Adaptive Diagnostic Observer Research Articles

Fault diagnosis and model predictive fault-tolerant control for stochastic distribution collaborative systems based on the T–S fuzzy model

ABSTRACTThis paper presents a fault-tolerant control scheme for a class of nonlinear stochastic distribution collaborative control systems, which are composed of two nonlinear subsystems connected in series to complete the target. The Takagi–Sugeno (T–S) fuzzy model is applied to approximate the nonlinear dynamics of a subsystem. The output of the whole system is the output probability density function (PDF) of the second subsystem. The fuzzy logic systems (FLS) is used to approximate the output PDF. To diagnose the fault that occurred in the first subsystem, an adaptive diagnostic observer and linear matrix inequality (LMI) technique are used to obtain the adaptive tuning law to estimate the fault. When a fault occurs, the fault itself cannot be compensated in the first subsystem and a model predictive fault-tolerant controller is designed in the second subsystem to compensate the fault, making the post-fault output PDF still track the desired PDF as close as possible. A simulated example is given, and the desired results have been obtained.

Fault Diagnosis and Minimum Rational Entropy Fault Tolerant Control of Stochastic Distribution Collaborative Systems.

In this paper, a fault-tolerant control scheme is presented for a class of stochastic distribution collaborative control systems, which are composed of three subsystems connected in series to complete the control target. The radial basis function neural network is used to approximate the output probability density function of the third subsystem, which is also the output of the entire system. When fault occurs in the first subsystem, an adaptive diagnostic observer is designed to estimate the value of fault. However, the first subsystem does not have the ability of self-recovery, minimum rational entropy controllers are designed in the latter subsystems to compensate the influence of the fault and minimize the entropy of the system output. A numerical simulation is given to verify the effectiveness of the proposed scheme.

Sliding Mode Fault Tolerant Control with Adaptive Diagnosis for Aircraft Engines

Abstract In this paper, a novel sliding mode fault tolerant control method is presented for aircraft engine systems with uncertainties and disturbances on the basis of adaptive diagnostic observer. By taking both sensors faults and actuators faults into account, the general model of aircraft engine control systems which is subjected to uncertainties and disturbances, is considered. Then, the corresponding augmented dynamic model is established in order to facilitate the fault diagnosis and fault tolerant controller design. Next, a suitable detection observer is designed to detect the faults effectively. Through creating an adaptive diagnostic observer and based on sliding mode strategy, the sliding mode fault tolerant controller is constructed. Robust stabilization is discussed and the closed-loop system can be stabilized robustly. It is also proven that the adaptive diagnostic observer output errors and the estimations of faults converge to a set exponentially, and the converge rate greater than some value which can be adjusted by choosing designable parameters properly. The simulation on a twin-shaft aircraft engine verifies the applicability of the proposed fault tolerant control method.

离心式压缩机执行器故障诊断方法设计

针对一类满足利普希茨条件的离心式压缩机系统，提出了一种新型压缩机执行器故障诊断方法。设计自适应诊断观测器，实时动态采集压缩机执行器故障前后的信息，对压缩机执行器故障进行精确跟踪，达到故障诊断的目的。利用Lyapounov函数分析了设计系统的稳定性。仿真结果表明，自适应诊断观测器能够实时精准的跟踪离心式压缩机执行器故障，证明了该方法的有效性。 A novel compressor actuator fault diagnosis method is proposed for the centrifugal compressor system satisfying Lipschitz condition. By collecting the real-time status of the compressor actuator faulty and normal conditions, adaptive diagnostic observer is design, and then the compressor actuator fault is tracked accurately, which realizes the fault detection. The stability of design system is analyzed by using Lyapounov function. The results show that the adaptive fault diagnosis observer can accurately track the centrifugal compressor actuator fault, which proves the effectiveness of the proposed method.

Output feedback fault-tolerant control for a class of discrete-time fuzzy bilinear systems

This paper studies the fault-tolerant control problem for a class of discrete-time fuzzy bilinear systems with unmeasurable states. A fuzzy detective observer is designed to detect the faults. Based on the fuzzy detective observer, a fuzzy controller is designed by solving a set of linear matrix inequalities (LMIs) to ensure that the closed-loop system without faults is asymptotically stable. For the discrete-time fuzzy bilinear system with faults, a fuzzy adaptive diagnostic observer is designed to estimate the faults by solving a set of LMIs. Then, a fuzzy faulttolerant controller is designed based on the fuzzy diagnostic observer to ensure that the closed-loop system with faults is asymptotically stable. At last, simulation results are presented to verify the effectiveness of the proposed output feedback fault-tolerant control method.

Actuator Fault Detection and Accommodation in Distributed Parameter Systems

This paper presents a general framework for model-based fault detection and accommodation for a class of distributed parameter systems with control actuator faults. A set of dedicated observers, each with its own time-varying threshold is constructed to detect the occurrence of fault in the corresponding actuator and reduce fault detection time. Additionally, an adaptive diagnostic observer is then designed and analyzed to estimate each individual actuator fault. Based on the online approximation of fault parameter, automated control reconfiguration architecture has been developed to accommodate actuator fault and to preserve closed-loop stability. An example has been discussed using the proposed scheme to demonstrate effectiveness of the method.

Adaptive fault detection and estimation scheme for a class of uncertain nonlinear systems

This paper presents a novel fault detection and estimation (FDE) scheme for a class of Lipschitz nonlinear systems subjected to modeling and measurement uncertainties. Many works in this field assume that the states of the system are measurable and the fault function acts as an additive term. The proposed FDE strategy deals with the uncertain nonlinear systems subjected to multiplicative faults, and it does not rely on availability of the full state. Multiplicative fault corresponds to the parameter or structure changes in the system or in the process model. Also, actuator gain fault is another important fault type which can be modeled as a multiplicative fault. The effects of this kind of fault are combined with the inputs and outputs of the system in a multiplicative form which, in turn, make the detection and estimation of the fault complex. The proposed scheme is based on an adaptive diagnostic observer that not only can estimate the states of the system and generate the residual signal simultaneously, but also is able to estimate the characteristic and magnitude of an unknown fault. In the fault detection step, the threshold is derived analytically to ensure the robustness of the proposed detection scheme against uncertainties. Also in the fault estimation step, a robust adaptive law based on the switching $$\sigma $$ -modification is developed to estimate the detected fault accurately. Design steps of the proposed estimation scheme are introduced in the form of LMI problem. This formulation provides an effective way to calculate the design parameters. The proposed FDE scheme guarantees that all signals are uniformly ultimately bounded. Simulation results of a single-link, flexible joint, robotic arm show the effectiveness and robustness of the proposed FDE strategy.

Dynamic online nonlinear robust detection and accommodation of incipient component faults for nonlinear dissipative distributed processes

SUMMARYThis paper proposes a new nonlinear detection observer for the detection of component faults and their subsequent accommodation for a class of nonlinear distributed processes. Specifically, the proposed results constitute a significant extension to previous precursory work that utilized a linear observer for both detection and diagnosis of component faults for the same class of nonlinear distributed processes. An added feature of the proposed nonlinear observer under consideration is not simply the inclusion of nonlinear dynamics terms in the detection and diagnostic observers but the inclusion of such additional information in the expression for the dynamic residual threshold. The resulting improved version of a dynamic threshold contributes to the robustness of the detection scheme and minimizes the fault detection time. Two different dynamic threshold approaches are employed within the same nonlinear detection observer leading to improved detection time. A combination of the two thresholds is also considered to arrive at a detection observer that reaps the beneficial attributes of each of the thresholds, thus resulting in significant reduction of the fault detection time. Finally, an adaptive diagnostic observer is proposed that is subsequently utilized in an automated control reconfiguration scheme that accommodates the component faults. Copyright © 2011 John Wiley & Sons, Ltd.

Robust detection and accommodation of incipient component and actuator faults in nonlinear distributed processes

AbstractA class of nonlinear distributed processes with component and actuator faults is presented. An adaptive detection observer with a time varying threshold is proposed that provides additional robustness with respect to false declarations of faults and minimizes the fault detection time. Additionally, an adaptive diagnostic observer is proposed that is subsequently utilized in an automated control reconfiguration scheme that accommodates the component and actuator faults. An integrated optimal actuator location and fault accommodation scheme is provided in which the actuator locations are chosen in order to provide additional robustness with respect to actuator and component faults. Simulation studies of the Kuramoto‐Sivashinsky nonlinear partial differential equation are included to demonstrate the proposed fault detection and accommodation scheme. © 2008 American Institute of Chemical Engineers AIChE J, 2008