Time-varying Sensor Faults Research Articles

Composite adaptive exponential tracking control for large-scale nonlinear systems with sensor faults

The issue of composite adaptive exponential tracking control for a class of large-scale nonlinear systems under model uncertainties, external disturbances, along with multiplicative and additive time-varying sensor faults is considered in this paper. The command filtered backstepping approach is employed to address the “explosion of terms” issue inherent in standard backstepping method. A novel compensating system is incorporated to mitigate the effects of filtering errors and enhance the convergence of tracking errors. The composite estimation laws are designed by integrating the compensated tracking errors, prediction errors stemming from output estimators, along with the proportional and integral estimation errors of faulty terms. This on-line estimation framework enables achieving fast, robust and accurate estimation, even when employing low learning and modification gains. By incorporating modification terms with appropriate time-varying gains, it is demonstrated that the resulting system is globally exponentially stable. Finally, the effectiveness of the presented FTC approach is illustrated through two simulation examples.

Adaptive fuzzy sliding mode control for underactuated systems with time-varying sensor faults

ABSTRACT The tracking control problem of a class of underactuated systems that have time-varying additive and multiplicative sensor faults is studied in this paper. A composite sliding mode surface is established, and the fuzzy logic system is used to estimate the unknown term in the system. The impact of sensor faults can be counteracted by using the proposed method, which also guarantees the tracking errors converge to zero and the signals in the closed-loop system are bounded. Furthermore, the usefulness of the designed control strategy is certified via a numerical simulation.

Adaptive Fuzzy Decentralized Output-Feedback Control of Large-Scale Systems With Sensor Faults: A Multichannel Asynchronous Triggering Approach

This paper proposes an adaptive fuzzy decentralized output feedback control scheme for large-scale systems with multichannel asynchronous event-triggering. Uncertain system dynamics, unknown interconnections and time-varying sensor faults are handled simultaneously, even though only the corrupted measured local output is available for the design procedure. First, local state estimation filters are designed to estimate the unmeasured states. Then, considering that the resource-limited communication and computation may exist in all three types of channels including state estimation filter-to-controller channel, parameter estimator-to-controller channel and controller-to-actuator channel, an asynchronous event-triggering framework with time-varying triggering threshold is developed for multiple channels to release the communication and computation burden. Compared with the existing synchronous triggering mechanism, the proposed asynchronous one has several advantages: 1) the redundant signal transmission is reduced, 2) the triggering conditions for different channels are uncorrelated, which enables the designer to adjust the signal transmission frequency of each channel independently, and 3) the robustness could be improved in the face of noise as ideal synchronous triggering is not easy to be achieved in practice. In addition, both gain and bias faults, which are allowed to be unknown and time-varying, are covered in a unified sensor fault model. It is proved that, with the proposed control scheme, all the closed-loop signals are semi-globally uniformly ultimately bounded and the output tracking error converges into an adjustable residual set without Zeno behavior. Finally, simulation and comparison results illustrate the effectiveness and advantages of the proposed control scheme.

Attitude Fault-Tolerant Control of Aerial Robots with Sensor Faults and Disturbances

In this paper, sensor fault diagnosis and fault tolerant control strategy are investigated for quadcopters under sensor faults and disturbances. We propose the fault diagnosis estimation system and the fault-tolerant control (FTC) method. The fault diagnosis system provides time-varying sensor fault estimation under an unknown bound of disturbances. Moreover, the fault-tolerant control eliminates disturbance that is estimated through the associated disturbance observer. Overall, the proposed FTC guarantees the finite-time tracking convergence using nonsingular fast terminal sliding mode algorithm. Stability of the closed-loop system is validated through the Lyapunov theory. Finally, conventional nonsingular fast terminal sliding mode and adaptive neural network sliding mode control are compared with the proposed method through simulations under sensor faults and disturbances with different scenarios.

A Robust Unscented Kalman Filter for Intermittent and Featureless Aircraft Sensor Faults

Fault tolerance is crucial to reliable state estimations in aircrafts. When time-varying sensor faults are coupled with nonlinear system models, it is non-trivial to robustly recover system states. In this paper, based on an intermittent-measurement unscented Kalman filter (IMUKF), we propose a new state-estimation method by combining the IMUKF with maximum-likelihood estimation and Gaussian mixture reduction. For nonlinear systems under time-varying and featureless sensor faults, the proposed method performs robust estimation without past error history or explicit fault detection, achieving significantly enhanced accuracy under severe conditions. With a nonlinear twin-spool jet engine as the example in simulations, the effectiveness of the proposed method is verified.

Sensor fault diagnosis and fault tolerant control for the multiple manipulator synchronized control system

In this paper, a fault diagnosis (FD) and fault tolerant control (FTC) scheme is proposed for the leader–follower based multiple manipulator system with sensor fault under network communication topology. The learning observer is designed to obtain the fault information when the time-varying sensor fault occurs in follower manipulators. The synchronization error between the leader manipulator and the follower manipulator is defined based on the graph theory. The distributed multiple manipulator synchronization controller is designed for each follower manipulator which contains the value of fault estimation and RBF neural network based approximator. Correspondingly, the stability analysis of the error system is analyzed by the Lyapunov stability theorem. Finally, a simulation example is given to prove the effectiveness of the algorithm.

Adaptive sensor fault-tolerant control for a class of multi-input multi-output nonlinear systems: Adaptive first-order filter-based dynamic surface control approach

This paper is concerned with the adaptive fault-tolerant control (FTC) problem for a class of multivariable nonlinear systems with external disturbances, modeling errors and time-varying sensor faults. The bias, drift, loss of accuracy and loss of effectiveness faults can be effectively accommodated by this scheme. The dynamic surface control (DSC) technique and adaptive first-order filters are brought together to design an adaptive FTC scheme which can reduce significantly the computational burden and improve further the control performance. The adaptation laws are constructed using novel low-pass filter based modification terms which enable under high learning or modification gains to achieve robust, fast and high-accuracy estimation without incurring undesired high-frequency oscillations. It is proved that all signals in the closed-loop system are uniformly ultimately bounded and the tracking-errors can be made arbitrary close to zero. Simulation results are provided to verify the effectiveness and superiority of the proposed FTC method.

Fault-tolerant control for a class of quantised networked control of nonlinear systems with unknown time-varying sensor faults

ABSTRACTIn this paper, fault-tolerant control problems in quantised networked control of nonlinear systems (NCSs) with sensor uncertainties are considered. The measured output equation of the given NCS system has unknown external time-varying uncertainties that may be unbounded in addition to the effects of network-induced constraints; network-induced delays, network-induced data packet losses and network quantisation errors. A simultaneous observer-controller is constructed to stabilise the overall NCS. A flexible-joint robot link example is simulated to illustrate the significant improvement on system tracking performance.

Active fault tolerant control design approach for the flexible spacecraft with sensor faults

In this paper, the problem of active fault tolerant control (FTC) is studied for a class of flexible spacecraft attitude systems with Lipschitz nonlinearity and sensor fault. Firstly, a functional observer is designed for the attitude systems of flexible spacecraft in order to detect the time of unknown sensor fault occurred. Next, the sensor fault estimation is performed by filtering the output estimation error, as usually done in the residual generation framework. Then, a dynamic output feedback-based FTC approach is proposed to the flexible spacecraft in sensor faulty case, it not only attenuates flexible appendage disturbance with a given level γ, but also tolerates the effect of unknown sensor fault. Finally, the effectiveness of the proposed FTC method is demonstrated in the attitude systems of flexible spacecraft subject to a time-varying sensor fault.

Guaranteed Cost Fault-Tolerant Control for Networked Control Systems with Sensor Faults

For the large scale and complicated structure of networked control systems, time-varying sensor faults could inevitably occur when the system works in a poor environment. Guaranteed cost fault-tolerant controller for the new networked control systems with time-varying sensor faults is designed in this paper. Based on time delay of the network transmission environment, the networked control systems with sensor faults are modeled as a discrete-time system with uncertain parameters. And the model of networked control systems is related to the boundary values of the sensor faults. Moreover, using Lyapunov stability theory and linear matrix inequalities (LMI) approach, the guaranteed cost fault-tolerant controller is verified to render such networked control systems asymptotically stable. Finally, simulations are included to demonstrate the theoretical results.