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The purpose of this paper is to accomplish robust actuator fault isolation and identification for microsatellite attitude control systems (ACSs) subject to a series of space disturbance torques and gyro drifts.

For the satellite attitude dynamics with Lipschitz constraint, a multi-objective nonlinear unknown input observer (NUIO) is explored to accomplish robust actuator fault isolation based on a synthesis of H_inf techniques and regional pole assignment technique. Subsequently, a novel disturbance-decoupling learning observer (D²LO) is proposed to identify the isolated actuator fault accurately. Additionally, the design of the NUIO and the D²LO are reformulated into convex optimization problems involving linear matrix inequalities (LMIs), which can be readily solved using standard LMI tools.

The simulation studies on a microsatellite example are performed to prove the effectiveness and applicability of the proposed robust actuator fault isolation and identification methodologies.

This research includes implications for the enhancement of reliability and safety of on-orbit microsatellites.

This study proposes novel NUIO-based robust fault isolation and D²LO-based robust fault identification methodologies for spacecraft ACSs subject to a series of space disturbance torques and gyro drifts.

The purpose of this paper is to create a new method of prognosis based on remaining useful life (RUL) prediction for degradation assessment.

In the present paper the authors describe a new method of prognosis to improve the accuracy of forecasting the system state. This framework of forecasting integrates the model-based information and the hybrid approach, which employs the structured residuals in the first part and the particle filter in the second part.

The performance of the suggested fusion framework is employed to predict the RUL of battery pack in hybrid electric vehicle. The results show that the proposed method is plausible due to the good prediction of RUL, and can be effectively applied to many systems for prognosis.

In this study the authors illustrate how the suggested method can provide an accurate prediction of the RUL over conventional data-driven methods without physical model and classical particle filter with a single damage model.

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.

This paper proposes a novel method of fault detection, which is based on H_/H∞ Runge–Kutta observer and an adaptive threshold for a class of closed-loop non-linear systems. The purpose of this paper is to improve the rapidity and accuracy of fault detection.

First, the authors design the H_/H∞ Runge–Kutta fault detection observer, which is used as a residual generator to decouple the residual from the input. The H_ performance index metric in the specified frequency domain is used to describe how sensitive the residual to the fault. The H∞ norm is used to describe the residual robustness to the external disturbance of the systems. The residual generator is designed to achieve the best tradeoff between robustness against unknown disturbances but sensitivity to faults, thus realizing the accurate detection of the fault by suppressing the influence of noise and disturbance on the residual. Next, the design of the H_/H∞ fault detection observer is transformed into a convex optimization problem and solved by linear matrix inequality. Then, a new adaptive threshold is designed to improve the accuracy of fault detection.

The effectiveness and correctness of the method are tested in simulation experiments.

This paper presents a novel approach to improve the accuracy and rapidity of fault detection for closed-loop non-linear system with disturbances and noise.

The purpose of this paper is to investigate the pose control of rigid spacecraft subject to dead-zone input, unknown external disturbance and parametric uncertainty in space maneuvering mission.

First, a 6-Degree of Freedom (DOF) dynamic model of rigid spacecraft with dead-zone input, unknown external disturbances and parametric uncertainty is derived. Second, a super-twisting-like fixed-time disturbance observer (FTDO) with strong robustness is developed to estimate the lumped disturbances in fixed time. Based on the proposed observer, a non-singular fixed-time terminal sliding-mode (NFTSM) controller with superior performance is proposed.

Different from the existing sliding-mode controllers, the proposed control scheme can directly avoid the singularity in the controller design and speed up the convergence rate with improved control accuracy. Moreover, no prior knowledge of lumped disturbances’ upper bound and its first derivatives is required. The fixed-time stability of the entire closed-loop system is rigorously proved in the Lyapunov framework. Finally, the effectiveness and superiority of the proposed control scheme are proved by comparison with existing approaches.

The proposed NFTSM controller can merely be applied to a specific type of spacecrafts, as the relevant system states should be measurable.

A NFTSM controller based on a super-twisting-like FTDO can efficiently deal with dead-zone input, unknown external disturbance and parametric uncertainty for spacecraft pose control.

This investigation uses NFTSM control and super-twisting-like FTDO to achieve spacecraft pose control subject to dead-zone input, unknown external disturbance and parametric uncertainty.

Sensorless online measurements, application of variable speed drives has been given a great attention, especially over the past few years. In most of the previous literates dealing with permanent magnet synchronous motor (PMSM) drives, the combination of inter-sampled behavior with high gain design approach has not been discussed yet. This paper aims to discuss this feature in-depth.

The study contains a different approach for an observer running with surface-mounted permanent magnet synchronous machine drives to implement sensorless control. Design of sampled data observer methodology for one kind of AC machine having non-linear model and backed by an elegant formal stability convergence analysis using the tools of Lyapunov stability techniques was highly recommended in scientific contributions, and it is yet needed to be solved.

In this study, a solution to observation problem is covered and developed by combining ideas from the high-gain design approach and inter-sample predictor based on stator voltage measurements. The output state currents are accessible only at the sampling instant to solve the problem of states observation at continuous-time mode. This allows to reducing the usage of online appliances, improving reliability of control design and saving costs.

The proposed observer is capable of guaranteeing an acceptable closed loop dynamic response over a wide range of operation region and industrial process for random initial conditions.

The output state predictor has been interred in constructing the innovation correct term to prove the robustness of the proposed observer against attenuated sampling interval. To validate the theoretical results introduced by the main fundamental theorem and prove the observer stability convergence, the proposed observer is demonstrated through a sample study application to variable speed permanent magnet synchronous machine drive.

Increasing commercial applications for small unmanned aircraft create growing challenges in providing safe flight conditions. The conventional measures to detect icing are either expensive, energy consuming or heavy. The purpose of this paper is to develop a fault identification and isolation scheme using unknown input observers to detect and isolate actuator and structural faults in simultaneous occurrence.

The fault detection scheme is based on a deviation in system parameters due to icing and lock-in-place (LIP), two faults from different categories with similar indications that require different reconfiguration actions. The obtained residual signals are selected to be triggered by desired faults, while insensitive to others.

The proposed observer is sensitive to both actuator and structural faults, and distinguishes simultaneous occurrences by insensitivity to LIP in selected residue signals. Simulation results confirm the success of the proposed system in the presence of uncertainty and disturbance.

The fault detection and isolation scheme proposed here is based on the linear model of a winged aircraft, the Aerosonde. Moreover, the faults are applied to rudder and aileron in simulations, but the design procedure for other models is provided. The designed scheme could be further implemented on a non-linear aircraft model.

Applying the proposed icing detection scheme increases detection system reliability, since fault isolation enables timely reconfiguration schemes.

The observers proposed in previous papers detected icing fault but were not insensitive to actuator faults.

To propose and adaptive nonlinear controller for adjustable speed sensorless induction motor drive, using a novel adaptive rotor flux observer. The adaptive flux observer scheme in this paper provides the simultaneous estimation of the rotor speed, rotor resistance and stator resistance.

The IM rotor speed and rotor flux controllers are designed based on combination of input‐output feedback linearizing, linear optimal feedback control and sliding‐mode (SM) control methods. In addition a novel adaptive rotor flux observer is designed based on Lyapunov theory. The proposed control method is tested by simulation and experimental results.

The composite rotor speed and rotor flux observer in combination with adaptive rotor flux scheme guarantees a perfect speed, torque and flux tracking control for the IM sensorless drive.

The proposed control method has a drawback in the IM low speed operating region. Additional research may be able to solve this problem as well as should analyze the sensitivity of the IM drive system performance with respect to variation of the system controller and adaptive flux observer gains. In addition, this research should also analyze the influence of sampling rate, truncation errors, measurement noise, simplifying model assumption and magnetic saturation.

The proposed control method can be used for adaptive and robust control of the IM drive where an optimal efficiency is desired subject to the variable load torque demand.

Based on Lyapunov theory, a novel adaptive rotor flux observer is introduced in which the rotor speed, rotor resistance and stator resistance are treated as the unknown constant parameters.

This paper aims to devise a robust controller for the non-linear aircraft model using output feedback control topology in the presence of uncertain aerodynamic parameters.

Feedback linearization-based state feedback (SFB) controller is considered along with a robust outer loop control which is designed using Lyapunov’s second method. A high-gain observer (HGO) in accordance with the separation principle is used to implement the output feedback (OFB) control scheme. The robustness of the controller and observer is assessed by introducing uncertain aerodynamics coefficients in the dynamic model. The proposed scheme is validated using MATLAB/SIMULINK.

The efficacy of the proposed scheme is authenticated with the simulation results which show that HGO-based OFB control achieves the SFB control performance for a small value of the high-gain parameter in the presence of uncertain aerodynamic parameters.

A HGO for the non-linear model of aircraft with uncertain parameters is a novel contribution which could be further used for the unmanned aerial vehicles autopilot, flight trajectory tracking and path following.

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.