Output Error Injection Signal Research Articles

Actuator FDI Scheme for a Wind Turbine Benchmark Using Sliding Mode Observers

This paper proposes a fault detection and isolation (FDI) scheme for a wind turbines subject to actuator faults in both the pitch system and the drive train system. The proposed scheme addresses fault detection and isolation problems using a fault estimation approach. The proposed approach considers the use of a particular class of sliding mode observers (SMOs) designed to maintain the sliding motion even in the presence of actuator faults. The fault detection problem is solved by reconstructing the actuator faults through an appropriate analysis of the nonlinear output error injection signal, which is required to keep the SMO in a sliding motion. To ensure accurate fault reconstruction, only two conditions are required, namely that the faults are bounded and they meet the matching condition. A scheme based on a bank of SMOs is proposed to solve the fault detection and isolation problem in the pitch system. For the drive train system, a scheme using only one SMO is proposed. The performance of the proposed FDI scheme is validated by using a wind turbine benchmark model subjected to several actuator faults. Normalized root mean square error (NRMSE) analysis is performed to evaluate the accuracy of the actuator fault estimations.

Generalized Sliding Mode Observers for Simultaneous Fault Reconstruction in the Presence of Uncertainty and Disturbance

In this paper, a generalized sliding mode observer design method is proposed for the robust reconstruction of sensors and actuators faults in the presence of both unknown disturbances and uncertainties. For this purpose, the effect of uncertainty and disturbance on the system has been considered in generalized state-space form, and the LMI tool is combined with the concept of an equivalent output error injection method to reduce the effects of them on the reconstruction process. The upper bound of the disturbance and uncertainty are minimized in the design of the sliding motion so that the reconstruction of the faults will be minimized. The design method is applied for actuator faults in the generalized state-space form, and then with some suitable filtering, the method extends as sensors and actuators coincidentally faults. Since in the proposed approach, the state trajectories do not leave the sliding manifold even in simultaneous sensors and actuators faults, then the faults are reconstructed based upon information retrieved from the equivalent output error injection signal. Due to the importance of the robust fault reconstruction in the wind energy conversion system (WECS), the proposed approach is successfully applied to a 5 MW wind turbine system. The simulation results verify the robust performances of the proposed approach in the presence of unknown perturbations and uncertainties.

Fault Reconstruction for Lipschitz Nonlinear Systems Using Higher Terminal Sliding Mode Observer

This paper considers the design of an adaptive second order terminal observer for robust fault reconstruction of nonlinear Lipschitz systems with unknown upper bound of derivative fault. Firstly, a linear transforming matrix is introduced, which transforms the system into two subsystems, and thus to reduce the dimension of the system. One of the subsystem is affected by fault and disturbances, while the other is free, which simplifies the design of observer. Then, the design method of the observer gain matrix is transformed into a convex optimization problem under linear matrix inequalities (LMIs). A second order non-singular terminal sliding mode observer is designed for the transformed system to realize the accurate estimation of state and fault. Considering the unknown upper bound of derivative fault, an adaptive algorithm is designed in the equivalent output error injection signal to ensure the sliding mode motion reach the sliding surface within limited time. Finally, an example demonstrates the effectiveness of the proposed method in the paper.

Sensor redundancy based FDI using an LPV sliding mode observer

In this study, a linear parameter varying (LPV) sliding mode sensor fault detection and isolation (FDI) scheme is proposed wherein knowledge of the measurement redundancy is utilised to achieve FDI in multiple channels simultaneously. Such a situation is common in some state-of-the-art aircraft fault diagnosis systems where information is generally/mainly measured based on triplex redundancy. The scheme proposed in this study is based on an LPV sliding mode observer and exploits the so-called equivalent output error injection signal to create estimates of the measurement faults. In the case of sensor measurement redundancy, and where there exists a fault-free (but unknown) sensor amongst the set of measurements, the fault reconstruction performance of the observer can be improved by isolating and using the output error injection signal associated with the fault-free redundant sensor. Simulation results using the RECONFIGURE benchmark model demonstrate the effectiveness of the scheme.

On the development of a sliding mode observer-based fault diagnosis scheme for a wind turbine benchmark model

This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output error injection signal. A well-known validated wind turbine benchmark model, developed by Aalborg University and KK-electronic a/c, is utilized to evaluate the FDD scheme. Different sensors and actuator fault scenarios are simulated in the drive train, generator, and pitch & blade subsystems of the benchmark model, and attempts have been made to estimate these faults via the proposed modified SMO. The simulation results confirm the effectiveness of the proposed diagnosis scheme, and the faults are well detected, isolated, and reconstructed in the presence of the measurement noise.

Sensor Fault Detection, Isolation, and Estimation in Lithium-Ion Batteries

In battery management systems (BMSs), real-time diagnosis of sensor faults is critical for ensuring the safety and reliability of the battery. For example, a current sensor fault leads to erroneous estimates of state of charge and other parameters, which in turn affects the control actions in the BMS. A temperature sensor fault may lead to ineffective thermal management. In this brief, a model-based diagnostic scheme is presented that uses sliding mode observers designed based on the electrical and thermal dynamics of the battery. It is analytically shown how the extraction of the equivalent output error injection signals on the sliding manifolds enables the detection, the isolation, as well as the estimation of the temperature, voltage, and current sensor faults. This brief includes simulation and experimental studies to demonstrate and evaluate the effectiveness of the proposed scheme. Discussions are also included on the effects of uncertainty and on threshold design.

Development and application of sliding mode LPV fault reconstruction schemes for the ADDSAFE Benchmark

This paper describes the development and the evaluation of a robust sliding mode observer fault detection scheme applied to an aircraft benchmark problem as part of the ADDSAFE project. The ADDSAFE benchmark problem which is considered in this paper is the yaw rate sensor fault scenario. A robust sliding mode sensor fault reconstruction scheme based on an LPV model is presented, where the fault reconstruction signal is obtained from the so-called equivalent output error injection signal associated with the observer. The development process includes implementing the design using AIRBUS׳s the so-called SAO library which allows the automatic generation of flight certifiable code which can be implemented on the actual flight control computer. The proposed scheme has been subjected to various tests and evaluations on the Functional Engineering Simulator conducted by the industrial partners associated with the ADDSAFE project. These were designed to cover a wide range of the flight envelope, specific challenging manoeuvres and realistic fault types. The detection and isolation logic together with a statistical assessment of the FDD schemes are also presented. Simulation results from various levels of FDD developments (from tuning, testing and industrial evaluation) show consistently good results and fast detection times.

Second order sliding mode observers for the ADDSAFE actuator benchmark problem

This paper presents the evaluation process and results associated with two different fault detection and diagnosis (FDD) schemes applied to two different aircraft actuator fault benchmark problems. Although the schemes are different and bespoke for the problem being addressed, both are based on the concept of a second order sliding mode. Furthermore both designs are considered as ‘local’ in the sense that a localized actuator model is used together with local sensor measurements. The schemes do not involve the global aircraft equations of motion, and therefore have low order. The first FDD scheme is associated with the detection of oscillatory failure cases (OFC), while the second scheme is aimed at the detection of actuator jams/runaways. For the OFC benchmark problem, the idea is to estimate the OFC using a mathematical model of the actuator in which the rod speed is estimated using an adaptive second order exact differentiator. For the jam/runaway actuator benchmark problem, a more classical sliding mode observer based FDD scheme is considered in which the fault reconstruction is obtained from the equivalent output error injection signals associated with a second order sliding mode structure. The results presented in this paper summarize the design process from tuning, testing and finally industrial evaluation as part of the ADDSAFE project.

A sliding mode observer for monitoring and fault estimation in a network of dynamical systems

SUMMARY In this paper, a novel fault estimation strategy is proposed for a network of dynamical systems at a supervisory monitoring level. The network nodes include linear and Lipschitz nonlinear dynamics and time-varying coupling strength. The aim is to enhance the autonomy level of this class of systems by means of this inherently robust, nonlinear strategy based on sliding mode ideas. The faults are reconstructed from the equivalent output error injection signal which is used to maintain sliding. A key facet of the strategy is that the synthesis of the sliding mode observer for the network depends solely on the dynamics of an individual node of the network. The theoretical results developed in the paper are demonstrated with an example consisting of a network of pendulums. Copyright © 2013 John Wiley & Sons, Ltd.

Robust fault reconstruction for linear parameter varying systems using sliding mode observers

SUMMARYThis paper presents a robust fault detection and isolation scheme using a sliding mode observer based on a linear parameter varying system, with fault reconstruction capability. Both actuator and sensor fault reconstruction schemes are considered that possess robustness against a certain class of uncertainty and corrupted measurements. For actuator fault reconstruction, the input distribution matrix (associated with the actuators being monitored) is factorized into fixed and varying components. LMIs are used to design the key observer parameters in order to minimize the effect of uncertainty and measurement corruption on the fault reconstruction signal. The faults are reconstructed using the output error injection signal associated with the nonlinear term of the sliding mode observer. For sensor fault reconstruction, the idea is to reformulate the problem into an actuator fault reconstruction scenario so that the same design procedure can be applied. This is achieved by augmenting the original system with the filtered sensors being monitored. Simulations using a full nonlinear model of a large transport aircraft are presented and show good fault reconstruction performance. Copyright © 2013 John Wiley & Sons, Ltd.

Second Order Sliding Mode Observers for the ADDSAFE Benchmark Problem

This paper presents the theoretical development of second order sliding mode observer schemes for two different ADDSAFE aircraft fault detection benchmark problems: one for sensor faults and one for actuator faults. For the sensor fault problem, a robust sliding mode reconstruction scheme based on an LPV system is presented. The scheme involves transforming the sensor fault reconstruction problem into an actuator reconstruction problem, and then the fault reconstruction is obtained from the equivalent output error injection signals associated with a second order sliding mode structure. For the actuator jam/runaway problem, a similar idea is considered using a local actuator model. Simulation results from the high fidelity nonlinear ADDSAFE benchmark aircraft model show the effectiveness of the proposed schemes.

Fault reconstruction using a LPV sliding mode observer for a class of LPV systems

This paper proposes a new sliding mode observer for fault reconstruction, applicable for a class of linear parameter varying (LPV) systems. Observer schemes for actuator and sensor fault reconstruction are presented. For the actuator fault reconstruction scheme, a virtual system comprising the system matrix and a fixed input distribution matrix is used for the design of the observer. The fixed input distribution matrix is instrumental in simplifying the synthesis procedure to create the observer gains to ensure a stable closed-loop reduced order sliding motion. The ‘output error injection signals’ from the observer are used as the basis for reconstructing the fault signals. For the sensor fault observer design, augmenting the LPV system with a filtered version of the faulty measurements allows the sensor fault reconstruction problem to be posed as an actuator fault reconstruction scenario. Simulation tests based on a high-fidelity nonlinear model of a transport aircraft have been used to demonstrate the proposed actuator and sensor FDI schemes. The simulation results show their efficacy.

Fault and disturbance reconstruction in non-linear systems using a network of interconnected sliding mode observers

A new technique for fault diagnosis and estimation of unknown inputs in a class of non-linear systems is presented in this study. The novelty of the approach is based on utilisation of a network of two interconnected sliding mode observers, the first is used for fault diagnosis and the second is used for estimation of unknown inputs. The two observers exchange information about their respective reconstructed signals online and in real time. Conditions and proofs of conversion are presented. A salient feature of the proposed approach is that the state trajectories do not leave the sliding manifold even in presence of unknown disturbances and faults. This allows for faults and unknown inputs to be reconstructed based on information retrieved from the equivalent output error injection signal.

Sliding Mode Observers for Fault Detection in a Network of Linear Dynamical Systems

In this paper, a novel methodology is proposed for the detection of faults in the individual nodes of a network of dynamical systems at a supervisory level. The scheme is based on sliding mode observers and the faults are reconstructed by appropriate processing of the equivalent output error injection signal required to maintain sliding. The proposed fault detection scheme is inherently robust, nonlinear and can accommodate time varying coupling strengths. Stability conditions for the sliding mode observer are derived and depend solely on the dynamics of an individual node of the network.

FAULT DIAGNOSIS IN NONLINEAR SYSTEMS USING INTERCONNECTED SLIDING MODE OBSERVERS

This paper presents a new technique for fault diagnosis and estimation of unknown inputs in a class of nonlinear systems. The novelty of the approach is governed by the use of two interconnected sliding mode observers. The first of the two observers is used for fault diagnosis and the second is used for the reconstruction of unknown inputs. The two observers exchange their respective reconstructed signals online and in real time. Conditions for the convergence are derived. The design is such that the state trajectories do not leave the sliding manifold even in presence of unknown inputs and faults. This allows for faults and unknown inputs to be reconstructed based on information retrieved from the equivalent output error injection signals.

Sliding mode observers for vehicle mode detection

This paper explores the use of sliding mode observers to detect the onset of potentially dangerous vehicle modes such as oversteer, understeer or split-μ braking. Provided these modes can be detected quickly enough, existing stability controllers can be engaged to ensure safe performance of the vehicle. It is shown that the equivalent output error injection signals associated with the sliding mode observer have distinctive signatures depending on the particular mode encountered. Appropriate thresholds on these signals can be set so the scheme ignores variations which arise during normal driving, but can detect and isolate different undesirable vehicle modes within 0.3 seconds of their onset.

MODE DETECTION IN VEHICLES USING A SLIDING MODE ESTIMATOR

This paper explores the use of sliding mode observers to detect the onset of potentially dangerous vehicle modes such as oversteer, understeer or split-mu braking. Provided these modes can be detected quickly enough, existing stability controllers can be engaged to ensure safe performance of the vehicle. It is shown that the equivalent output error injection signals associated with the sliding mode observer have distinctive signatures depending on the particular mode which is encountered. Appropriate thresholds on these signals can be set so the scheme ignores variations which arise during the course of normal driving, but can detect and isolate different undesirable vehicle modes within 0.3 seconds of their onset.

A Sliding Mode Observer Based FDI Scheme for the Ship Benchmark

A method has recently been proposed which uses a particular sliding mode observer to reconstruct faults by analysing the equivalent output error injection signal required to maintain the observer in a sliding motion. This paper considers the application of the method to a recently proposed ship benchmark problem. The observer design is performed using a linearisation of a single engine single propeller system. Nonlinear simulation tests are carried out using a fault test sequence applied to a two engine two propeller system. Appropriate analysis of the observer output is shown to yield estimates of the faults with no false alarms or missed detections. The results obtained are compared with those already reported in the literature using alternative observer based approaches.