Fault tolerant control applied on an inverted pendulum by using extended Kalman filter

This paper proposes an active fault-tolerant control scheme based on a gain-scheduled H∞ design strategy. Under the assumption that the effects of faults on the system can be of affine parameter dependence, a reconfigurable robust H∞ controller is developed. The resulting controller is a function of the fault effect factors, which can be derived online from the residual vector of the fault detection and isolation (FDI) mechanism. To demonstrate the effectiveness of the proposed method, a non-linear double inverted pendulum system with a fault in the motor tachometer loop is considered. The adaptive fault-tolerant controller recovers well from the unstable system with loop failure.

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Sliding mode fault-tolerant control for Takagi-Sugeno fuzzy systems with local nonlinear models: Application to inverted pendulum and cart system

Transactions of the Institute of Measurement and Control ◽

10.1177/0142331220949366 ◽

2020 ◽

pp. 014233122094936

Author(s):

Riadh Hmidi ◽

Ali Ben Brahim ◽

Slim Dhahri ◽

Fayçal Ben Hmida ◽

Anis Sellami

Keyword(s):

Fuzzy Systems ◽

Inverted Pendulum ◽

Fault Tolerant ◽

Sliding Mode ◽

Nonlinear Models ◽

Fault Tolerant Control ◽

Simultaneous Occurrence ◽

Sensor Faults ◽

Adaptive Sliding Mode ◽

Takagi Sugeno

This paper proposes fault-tolerant control design for uncertain nonlinear systems described under Takagi-Sugeno fuzzy systems with local nonlinear models that satisfy the Lipschitz condition. First, by transforming sensor faults as ‘pseudo-actuator’ faults, an adaptive sliding mode observer is designed in order to simultaneously estimate system states, actuator and sensor faults despite the presence of norm-bounded uncertainties. Second, an adaptive sliding mode controller is suggested to provide a solution to stabilize the closed-loop system, even in the event of simultaneous occurrence of faults in actuators and sensors. Next, the main objective of the fault-tolerant control strategy is to compensate for the effects of fault based on the feedback information. Therefore, using the LMI optimization method, sufficient conditions are developed with [Formula: see text] to calculate the gains of the observer and the controller. Then, particular attention is paid to the simultaneous maximization, by convex multi-objective optimization, of the Lipschitz nonlinear constant in Takagi-Sugeno fuzzy modelling and uncertainties attenuation level. The results of the simulation illustrate the effectiveness of our fault-tolerant control approach using a nonlinear inverted pendulum with a cart system.

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Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter

Energies ◽

10.3390/en13112972 ◽

2020 ◽

Vol 13 (11) ◽

pp. 2972 ◽

Cited By ~ 1

Author(s):

Waseem El Sayed ◽

Mostafa Abd El Geliel ◽

Ahmed Lotfy

Keyword(s):

Kalman Filter ◽

Fault Diagnosis ◽

Extended Kalman Filter ◽

Continuous Monitoring ◽

Unscented Kalman Filter ◽

Fault Tolerant ◽

Synchronous Generator ◽

Operating Conditions ◽

Practical Implementation ◽

Complete Failure

Since the permeant magnet synchronous generator (PMSG) has many applications in particular safety-critical applications, enhancing PMSG availability has become essential. An effective tool for enhancing PMSG availability and reliability is continuous monitoring and diagnosis of the machine. Therefore, designing a robust fault diagnosis (FD) and fault tolerant system (FTS) of PMSG is essential for such applications. This paper describes an FD method that monitors online stator winding partial inter-turn faults in PMSGs. The fault appears in the direct and quadrature (dq)-frame equations of the machine. The extended Kalman filter (EKF) and unscented Kalman filter (UKF) were used to detect the percentage and the place of the fault. The proposed techniques have been simulated for different fault scenarios using Matlab®/Simulink®. The results of the EKF estimation responses simulation were validated with the practical implementation results of tests that were performed with a prototype PMSG used in the Arab Academy For Science and Technology (AAST) machine lab. The results showed impressive responses with different operating conditions when exposed to different fault states to prevent the development of complete failure.

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Fault-tolerant pose and inertial parameters estimation of an uncooperative spacecraft based on dual vector quaternions

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering ◽

10.1177/0954410017751766 ◽

2018 ◽

Vol 233 (4) ◽

pp. 1250-1269 ◽

Cited By ~ 4

Author(s):

Jianping Yuan ◽

Xianghao Hou ◽

Chong Sun ◽

Yu Cheng

Keyword(s):

Kalman Filter ◽

Extended Kalman Filter ◽

Formation Flying ◽

Fault Tolerant ◽

Estimation Algorithm ◽

Parameters Estimation ◽

Small Satellites ◽

Dual Vector ◽

Inertial Parameters ◽

Space Target

Estimating the parameters of an unknown free-floating tumbling spacecraft is an essential task for the on-orbit servicing missions. This paper proposes a dual vector quaternion based fault-tolerant pose and inertial parameters estimation algorithm of an uncooperative space target using two formation flying small satellites. Firstly, by utilizing the dual vector quaternions to model the kinematics and dynamics of the system, not only the representation of the model is concise and compacted, but also the translational and rotational coupled effects are considered. By using this modeling technique along with the measurements from the on-board vision-based sensors, a dual vector quaternion based extended Kalman filter for each of the two small satellites is designed. Secondly, both of the estimations from each small satellite will be used as inputs of the fault-tolerant algorithm. This algorithm is based on the fault-tolerant federal extended Kalman filter strategy to overcome the estimation errors caused by the faulty measurements, the unknown space environment and the computing errors by setting the appropriate ratios of the two estimations from the first step dual vector quaternions extended Kalman filter. Together with the first and second steps, a novel fault-tolerant dual vector quaternions federal extended Kalman filter using two formation flying small satellites is proposed by this paper to estimate the pose and inertial parameters of a free-floating tumbling space target. By utilizing the estimation algorithm, a good prior knowledge of the unknown space target can be achieved. Finally, the proposed dual vector quaternion federal extended Kalman filter is validated by mathematical simulations to show its robust performances.

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