The hunting phenomenon is an intrinsic swaying motion appearing in railway vehicles due to the vehicle’s forward speed and the wheel–rail contact forces. Hunting motion consists of wheelset and other vehicle’s components oscillations that arise above a certain vehicle’s speed known as critical or hunting speed. These oscillations are of unstable nature and represent a safety hazard as they could lead to the vehicle’s derailment. This article analyses the stability of a bogie nonlinear model for a Spanish high-speed train when this is travelling at speeds near the hunting speed. The vehicle’s stability is studied by means of root loci methods, and the value of the critical speed is found. In addition to this, the behaviour of the vehicle is studied in both stable and unstable regions and the existence of limit cycles is discussed in this work. Finally, a sensitivity analysis of the axle load and suspension parameters is performed. The results show that the axle load, the vertical stiffness of the primary suspension and the lateral damping of the secondary suspension have a significant influence on the value of the critical speed.

En este tutorial se aborda el tema del modelado y control de las turbinas eólicas marinas flotantes. En primer lugar se describen estos sistemas de extracción de energía eólica que están situados en alta mar, en aguas profundas, y se comentan algunas aproximaciones a su modelado. El control de potencia de estas turbinas es presentado con detalle, explicando los distintos tipos de control que buscan maximizar la obtención de energía. Se resalta el problema de la inducción de dinámicas inestables en la plataforma flotante debido al control del rotor del aerogenerador, una dificultad que no aparece en otros tipos de turbinas. La reducción de las vibraciones mediante estrategias de control estructural se ilustra con un ejemplo, usando un dispositivo pasivo que es complementado con un mecanismo denominado inerter, mostrando con resultados de simulación cómo se consiguen eliminar las oscilaciones de la turbina flotante. Este ejemplo está basado en resultados preliminares obtenidos en la investigación que llevan a cabo los autores de este tutorial.

In this paper we study a recently introduced technique for nonlinear dynamical systems in which the equation is replaced by a sequence of linear, time‐varying approximations. This allows many of the classical results in linear systems theory to be applied to nonlinear systems. Here we study two particular areas—stability theory and the frequency‐domain theory of nonlinear systems.

Floating offshore wind turbines (FOWT) are designed to overcome some of the limitations of offshore bottom-fixed ones. The development of computational models to simulate the behavior of the structure and the turbine is key to understanding the wind energy system and demonstrating its feasibility. In this work, a general methodology for the identification of reduced dynamic models of barge-type FOWTs is presented. The method is described together with an example of the development of a dynamic model of a 5 MW floating offshore wind turbine. The novelty of the proposed identification methodology lies in the iterative loop relationship between the identification and validation processes. Diversified data sets are used to select the best-fitting identified parameters by cross evaluation of every set among all validating conditions. The data set is generated for different initial FOWT operating conditions. Indeed, an optimal initial condition for platform pitch was found to be far enough from the system at rest to allow the dynamics to be well characterized but not so far that the unmodeled system nonlinearities were so large that they affected significantly the accuracy of the model. The model has been successfully applied to structural control research to reduce fatigue on a barge-type FOWT.