Search

The presence of faults in dynamic systems causes the potential loss of some of the control objectives. For that reason, a fault-tolerant controller is required to ensure a proper operation, as well as to reduce the risk of accidents. The present work proposes a passive fault-tolerant controller that is based on robust techniques, which are utilized to adjust a proportional-derivative scheme through a linear matrix inequality. In addition, a nonlinear term is included to improve the accuracy of the control task. The proposed methodology is implemented in the control of a two degrees of a freedom robotic helicopter in a simulation environment, where abrupt faults in the actuators are considered. Finally, the proposed scheme is also tested experimentally in the Quanser® 2-DOF Helicopter, highlighting the effectiveness of the proposed controller.

This paper considers a general approach to fault diagnosis using a generalized Hamiltonian system representation. It can be considered that, in general, nonlinear systems still represent a problem in fault diagnosis because there are results only for a specific class of them. Therefore, fault diagnosis remains a challenging research area despite the maturity of some of the available results. In this work, a type of nonlinear system that admits a generalized Hamiltonian representation is considered, in practice, there are many systems that have this kind of representation. Thereupon, an approach for fault detection and isolation based on the Hamiltonian representation is proposed. First, following the classic approach, the original system is decoupled in different subsystems so that each subsystem is sensitive to one particular fault. Then, taking advantage of the structure, a simple way to design the residuals is presented. Finally, the proposed scheme is validated at the two-degree of freedom (DOF) helicopter of Quanser&reg, where the presence of faults in sensors and actuators were considered. The results show the efficacy of the proposed scheme.

In this document, a data-driven algorithm to continuous-time observer-based fault isolation from sampled input-output data is considered. The core of the proposed algorithm is to show the advantages with respect previous results such as fault isolation and the capability of consider a special class of nonlinear systems. An example is shown using the algorithm to prove its efficiency as well as a justification of the results.

The problem of fault detection and isolation in a class of nonlinear systems having a Hamiltonian representation is considered. In particular, a model of a planar vertical take-off and landing aircraft with sensor and actuator faults is studied. A Hamiltonian representation is derived from an Euler-Lagrange representation of the system model considered. In this form, nonlinear decoupling is applied in order to obtain subsystems with (as much as possible) specific fault sensitivity properties. The resulting decoupled subsystem is represented as a Hamiltonian system and observer-based residual generators are designed. The results are presented through simulations to show the effectiveness of the proposed approach.

Fault diagnosis in nonlinear systems is a challenging and very active research area. One of the difficulties to detect and isolate faults in nonlinear systems via observer-based methods is the design of a residual generator. In this work an integrated procedure combining conventional decoupling methods and Fuzzy Takagi-Sugeno observers for fault diagnosis in nonlinear systems is proposed. The advantage of the proposed AI based approach is that the design condition for the observers is relaxed in contrast with conventional approaches. Furthermore the potential use of decoupling techniques is reinforced. The design methodology is shown using a three tank system.

Abstract The problem of threshold selection for fault detection in nonlinear systems is considered. For the linear case the existing result requires of factorization of transfer function from perturbations to the output. In the nonlinear case a different approach is proposed in this work. Using ideas based on the concept of uniform ultimate boundedness a procedure to construct a residual generation is considered. The residual obtained is defined in such a way that a corresponding threshold can be defined in a natural form, in fact, as term in the residual equation. The proposed threshold can reduce the size of detectable faults and in this way the result is comparable to the existing for linear systems. The benefits of the approach are discussed.

Este artículo presenta un método de control tolerante a fallas para sistemas no lineales planos. Las propiedades intrínsecas d e los sistemas planos generan redundancia analítica y permiten calcular todos los estados y las entradas de control del sistema. Los residuo s son calculados comparando las medidas reales provenientes de los se nsores y las señales obtenidas gracias al conjunto de ecuacione s del sistema plano. Fallas multiplicativas y aditivas se pueden man ejar de manera indistinta. Las señales redundantes obtenidas co n las ecuaciones del sistema plano son usadas para reconfigurar el si stema con falla. La factibilidad del método propuesto es verifi cada para fallas aditivas en un sistema de tres tanques.

This paper addresses a fault detection and isolation technique for differential flat systems. For such nonlinear systems, it is possible to find a set of variables, named flat outputs such that states and control inputs can be expressed as functions of flat outputs and their derivatives. Flat systems properties are used to detect and isolate faults and the non-uniqueness property of the set of flat outputs is used for increase the number of residues and improve the fault isolation, the proposed approach will be applied on a classical three tank system.

The characterization of frequency response functions for convergent systems is considered in this paper. Besides a couple of approaches available in the literature, this paper is focused on the frequency response function proposed recently for a class of non-linear systems which are called convergent. Using some properties of convergent systems a characterization of a frequency response function based on Fourier series is obtained. This result expands a known result from linear to nonlinear systems and complements the existing results about frequency response functions of nonlinear systems. An example is utilized to show the proposed approach.