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Fault detection, isolation and reconfiguration of the flight control system is an important problem to obtain healthy flight. This paper aims to propose an integrated approach for aircraft fault-tolerant control.

The integrated structure includes a Kalman filter to obtain without noise, a full order observer for sensor fault detection, a GOS (generalized observer scheme) for sensor fault isolation and a fuzzy controller to reconfigure of the healthy sensor. This combination is simulated using the state space model of a lateral flight control system in case of disturbance and under sensor fault scenario.

Using a dedicated observer scheme, the detection and time of sensor fault are correct, but the sensor fault isolation is evaluated incorrectly while the faulty sensor is isolated correctly using GOS. The simulation results show that the suggested approach works affectively for sensor faults with disturbance.

This paper proposes an integrated approach for aircraft fault-tolerant control. Under this framework, three units are designed, one is Kalman filter for filtering and the other is GOS for sensor fault isolation and another is fuzzy logic for reconfiguration. An integrated approach is sensitive to faults that have disturbances. The simulation results show the proposed integrated approach can be used for any linear system.

The purpose of this paper is to propose a decentralized observer for large‐scale singular systems.

In this paper, the authors investigate the problem of observers' design for large‐scale singular systems. The proposed decentralized observer is based on a new parameterization of the generalized Sylvester equation solution. The considered system is partitioned into small‐sizes interconnected subsystems with unknown interconnections.

A decentralized observer based on new parameterization of generalized Sylvester equation. The performance of the proposed approach is illustrated by a numerical example.

The proposed approach unites the full‐order, the reduced‐order and the minimal order observer design for large‐scale system. The conditions of the existence of this observer are given in the linear matrix inequalities (LMI) form.

This paper aims to obtain an accurate and robust estimation method of the rotor flux and speed for the sensorless induction motor (IM) drive.

The reduced order observer has been used as an online tuned rotor flux model in the model reference adaptive system (MRAS) concept applied for the IM speed estimation. The output of this observer was used also as a feedback signal required in the direct field‐oriented control (DFOC) structure of the IM.

It is shown that a new rotor flux and speed estimator are more robust to motor parameter changes in comparison with the classical MRAS estimator and can work stably in the DFOC structure, in the wide speed range, even for relatively high (50 per cent) identification errors of equivalent circuit parameters of the IM.

The investigation looked mainly at the estimation accuracy performance and whole system stability while economic issues will still need to be addressed.

The proposed new improved MRAS speed estimator can be easily realised using modern digital signal processors. The implementation was tested in an experimental set‐up with floating point DSP used as the system controller. The fixed‐point realisation needs to be developed to obtain the practical application in the industrial drive systems.

The application of the reduced order flux observer as a tuned flux model in the MRAS type speed estimator instead of the simple, but very sensitive to motor parameter uncertainties, current flux model, enables much better accuracy and stability of the rotor speed estimation in the complex DFOC structure than in the case of classical MRAS estimator.

The purpose of this paper is to present a fixed‐point implementation of a complete direct torque control (DTC) algorithm connected with a rotor speed estimation algorithm for the induction motor drive, using field‐programmable gate array (FPGA).

The parallel processing approach is described, which requires a decomposition of the control and estimation algorithms for the converter‐fed induction motor to several tasks, realised in parallel. The advanced data processing techniques are described, like PIPELINE technique for data streams design, coordinate rotation digital computer algorithm for transformation of stator flux vector components from Cartesian to polar coordinates. Moreover, the method for the qualitative analysis of the full‐order state observer's sensitivity to the variations of the induction motor equivalent circuit parameters is presented.

It is shown that the developed FPGA‐based DTC structure enables designing an efficient application for the induction motor control. Owing to the high‐processing frequency, the digital FPGA‐based DTC application is similar in its features to the analogue realisation based on the comparators. Yet all the advantages of the digital structure, i.e. high flexibility, parameterization capability, etc. remain unchanged. Furthermore, FPGA is hardware realisation of a digital data processing algorithm; hence the reliability of the control system is improved.

The investigations are performed in the developing prototype setup, based on PXI‐1042 Industrial PC equipped with Xilinx Virtex‐II FPGA matrix, programmed with LabVIEW.

The experimental tests of the FPGA‐based implementation of the whole control structure of the sensorless DTC drive system are demonstrated. It is also shown, that the full‐order state observer with the speed adaptation loop is significantly sensitive to motor parameter variations in the low‐speed region, which must be taken into account while designing the adaptation algorithm for speed estimation in real application.

The paper's value lies in the overall, FPGA‐based design of the speed sensorless DTC structure for the induction motor including motor speed, torque and stator flux control loops, stator flux and rotor speed estimation.

The purpose of this paper is to generate residuals which can be used to detect fault and isolate on a vertical takeoff and landing (VTOL) aircraft dynamic model.

In the proposed approach, a generalized observer scheme method based on an unknown input observer is used for residual generation and applied to detect and isolate a faulty sensor. A bank of robust unknown input observers estimates the state variables of the system and gathers necessary information for fault detection and isolation purposes.

A sinus signal is considered as a non‐linear disturbance in simulations. A failure simulation was prepared in different times. In this situation an unknown input observer should be designed which could predict the states of the system against the disturbances or unknown inputs. In the real world, there exist unknown inputs such as system non‐linearities, noise and disturbances. The paper shows that the system based on UIO is robust for unknown inputs mentioned above.

It is simulated on a VTOL dynamic model using MATLAB/Simulink. Any single sensor fault could be detected and isolated correctly. This kind of observer is also robust and flexible.

A full-order multi-objective anti-disturbance robust filter for SINS/GPS navigation systems with multiple disturbances is designed. Generally, the unmodeled dynamics, the external environmental disturbance and the inertial apparatus random drift may exist simultaneously in an integrated navigation system, which can be classified into three type of disturbances, that is, the Gaussian noise, the norm bounded noise and the time correlated noise. In most classical studies, the disturbances in integrated navigation systems are classified as Gaussian noises or norm bounded noises, where the Kalman filtering or robust filtering can be employed, respectively. While it is not true actually, such assumptions may lead to conservative results. The paper aims to discuss these issues.

The Gaussian noises, the norm bounded noises and the time correlated noises in the integrated navigation system are considered simultaneously in this contribution. As a result, the time correlated noises are augmented as a part of system state of the integrated navigation system error model, the relative integrated navigation problem can be transformed into a full-order multi-objective robust filter design problem for systems with Gaussian noises and norm bounded disturbances. Certainly, the errors of the time correlated noises are estimated and compensated for high precision navigation purpose. Sufficient conditions for the existence of the proposed filter are presented in terms of linear matrix inequalities (LMIs) such that the system stability is guaranteed and the disturbance attenuation performance is achieved.

Simulations for SINS/GPS integrated navigation system given show that the proposed full-order multi-objective anti-disturbance filter, has stronger robustness and better precision when multiple disturbances exist, that is, the present algorithm not only can suppression the effect of white noises and norm bounded disturbance but also can estimate and compensate the modeled disturbance.

The proposed algorithm has stronger anti-disturbance ability for integrated navigation with multiple disturbances. In fact, there exist multiple disturbances in integrated navigation system, so the proposed scheme has important significance in applications.

Condition monitoring and health management of an aircraft engine is of importance due to engine’s critical position in aircraft. Missions require uninterrupted and safer conditions during the flight or taxi operations. Hence, the deviations, abnormal situations or failures have to be under control. This paper aims to propose a cascade connected approach for an aircraft engine fault tolerant control.

The cascade connected structure includes a full-order unknown input observer for fault detection and eliminating the unknown disturbance effect on system, a generalized observer scheme for fault isolation and a Boolean logic mechanism for decision-making in reconfiguration process, respectively. This combination is simulated on a linear turbojet engine model in case of unknown input disturbance and under various sensor failure scenarios.

The simulation results show that the suggested fault detection isolation reconfiguration (FDIR) approach works effectively for multiple sensor failures with various amplitudes.

Different from other studies, the proposed model is sensitive to unknown input disturbance and failures that have unknown amplitudes. One another notable feature of suggested FDIR approach is adaptability of structure against multiple sensor failures. Here, it is assumed that only a single fault is to be detected and isolated at a time. The simulation results show that the proposed structure can be suggested for linear models especially for physical redundancy-based real-time applications easily, quickly and effectively.

The purpose of this study is to present a new integrated structure for a fault tolerant aircraft control system because fault diagnosis of flight control systems is extremely important in obtaining healthy flight. An approach to detect and isolate aircraft sensor faults is proposed, and a new integrated structure for a fault tolerant aircraft control system is presented.

As disturbance and sensor faults are mixed together in a flight control system, it is difficult to isolate any fault from the disturbance. This paper proposes a robust unknown input observer for state estimation and fault detection as well as isolation using fuzzy logic.

The dedicated observer scheme (DOS) and generalized observer scheme (GOS) are used for fault detection and isolation in an observer-based approach. Using the DOS, it has been shown through simulation that sensor fault detection and isolation can be made, but here the threshold value must be well chosen; if not, the faulty sensor cannot be correctly isolated. On the other hand, the GOS is more usable and flexible than the DOS and allows isolation of faults more correctly and for a fuzzy logic-based controller to be used to realize fault isolation completely.

The fuzzy logic approach applied to the flight control system adds an important key for sensor fault isolation because it reduces the effect of false alarms and allows the identification of different kinds of sensor faults. The proposed approach can be used for similar systems.

In order to improve the practicability of the design in state estimation, the paper aims to present a novel disturbance decoupled reduced‐order observer (DDRO) design scheme.

The paper first uses equivalence transformation to eliminate unknown input appearing in measurement. Then based on Luenberger observer and using two non‐singular coordinate transformation, the design observer can get no bias error in the state estimation.

By using this approach we find that the conditions of DDRO depend on the system itself that is weaker than other observers. It is a qualified and simple and straightforward approach to be applied in wide domains.

We should note that the number of independent rows of the matrix C must not be less than the number of the independent columns of the matrix E to satisfy condition rank(CE)=rank(E)=q. In other words, the maximum number of disturbances which can be decoupled cannot be larger than the number of independent measurements.

It is a very useful approach to solve the problem that the measurement is contaminated by disturbances.

The paper proposed an equivalence transformation. It is used to eliminate unknown input appearing in measurement. At the same time the algebraic transformation guaranteed that it would lose no information of the unknown inputs. And compared with other known results, the design condition of the reduced‐order observer which proposed in this paper depends on system itself, especially, which is weaker than others.

The purpose of this paper is to investigate the influence of back-EMF and current harmonics on position and speed estimation accuracy for single and dual three-phase (DTP) permanent magnet synchronous machines (PMSMs) with two fundamental-model-based sensorless control strategies which are widely utilized for AC machines, i.e. flux-linkage observer (FO) and simplified extended Kalman filter (EKF).

The effect of distorted back-EMF is studied for sensorless vector control of single three-phase PMSM. For the influence of current harmonics, unlike the existing literature where the current harmonics are deliberately injected, in this paper, sensorless switching-table-based direct torque control (ST-DTC) strategies for DTP-PMSM which inherently suffer from non-sinusoidal stator currents in addition to the distorted back-EMF, are investigated experimentally.

By employing the FO and simplified EKF-based sensorless vector control of single three-phase PMSM, it can be concluded that the rotor position estimation accuracy is less affected by the back-EMF harmonics when the simplified EKF method is utilized since it is less sensitive to such noises. When the influence of non-sinusoidal stator currents together with back-EMF harmonics is investigated for the conventional and modified ST-DTC of DTP-PMSM, it is indicated that the simplified EKF exhibits better position and speed estimation accuracy in both the conventional and modified ST-DTC strategies. In addition, its steady-state performance shows a slight superiority over that based on FO, in terms of flux and torque ripples, and THD of phase currents. For the dynamic performance, the estimated speed of simplified EKF shows less phase lag and fluctuations compared to that of FO.

This paper introduces the influence of back-EMF and current harmonics on sensorless control performance for single and DTP PMSMs. Detailed experimental results show that the simplified EKF exhibits better rotor position and speed estimation accuracy compared to that of FO due to its higher noise-rejection ability.