Fault tolerant shape control for particulate process systems under simultaneous actuator and sensor faults

The paper tackles the problem of designing a simultaneous actuator and sensor fault estimator with an adaptive threshold. In general, the work is focused on developing an adaptive estimation strategy with a quadratic boundedness approach. This method guarantees the convergence of the estimator under bounded disturbances. The main novelty lies in the simultaneous estimation of actuator and sensor faults, while these problems are usually treated separately. Another appealing advantage of the proposed approach is the fact that it provides a confidence interval of the state and faults, which supports diagnostic decisions. The final part of the paper portrays an illustrative example concerning laboratory DC motor, which confirms the effectiveness of the proposed strategy.

This paper aims at providing two competitive solutions to the problem of estimating state as well as sensor and actuator faults. The development starts with a common system description, which is transformed into a nonlinear descriptor system-like form. The appealing property of such an approach is that the sensor fault is eliminated from the output equation by suitably extending the state vector. Subsequently, a novel fault estimation scheme is proposed and its error dynamics are carefully described. Having such a unified framework, two competitive design procedures are proposed. One is based on the celebrated H_∞ while the other employs the quadratic boundedness strategy. With the estimators, the paper provides a unified framework for assessing the uncertainty of the resulting estimates in the form of uncertainty intervals. Thus, both solutions can be compared from the theoretical perspective. The final part of the paper contains a numerical simulation example concerning a twin-rotor system that clearly shows the comparison and performance of the above approaches. Subsequently, an experimental study concerning a multi-tank system using real data is reported.

This paper develops a novel fault reconstruction (FR) method and an FR-based fault-tolerant control (FTC) scheme for systems suffering from both sensor and actuator faults based on the combination of a Luenberger-like reduced-order observer and an interval observer. Firstly, by introducing an output transformation, an auxiliary output that is able to decouple the sensor fault is obtained. Secondly, for addressing the external disturbance and actuator fault, a multiple unknown input (MUI) is formed, and a reduced-order observer that is able to decouple the MUI is constructed. Consequently, asymptotic convergence estimations of the state and the sensor fault can be accomplished. Thirdly, in order to obtain the asymptotic convergence actual FR (AFR), an interval observer is designed. After this, an algebraic connection of the MUI and the state error estimation is given, and, based on the algebraic relationship, an algebraic MUI reconstruction (MUIR) method is proposed. Finally, an FTC scheme is developed by using the state estimation and MUIR. Under the FTC, the closed-loop system is asymptotically stable even if it suffers from sensor and actuator faults simultaneously. Theoretical analysis demonstrates that the observer-based FTC mechanism satisfies the separation principle. At last, two simulation examples are given to verify the effectiveness of the proposed methods.

The paper deals with the design of an active fault-tolerant control scheme, which is based on the actuator and sensor fault estimator. Thus, the paper starts with the development of such a fault estimation scheme capable of estimating these faults simultaneously. It is assumed that the estimator should have a desired \(H_\infty \) performance. Subsequently, a new fault-tolerant control law is proposed, which is based on a parallel digital twin of the system. Thus, the goal is to control the system in such a way as to follow the states of the references digital twin irrespective of the faults. Finally, the effectiveness of the proposed approach is verified with the laboratory three-tank system. In particular, the performance of the system is tested against a set of simultaneous actuator and sensor faults, respectively.

This paper studies the problem of fault estimation (FE) and the active fault tolerant control (FTC) for a class of Takagi-Sugeno (T-S) fuzzy systems with time-varying delay and simultaneous actuator and sensor faults. Based on the fault estimation algorithm, an adaptive observer-based controller is designed to guarantee the dynamic error system to be asymptotically stable and satisfy the H ∞ performance index. Then, based on the information of online fault-estimation information, a dynamic output feedback fault tolerant controller is designed to compensate the fault effects on the closed-loop fuzzy system. Finally, simulation results are given to verify the effectiveness of the proposed method.

This paper focuses on insufficient perception in blind scenes and the failures of the actuator and sensor of vehicle suspension. The safe speed is designed and the fault-tolerant strategy based on the observer is designed when the actuator and sensor fail simultaneously. A speed planning strategy to ensure that vehicles operate at a safe speed is proposed. The Markov suspension fault jump model considering the suspension sensor and actuator faults is established. Based on the fault estimation obtained by the fault observer, a fault tolerance control strategy of sensor signal reconstruction and actuator fault compensation is adopted. The measurement index for evaluating fault tolerance effectiveness has been established, and an exploration of fault tolerance control is conducted across various fault levels, to identify the preferred fault tolerance strategies corresponding to different levels of fault tolerance. The simulation results show that the designed speed control strategy can improve vehicle safety by decelerating in advance, the fault observer is capable of accurately estimating the true values of actuator and sensor faults. The simulation and vehicle test results demonstrate that similar suspension performance has been obtained by fault-tolerant control strategy and preferred fault tolerance under different fault tolerance levels compared with normal fault tolerance.

This paper investigates the problems of simultaneous actuator and sensor faults estimation, as well as the fault‐tolerant control scheme for a class of linear continuous‐time systems subject to external disturbances. First, the original system is transformed into a singular form by extending the actuator fault and sensor fault to be parts of the new state. Then, a new estimation technique named non‐fragile proportional‐derivative observer is designed for the singular system to achieve simultaneous estimations of states and faults. With the obtained estimations information, an integrated design of the non‐fragile output feedback fault‐tolerant controller is explored to compensate for the effect of faults by stabilizing the closed‐loop system. Finally, a simulation study on a two‐stage chemical reactor with recycle streams is provided to verify the effectiveness of the proposed approach.

Disturbance observer based fault estimation and dynamic output feedback fault tolerant control for fuzzy systems with local nonlinear models

Fault Tolerant Control of the Wind Turbine Benchmark using Virtual Sensors/Actuators

ABSTRACTIn this paper, a fault estimation and fault-tolerant control problem for a class of T-S fuzzy stochastic time-delay systems with actuator and sensor faults is investigated. A novel sliding mode observer is proposed, which can simultaneously estimate the system states, actuator and sensor faults with good accuracy. Based on the state and actuator fault estimation, a new sliding mode control scheme is developed, which can effectively eliminate the influence of actuator fault. Sufficient conditions for the existence of the proposed observer and fault-tolerant sliding mode controller are provided in terms of linear matrix inequality, and moreover, the reachability of the sliding mode surface can be guaranteed under the proposed control scheme. The propose sliding mode observer and fault-tolerant sliding mode controller can overcome the restrictive assumption that the input matrix of all local modes is the same. Finally, a numerical example is provided to verify the effectiveness of the proposed sliding mode observer and fault-tolerant sliding mode control technique.

This paper develops a novel observer-based fault-tolerant control (FTC) for wind turbine blade pitch system subjected to simultaneous actuator and sensor faults. The main contribution of this paper is the proposal of new architecture based on a combination of sliding mode control (SMC) and a proportional–proportional–integral-observer (PPIO) to provide tight reference blade pitch angle tracking regardless of the effects of actuator and sensor faults. Within this architecture, an integral sliding surface-based SMC (ISMC) has been developed to stabilize tracking error dynamics during sliding phase while the system is subjected to actuator faults. The robust PPIO-based sensor fault estimation is utilized to compensate sensor fault from the input of ISMC and thereby guarantee closed-loop system robustness against actuator and sensor faults. Stability analysis has clearly demonstrated using linear matrix inequality and Lyapunov approach. The proposed method is applied to 4.8 MW wind turbine FTC benchmark model.

Introduction. Fault diagnosis, and fault tolerant control issues are becoming very important to ensure a good supervision of systems and guarantee the safety of human operators and equipments even if system complexity increases. Problem. In fact, the presence of faults in actuators, sensors and processes can lead to system performance degradation, system breakdown, economic loss, and even disastrous situations. Furthermore, Actuator saturation or control input saturation is probably the most usual nonlinearity encountered in control engineering because of the physical impossibility of applying unlimited control signals and/or safety constraints. Purpose. This article is dedicated to the problem of fault tolerant control for constrained nonlinear systems described by a Takagi-Sugeno model. One of the interests of this type of models is the possibility of extend some tools and methods from linear system case to the nonlinear one. The novelty of the work consists in developing a fault tolerant control algorithm for a nonlinear Permanent Magnet Synchronous Machine model using an observer based state-feedback control technique in order to enhance fault and state estimation despite actuator saturation and system disturbances. Methods. Indeed a sensor fault detection observer based residual generator is synthesized with a guaranteed L2 performance to attenuate the external disturbances effect from one side and to maximize the residual sensitivity to faults from the other side. Based on Lyapunov function, design conditions are formulated in terms of Linear Matrix Inequalities to ensure stability of the global system. Practical value. A detailed study concerning nonlinear permanent magnet synchronous machine model, which is consolidated by simulation results, is conducted to show the used algorithm’s effectiveness guarantying fault estimation and reconfiguration of the control law to maintain stable performance even in the presence of actuator faults, external perturbation and the phenomenon of actuator saturation.

A vehicle health monitoring system based on analytical redundancy, is developed for automated passenger vehicles. A residual generator and a residual processor are designed together to detect and identify actuator and sensor faults of the Buick LeSabre rapidly. The residual generator includes fault detection filters and parity equations. It uses the control commands and sensor measurements to generate the residuals, which have a unique static pattern in response to each fault. Then, the residual processor interrogates the residuals by matching them to one of several known patterns. It computes the probability of each hypothesis conditioned on the history of residuals. The fault detection latency is reduced by integrating the design of the residual generator and the residual processor. The vehicle health monitoring system is evaluated in real-time on a Buick LeSabre. The vehicle sensor and actuator faults are simulated artificially by the computer or created manually by the driver. In one experiment, a real intermittent sensor fault occurred and was immediately detected and identified. The real-time evaluation demonstrates that the vehicle health monitoring system can detect and identify actuator and sensor faults under various disturbances and uncertainties with almost minimal detection latency.

Detection, isolation and identification of multiple actuator and sensor faults in nonlinear dynamic systems: Application to a waste water treatment process

For dynamic systems with actuator faults, sensor faults, input disturbances, and measurement noises, a novel high-gain estimation technique is presented in this paper to estimate system states, actuator faults, and sensor faults simultaneously. The key idea is to represent faults as auxiliary system states so that a descriptor system representation can be formulated. By using the estimated state and fault signals, a fault-tolerant controller design approach is developed, where the closed-loop dynamic system can still be guaranteed to operate normally when actuator and sensor faults occur. It has been shown that in the proposed design framework, the actuator fault, sensor fault, input disturbance, and measurement noise can appear simultaneously and can be allowed to be in different bounded forms. Finally, the proposed algorithm is applied to the simulation study of a three-shaft gas turbine system and desired results have been obtained.