Paolo Castaldi

Identification of dynamic errors-in-variables models

This paper deals with the identifiability of scalar dynamic errors-in-variables models characterized by rational spectra. The hypothesis of causality for the underlying dynamic system is taken into account. By making use of stochastic realization theory and of the structural properties of state-space representations, it is shown that, under mild assumptions, the model is uniquely identified.

Data Driven Approach for Wind Turbine Actuator and Sensor Fault Detection and Isolation

Abstract In order to improve reliability of wind turbines, it is important to detect and isolate faults as fast as possible, and handle them in an optimal way. An important component in modern wind turbines is the converter, which for a wind turbine control point–of–view normally provides the torque acting on the wind turbine generator, as well as measurement of this torque. In this work, a diagnosis strategy based on fuzzy prototypes is presented, in order to detect these faults in the converter, and isolate them either to be an actuator or a sensor fault. The fuzzy system is used since the model under investigation is nonlinear, whilst the wind speed measurement is highly noisy, due to the turbulence around the rotor plane. The fuzzy system consists of a set of piecewise affine Takagi–Sugeno models, which are identified from the noisy measurements acquired from the simulated wind turbine. The fault detection and isolation strategy is thus designed based on these fuzzy models. The wind turbine simulator is finally used to validate the achieved performances of the suggested fault detection and isolation scheme.

Fault Diagnosis of a Wind Turbine Benchmark via Identified Fuzzy Models

In order to improve the availability of wind turbines and to avoid catastrophic consequences, the detection of faults in their earlier occurrence is fundamental. This paper proposes the development of a fault diagnosis scheme relying on identified fuzzy models. The fuzzy theory is exploited since it allows approximating uncertain models and managing noisy data. These fuzzy models, in the form of Takagi-Sugeno prototypes, represent the residual generators used for fault detection and isolation (FDI). A wind turbine benchmark is used to validate the achieved performances of the designed FDI scheme. Finally, extensive comparisons with different fault diagnosis methods highlight the features of the suggested solution.

Parameter estimation of induction motor at standstill with magnetic flux monitoring

The paper presents a new method for the estimation of the electric parameters of induction motors (IMs). During the identification process the rotor flux is also estimated. The procedure relies on standstill tests performed with a standard drive architecture, hence, it is suitable for self-commissioning drives. The identification scheme is based on the model reference adaptive system (MRAS) approach. A novel parallel adaptive observer (PAO) has been designed, starting from the series-parallel Kreisselmeier observer. The most interesting features of the proposed method are the following: 1) rapidity and accuracy of the identification process; 2) low-computational burden; 3)excellent noise rejection, thanks to the adopted parallel structure; 4) avoidance of incorrect parameter estimation due to magnetic saturation phenomena, thanks to recursive rotor flux monitoring. The performances of the new scheme are shown by means of simulation and experimental tests. The estimation results are validated by comparison with a powerful batch nonlinear least square (NLS) method and by evaluating the steady-state mechanical curve of the IM used in the tests.

Hybrid Model–Based Fault Detection of Wind Turbine Sensors

Abstract In order to improve reliability of wind turbines, it is important to detect faults in their very early occurrence, and to handle them in an optimal way. This paper focuses on the pitch sensors of the turbine blade system, as they are mainly used for wind turbine control, in order to maximise the power production, and the efficiency of the whole process. On the other hand, as the input-output behaviour of the system under diagnosis is nonlinear, this work suggests a modelling scheme relying on piecewise affine models, whose parameters are identified through the acquired input–output measurements affected by measurement uncertainty. Therefore, these hybrid prototypes are exploited for generating suitable residual signals, which allow the detection and the isolation of the considered sensor faults. This noise rejection scheme is used since the wind turbine measurements are not very reliable, due to the uncertainty of wind speed acting on the wind turbine, and to the turbulence around the rotor plane. A detailed benchmark model simulating the wind turbine where realistic fault conditions can be considered shows the effectiveness of both the identification and fault diagnosis techniques.

Nonlinear actuator fault detection and isolation for a general aviation aircraft

Abstract This paper addresses the problem of detection and isolation of actuator faults for a general aviation aircraft, where the nonlinear simulation aircraft model embeds the effects of wind gusts, atmospheric turbulence and measurement errors. The approach is based on the recently introduced NonLinear Geometric Approach (NLGA) to the Fault Detection and Isolation (FDI) problem. The actuators FDI is performed in a coordinated turn, hence with coupled longitudinal and lateral–directional dynamics. This work represents the first complete NLGA FDI scheme for a general aviation aircraft in a condition with tight–coupled dynamics. The results obtained in the simulation of the faulty behaviour of a nonlinear Piper PA30 aircraft are finally reported.

Active Fault Tolerant Control of Nonlinear Systems: The Cart-Pole Example

Active fault tolerant control of nonlinear systems: The cart-pole example This paper describes the design of fault diagnosis and active fault tolerant control schemes that can be developed for nonlinear systems. The methodology is based on a fault detection and diagnosis procedure relying on adaptive filters designed via the nonlinear geometric approach, which allows obtaining the disturbance de-coupling property. The controller reconfiguration exploits directly the on-line estimate of the fault signal. The classical model of an inverted pendulum on a cart is considered as an application example, in order to highlight the complete design procedure, including the mathematical aspects of the nonlinear disturbance de-coupling method based on the nonlinear differential geometry, as well as the feasibility and efficiency of the proposed approach. Extensive simulations of the benchmark process and Monte Carlo analysis are practical tools for assessing experimentally the robustness and stability properties of the developed fault tolerant control scheme, in the presence of modelling and measurement errors. The fault tolerant control method is also compared with a different approach relying on sliding mode control, in order to evaluate benefits and drawbacks of both techniques. This comparison highlights that the proposed design methodology can constitute a reliable and robust approach for application to real nonlinear processes.

A comparison among different inversion methods for multi-exponential NMR relaxation data

The inversion of data to be represented by sums or continuous distributions of exponentials is done by different algorithms and compared. The published CONTIN program presents a chosen solution with an appropriate amount of detail. An in-house program EXDISTR allows operative choice of various constraints in order to show the consequences in quality of fit of allowing various features such as extra maxima or minima. Another in-house program based on the system theory approach, IDENT, treats the data as the output samples of a linear, time-invariant, autonomous dynamic system.

Adaptive Fault–Tolerant Control Design Approach for a Wind Turbine Benchmark

Abstract This paper addresses the development of an active fault tolerant control scheme that is applied to a wind turbine simulated benchmark. The proposed methodology is based on a comprehensive scheme relying on adaptive controllers designed by means of the on–line identification of the system model under diagnosis. In this way, the controller reconfiguration mechanism exploits an adaptive regulator implementation, depending on the on–line estimate of system model. One of the advantages of this strategy is that, for example, the original structure of logic–based switching digital controller scheme already implemented for the wind turbine benchmark can be almost preserved. The active fault tolerant control scheme is therefore applied to a wind turbine simulated benchmark, in the presence of disturbance and measurement errors, along nominal operating conditions, including also different realistic fault situations. The achieved results in both fault–free and faulty conditions serve to show the enhancement of the control performances, and the fault accommodation features.

Fault diagnosis and control reconfiguration for satellite reaction wheels

This paper presents preliminary results regarding the development of a supervision scheme for the attitude control system of a nonlinear satellite model. The main issue concerns the handling of faults affecting the reaction wheels, i.e. how to detect and isolate faults, and how to prevent propagation into failures with potential mission loss as a consequence. Thus, this work investigates the design of a scheme for fault detection, isolation and control reconfiguration applied to the reaction wheels of a spacecraft attitude control, based on the satellite model. As the study focuses on a general satellite nonlinear model, where aerodynamic and gravitational disturbances, as well as measurement errors are present, the robustness of the suggested strategy is achieved by exploiting an explicit disturbance decoupling method. The results obtained demonstrate how the proposed methodology can constitute a successful approach for real application in future spacecraft.