm adept at concurrently estimating unknown actuator faults and upper bounds of lumped uncertainties. Moreover, our adaptive schemes accurately estimate the upper bound of the lumped uncertainty term, encompassing model uncertainties, external disturbances, and unmodeled dynamics, thereby eliminating the need for assuming known bounds on uncertainties. Stability analysis under the developed control law is thoroughly performed using the Lyapunov stability theory. Notably, our strategy employs an extended Kalman filter (EKF) observer for state estimation and fault detection, facilitating fault detection through an adaptive threshold technique dynamically adjusted based on real-time mean and variance of the residual signal. Through comprehensive simulation and experimental validations, our proposed methodology demonstrates significant advancements in ensuring safety and reliability in UAVs.

Robust multiple fault detection and estimation approaches based on adaptive finite‐time observer for nonlinear systems

AbstractThis article investigates robust multiple fault detection (FD) and fault estimation (FE) schemes, based on adaptive finite‐time observer (AFTO), applied to nonlinear systems with disturbances, actuator faults, and sensor faults. The AFTO is designed, and a parameter adaptive law is constructed to continuously optimize the residual based performance function to improve the AFTO robustness. The schemes are able to simultaneously detect and estimate unknown states, disturbances, and faults. The AFTO's design, finite‐time convergence and stability conditions are guaranteed in terms of linear matrix inequalities. Finally, simulation results, based on two typical practical systems, are given to illustrate the effectiveness of the proposed approaches. The simulation results also show that the designed AFTO can offer faster convergence speed, higher estimation accuracy, and stronger robustness than conventional observer and sliding mode observer.

Event-triggered fixed-time fault-tolerant attitude control for the flying-wing UAV using a Nussbaum-type function

This paper introduces an innovative adaptive event-triggered fault-tolerant attitude control framework designed for a flying-wing unmanned aerial vehicle (UAV) operating under constraints such as limited embedded resources, unknown actuator failures, system uncertainties, and external disturbances. The proposed scheme incorporates several noteworthy features: (i) Implementation of a relative threshold event-triggered mechanism to efficiently alleviate communication pressures and computational burdens inherent in the attitude control system. (ii) Utilization of a radial basis function neural network to approximate lumped disturbances, reducing dependence on prior knowledge. (iii) Adaptive compensation for sampling errors and actuator faults by employing the Nussbaum gain. (iv) Integration of a smooth function to address singularity issues and prevent Zeno behavior. Furthermore, Lyapunov analysis validates that all signals within the closed-loop system remain bounded and converge within a predetermined time frame. Comparative numerical simulations underscore the effectiveness and superiority of the proposed control approach.

Incremental fully actuated system approach-based prescribed-time fault-tolerant formation control of helicopters under multiple faults

Helicopter formation is characterized by intricate dynamics, complex mechanics, and challenging scenarios, raising the necessity for agile, robust, and convenient controller design. This paper explores the prescribed-time fault-tolerant formation control of multiple helicopters through the incremental fully actuated system approach, which addresses multiple faults in sensors and swash plate struts. First, the helicopter model encompassing aerodynamic, flapping dynamic, swash plate dynamic, actuator faults, and sensor faults is established and further partitioned into attitude and position subsystems. Then, in the attitude subsystem, a prescribed-time attitude controller based on the incremental fully actuated system approach is proposed to track the desired attitude with robustness against actuator faults, aerodynamic drags, inter-axis coupling, and non-linearity. Next, in the position subsystem, the faults of velocity and position sensors are estimated and compensated through the prescribed-time fault-estimation observer, and a prescribed-time formation controller through the incremental fully actuated system approach is designed to achieve distributed leader-follower formation control. A Task-Fault dual-driven scheduling mechanism of the parameters of the prescribed-time technique is developed to promptly activate the prescribed-time function, and the control scheme is proven to be prescribed-time convergent via Lyapunov stability theory. Finally, numerical simulations are conducted to illustrate the efficiency of the algorithm.

Adaptive event-triggered exponential convergence tolerant control for fuzzy communication delay network systems with actuator faults, deception attacks and disturbances

Adaptive event-triggered exponential convergence tolerant control for fuzzy communication delay network systems with actuator faults, deception attacks and disturbances

Intermediate estimator based finite-time fault-tolerant control for nonlinear switched stochastic systems

The finite time fault-tolerant control problem for switched stochastic nonlinear systems with actuator and sensor faults is studied in this paper. Firstly, the finite-time intermediate estimator is considered to reconstructed the system state, sensor and actuator faults. The proposed observer involves the output estimation error feedback to improve the estimation accuracy. According to the estimator mentioned above, the fault-tolerant controller is proposed to reduce the fault impact. Using the average dwell time and piecewise Lyapunov functions, sufficient conditions for the nonlinear switched stochastic systems to achieve finite-time stochastic boundedness are obtained. Finally, two examples are proposed to illustrate the feasibility of above method.

Robust fault-tolerant preview control for automatic landing of carrier-based aircraft

PurposeThis paper aims to propose the automatic carrier landing system with the fault-tolerant ability for carrier-based aircraft in the presence of deck motion, external airwake disturbance and actuator fault, which consists of the reference trajectory generation module and flight control module.Design/methodology/approachThe longitudinal and lateral basic controllers are designed based on the optimal preview control (OPC), which can ensure favorable tracking performance and anti-disturbance ability of system. Furthermore, based on the OPC, the robust fault-tolerant preview control scheme is proposed to attenuate the impact of actuator fault on system, which ensures the safe landing of carrier-based aircraft in case of actuator failure.FindingsBoth the Lyapunov method and simulations prove that the tracking errors can converge to zero and system states can be asymptotically stable both in normal and fault operations.Originality/valueThe fault-tolerant control strategy is introduced into preview control to deal with actuator fault, which combines feedforward control based on future previewable information and feedback control based on current information to improve the system performance.

A robust [formula omitted] fault-tolerant control approach for time-delay LPV systems with uncertain parameters and unknown disturbances

The article proposes a H∞ fault-tolerant control approach for a series of uncertain linear parameter-varying (LPV) time-delay models to obtain disturbance suppressions. Specifically, by applying the Lyapunov functions, a series of feedback controllers are provided to ensure the robust performance of LPV models with actuator faults. Meanwhile, a convex optimization strategy is developed for resolving optimization problems in the presence of bilinear matrix inequalities (BMIs), where the robustness conditions are improved to guarantee the stability of LPV model under uncertain factors. By resolving a class of linear matrix inequalities (LMIs), the gain matrices for LPV systems can be obtained. Furthermore, the less conservative conditions are developed and supported by strict theoretical derivation. Ultimately, the validity of proposed approach is confirmed by simulation analyses of truck–trailer systems.

Distributed adaptive disturbance observer-based multi-channel event-triggered finite-time coordinated control for multi-UAVs with actuator failures

A finite-time coordination controller based on an adaptive disturbance observer and a multi-channel event-triggered strategy is proposed for the multi-UAVs control problem with actuator faults, external disturbances, and communication constraints. First, an adaptive finite-time disturbance observer based on a hyperbolic tangent function is established to compensate for actuator faults and external disturbances without knowing the upper limit of the total disturbance derivative in advance. Second, a multi-channel event-triggered strategy is proposed to reduce communication between neighboring UAVs, between the controller and actuator, and between the disturbance observer and the controller at the same time. Then, the event-triggered strategy integrates the designed disturbance observer and controller, and the proposed control strategy is analyzed for finite-time stability using Lyapunov stability theory and finite-time theory without applying the separation principle. Finally, the effectiveness of the proposed control scheme is verified by numerical simulations.

Lowering carbon emissions from a zinc oxide rotary kiln using event-scheduling observer-based economic model predictive controller

Background:The leading carbon emitting unit of the zinc smelting industry is the zinc oxide rotary kiln, which preserves a trade-off between carbothermic reduction and the zinc recovery rate. To scale up a substantial zinc restoration rate during the hydrometallurgical process, a substantial amount of coke is combusted, which leads to significant greenhouse gas emissions. It is imperative to mitigate the emission of carbon as reduced as possible. Since the kiln operates in three different regions — gas, solid, and wall — several highly non-uniform paths are typically linked to one another to yield complex looping processes. In industrial settings, solid maldistribution and gas refluxing pose prevalent challenges in the gas–solid flow mechanism. Consequently, control over processes and observation of the internal states/concomitant parameters become critical for ensuring safe and reliable operation. Therefore, it is imperative to devise effective control layouts to optimize the functioning of the kiln system. Method:(i) The usual form of model-predictive control rule is paired with an economic stage cost (using the CasADi optimization method) to offer optimal consumption of the coal and the rotation speed, thereby effectively alleviating the adverse effects of the unmeasured perturbations, actuator faults, or multi-sensor failures. (ii) With the aid of accessible state sensors, a cubature Kalman filter infused with a singular-value-decomposition strategy reliably predicts uncertainties/faults of the actuators or the unmeasured states of the kiln. (iii) cubature Kalman filter and event-triggered scheduling are utilized together, to consume less communication resources. Significant findings:A variety of indicators, such as zinc recovery rate (1.35% improvement), carbon emissivity (11.54% improvement), residence time (6% shorter), accuracy of the controllers/observers were well assessed and compared with standard form of the non-linear model predictive control law to figure out the efficiency and acceptability of the economic model predictive controller, demonstrating on an industrial rotary kiln. An in-depth study of the proposed control method satisfying Lyapunov inequality has been addressed.

Adaptive fixed-time fuzzy fault-tolerant control for robotic manipulator with unknown friction and composite actuator faults

This paper exploits the issue of fixed-time (FT) tracking control (TC) for uncertain robotic manipulator systems (RMS) with composite actuator faults (CAFs), unknown disturbances and joint friction. The fuzzy logic system (FLS) algorithm is introduced to fit the unknown uncertainties including unmodeled parameters, CAFs and joint friction of the RMS, after which a relevant updating algorithm is employed to generate the unidentified boundary of the plant disturbance and FLS approximation error. Then a novel adaptive fuzzy sliding mode (SM) fault-tolerant controller is synthesized, which not only guarantees the boundedness of estimation errors of the involved adaptive parameters, but also actualizes the reachability of the predevised sliding surface. Furthermore, the proof that the system trajectories can achieve the FT convergence to the expected position signals, is then provided on account of the FT stability theory. Ultimately, simulation experiments exhibit the rationality based upon the current control algorithm.

Image-Based Visual Servoing for Three Degree-of-Freedom Robotic Arm with Actuator Faults

Image-Based Visual Servoing for Three Degree-of-Freedom Robotic Arm with Actuator Faults

Optimal control of the E–L dynamic systems during the actuator faults

AbstractIn this article, we deal with finite‐time optimal control of the Euler–Lagrange (E–L) multi‐body mechanism under: uncertain its kinematics and dynamics, displacement blocking of the damaged joint caused by the actuator failure, undesirable forces/torques exerted on the end‐effector and unknown friction forces originating from joints directly driven by the actuators, as well as completely unstructured forces arising from the kinematic singularities appearing on the mechanism trajectory. Based on the suitably defined task space non‐singular terminal sliding manifold and the Lyapunov stability theory, we propose a class of new fault tolerant estimated generalized Jacobian controllers, which seem to be effective in reducing (minimizing) the joint velocity jumps as well as in counteracting the unstructured forces/torques. On account of the fact, that the multi‐body mechanism is a redundant one, a useful criterion function (energy consumption manipulability measure) has been utilized in our controller to temporarily optimally track a desired trajectory. The proposed controllers' performance is demonstrated by computer simulations conducted on a redundant manipulator in conditions of unexpected actuator failure and the corresponding joint lock. Additionally, numerical comparisons are also provided with other representative controllers, found in the literature.

Finite-Time Fuzzy Adaptive Output Feedback Resilient Control of Nonlinear Cyber-Physical Systems with Sensor Attacks and Actuator Faults

Finite-Time Fuzzy Adaptive Output Feedback Resilient Control of Nonlinear Cyber-Physical Systems with Sensor Attacks and Actuator Faults

Dynamic output feedback based fault tolerant control for continuous-time switched affine systems via reduced-order observer

In this study, the issue on dynamic output feedback fault-tolerant controller design is addressed for a class of continuous-time switched affine systems in the presence of actuator faults. The existence of affine terms gives rise to the lack of a common equilibrium point and further makes it more difficult to propose the desired output-feedback-based fault-tolerant control scheme. Firstly, the actuator fault estimation is achieved through a reduced-order observer design approach. Then, a kind of dynamic output feedback controller is constructed to perform the fault tolerance goal by utilizing fault estimation information. Moreover, the mode-dependent average dwell time switching constraint is borrowed to avoid the chattering owing to the high-frequency switching. The sufficient conditions with less conservative are derived to guarantee the practical exponential stability of closed-loop system with a prescribed L∞ gain. Finally, both the effectiveness and validity of the designed fault-tolerant control strategy are illustrated via a case study of a buck-boost DC-DC converter.

Predefined-time adaptive consensus control for nonlinear multi-agent systems with input quantization and actuator faults

Predefined-time adaptive consensus control for nonlinear multi-agent systems with input quantization and actuator faults

Adaptive prescribed performance tracking control for a class of nonlinear systems with actuator faults via a quantized event-triggered control scheme

Adaptive prescribed performance tracking control for a class of nonlinear systems with actuator faults via a quantized event-triggered control scheme

Optimal fuzzy event-triggered fault-tolerant control of fractional-order nonlinear stochastic systems

This paper considers the optimal fuzzy fault-tolerant control issue for fractional-order nonlinear stochastic systems (FONSS) using event-triggered mechanisms with fractional-order derivative α∈(0,1). First, in order to weaken the impacts of actuator and sensor faults, a fuzzy observer and augmented system are developed. Since stochastic disturbance can adversely affect stability, based on fractional Barbalat lemmas and Lyapunov theory, an adaptive fault-tolerant controller and the corresponding adaptive update law are designed to ensure the stability of FONSS. Then, the architecture of identifier-critic-actor NN, which is more concise than the traditional one, is described. This NN architecture recognizes unknown dynamics and completes control actions after evaluating the control performance, driving control toward optimization. Furthermore, the event-triggered mechanism is devised to save control resources and avoid Zeno behavior. Finally, simulation results demonstrate that under equivalent conditions, the proposed optimal event-triggered control reduces the number of information transmissions compared to traditional time-triggered control, saving communication resources and enhancing the overall control performance.