Saverio Farsoni

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.

Residual Generator Fuzzy Identification for Wind Farm Fault Diagnosis

Abstract In the recent years the wind turbine industry has focused on optimising the cost of energy. One of the important factors in the achievement of this task consists of increasing the reliability of the wind turbines, which can be obtained using advanced fault detection and isolation strategies. Clearly, most faults are managed quite easily at a wind turbine control level. However, some faults are better dealt with at wind farm level, when the wind turbine is located in a wind farm. This paper aims at proposing a fault detection and isolation solution with application to a wind farm benchmark model. The considered benchmark includes a small wind farm of nine wind turbines, based on simple models of wind turbines, as well as the wind and interactions between wind turbines in the wind farm. The solution relies on a set of piecewise affine Takagi–Sugeno models, which are identified from the noisy measurements acquired from the simulated wind park. The design of the fault isolation strategy is also enhanced by the use of the proposed fuzzy approach. Finally, the wind park simulator is exploited for validating the achieved performances of the suggested methodology.

Fault tolerant control of an offshore wind turbine model via identified fuzzy prototypes

In order to improve the safety, the reliability, the efficiency, and the sustainability of offshore wind turbine installations, thus avoiding expensive unplanned maintenance, the accommodation of faults in their earlier occurrence is fundamental. Therefore, the main contribution of this work consists of the development of a fault accommodation scheme applied to the control of a wind turbine nonlinear model. In particular, a data-driven strategy relying on fuzzy models is exploited to build the fault tolerant control scheme. Fuzzy theory is exploited here since it allows to approximate easily the unknown nonlinear model and manage uncertain data. Moreover, the fuzzy prototypes, which are directly identified from the wind turbine measurements, provide the reconstruction of the considered faults, thus leading to the direct design of the fault tolerant control module. In general, the nonlinearity of wind turbine system could generate complex analytic solutions. This aspect of the work, followed by the simpler strategy relying on fuzzy prototypes, represents the key point when on-line implementations are considered for a viable application of the proposed methodology. A realistic offshore wind turbine simulator is used to validate the achieved performances of the suggested methodology. Finally, comparisons with different fault tolerant control methods serve to highlight the advantages of the suggested approach.

Compensation of Load Dynamics for Admittance Controlled Interactive Industrial Robots Using a Quaternion-Based Kalman Filter

The paper describes a control architecture for industrial robotic applications allowing human/robot interactions, using an admittance control scheme and direct sensing of the human inputs. The aim of the proposed scheme is to support the operator of an industrial robot, equipped with a force/torque (F/T) sensor on the end-effector, during human/robot collaboration tasks involving heavy payloads carried by the robot. In these practical applications, the dynamics of the load may significatively affect the measurements of the F/T sensor. Model-based compensation of such dynamic effects requires to compute linear acceleration and angular acceleration/velocity of the load, that in this paper are estimated by means of a quaternion-based Kalman filter and assuming that the only available measurements come from the forward kinematics of the robot. Experimental results demonstrate the feasibility of the approach and its industrial applicability.

Fault tolerant control design for a wind farm benchmark via fuzzy modelling and identification

In order to improve the safety, the reliability, and the efficiency of wind farm installations, thus avoiding expensive unplanned maintenance, the accommodation of faults in their earlier occurrence is fundamental. Therefore, the main contribution of this paper consists of the development of a tolerant control scheme applied by means of a direct and viable approach. In particular, a data-driven strategy based on fuzzy logic is exploited for deriving the fault tolerant control scheme. Fuzzy theory is exploited since it is able to approximate easily unknown nonlinear models and manage uncertain data. Moreover, these fuzzy prototypes are directly identified from the wind farm measurements and lead to the straightforward design of the fault tolerant control scheme. In general, an analytic approach, where the system nonlinearity is explicitly considered, would require more complex control design methodologies. This aspect of the work, followed by the simpler solution relying on fuzzy rules, represents the key point when on-line implementations are considered for a viable application of the proposed methodology. A realistic wind farm simulator is used to validate the achieved performances of the suggested methodology.

A Versatile Ultrasound Simulation System for Education and Training in High-Fidelity Emergency Scenarios

Point of care ultrasonography and the related focused assessment with sonography for trauma protocol, if performed by experienced physicians, is a highly sensitive examination, and specific for the detection of free fluids. Different systems and methods have been proposed for training, including simulation as one of the most efficient. This paper presents an ultrasound training system, specifically designed to be used during bedside high fidelity simulation scenarios, that could facilitate the learning process. The development of the proposed system exploited novel rapid prototyping electronic boards as a means to obtain good performances with a low cost. Moreover, the design of the data structure permits the construction of a library that caters for individual needs, with the possibility of adding emergency scenarios, collecting pictures or videos, as well as 3-D volumes. The device has been compared with currently commercial ultrasound simulators and its innovative aspects have been highlighted. Finally, it has been tested during a training session in order to evaluate features, such as realism and user-friendliness.

Robust actuator fault diagnosis of a wind turbine benchmark model

This paper describes the design of a robust fault diagnosis scheme that is applied to the actuators of a wind turbine benchmark. The methodology is based on adaptive filters obtained via a nonlinear geometric approach, which allows to obtain interesting decoupling property with respect to uncertainty affecting the wind turbine system. The residual generation scheme exploits the on-line estimation of the actuator fault signal generated by the adaptive filters. The nonlinearity of the wind turbine model is described by the mapping to the power conversion ratio from tip-speed ratio and blade pitch angles, usually not known in analytical form. The wind turbine unit is considered as benchmark to show the design procedure, including the aspects of the nonlinear disturbance decoupling method, as well as the viability of the proposed approach. Extensive simulations of the benchmark process are practical tools for assessing experimentally the features of the developed actuator fault diagnosis scheme, in the presence of modelling and measurement errors.

System and Fault Modeling

This chapter provides an overview of the main challenges of modeling for very demanding systems, such as wind turbine systems, which require reliability, availability, maintainability, and safety over power conversion efficiency. These issues have begun to stimulate research and development in the wide control community particularly for the installations that need a high degree of sustainability. This represents a key point for offshore wind turbines and wind park installations, since they are characterized by expensive and/or safety critical maintenance work. In this case, a clear conflict exists between ensuring a high degree of availability and reducing maintenance times, which affect the final energy cost. On the other hand, wind turbines have highly nonlinear dynamics, with a stochastic and uncontrollable driving force as input in the form of wind speed, thus representing an interesting challenge also from the modeling point of view. Moreover, a proper mathematical description of the wind turbine system should be able to capture the complete behavior of the process under monitoring, thus providing an important impact on the control design itself. In this way, the fault diagnosis and control schemes could guarantee prescribed performance, whilst also giving a degree of tolerance to possible deviation of characteristic properties or system parameters from standard conditions, if properly included in the wind turbine model itself.

Fault Tolerant Control for Wind Turbine Systems

This chapter introduces the fault diagnosis and the fault tolerant schemes that will be adopted in the simulations of the wind turbine systems considered in this monograph. Firstly, in the light of the design of the fault diagnosis module already proposed and oriented to the design of the control reconfiguration and accommodation system, the effective design of the fault estimators for fault tolerant control is summarized. Then, by exploiting the fault diagnosis scheme, interesting by-products consisting of the fault detection and isolation tasks are achieved. Finally, possible implementations of fault tolerant controller schemes are shown, which represent the key issues of the sustainable control design for safety-critical systems, such as the offshore wind turbine installations. In general, the most effective fault tolerant control schemes rely on the online estimation and compensation of the system faults, modeled as equivalent input and output sensor faults, which are able to effectively describe any fault conditions affecting the considered wind turbine systems.

Matlab and Simulink Implementations

This chapter describes the main implementation and computational aspects of the most important modeling and control blocks used for the development of the wind turbine and wind farm benchmarks in the Matlab and Simulink environments. An insight into the wind turbine and farm modeling, as well as their control loops, is provided with the goal of providing overviews of the typical actuation, sensing, and control implementations available for wind turbine simulators. The chapter intended to provide also an updated and broader perspective by covering not only the modeling and control aspects in the Matlab and Simulink environments of individual wind turbines, but also outlining a number of solutions of advanced control approaches. In summary, wind energy is a fast growing industry, and this growth has led to a large demand for better modeling and control of wind turbines by means of suitable simulation codes. Uncertainty, disturbance and other deviations from normal working conditions of the wind turbines make the control challenging, thus motivating the need for advanced implementations and a number of sustainable control realizations that should be exploited to reduce the cost of wind energy. Finally, the development of fault diagnosis and sustainable control solutions for wind energy systems is demonstrated in this chapter by means of proper simulation codes, whilst there are many fundamental and applied issues that are addressed by the systems and control community to significantly improve the efficiency, operation, and lifetimes of wind turbines.