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This study proposes a parameter estimation method, together with a grid synchronisation algorithm, for wind turbinedriven doubly fed induction generators (DFIGs). Aiming at achieving an automated control procedure, their integration with a previously published power control strategy is also addressed. During a normal operation mode, the DFIG is grid-connected and generated power is commanded by combining a sliding-mode control (SMC) scheme, which provides high dynamic performance and robust behaviour, with a model reference adaptive system observer, estimating both rotor position and speed without the use of mechanical sensors. In order to preserve performance during start-up and grid connection without the additional requirement of an encoder, the proposed parameter estimation and grid synchronisation schemes are both sensorless. Moreover, the same SMC structure of the power control strategy is also adopted for the grid synchronisation algorithm, which facilitates transfer between synchronisation and power controllers at the instant of grid connection. Thereby, a global sensorless SMC configuration result, which is self-matched by the parameter estimation process. The resulting scheme has been applied to a hardware-in-the-loop-based DFIG virtual prototype under realistic wind conditions, obtaining satisfactory results.

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Hydrodynamic Floating Offshore Wind Turbine (FOWT) platform specifications are typically dominated by seaworthiness and maximum operating platform-pitch angle-related requirements. However, such specifications directly impact the challenge posed by an FOWT in terms of control design. The conventional FOWT systems are typically based on large, heavy floating platforms, which are less likely to suffer from the negative damping effect caused by the excessive coupling between blade-pitch control and platform-pitch motion. An advanced control technique is presented here to increase system stability for barge type platforms. Such a technique mitigates platform-pitch motions and improves the generator speed regulation, while maintaining blade-pitch activity and reducing blade and tower loads. The NREL's 5MW + ITI Energy barge reference model is taken as a basis for this work. Furthermore, the capabilities of the proposed controller for performing with a more compact and less hydrodynamically stable barge platform is analysed, with encouraging results.Several attempts have been done to control and improve FOWT systems-however, not so many for barge mounted systems. This is because of the dilemma presented by this type of platform. When the blade-pitch action tries to regulate the generator speed in the above rated wind speed, a coupling between blade-pitch and platform-pitch motions can happen [10], known as the negative platform damping effect. This phenomenon makes the turbine unstable, potentially damaging mechanical components. One of the first and most complete studies done to tackle this phenomenon was carried out in [11], where three control alternatives were proposed to mitigate the barge platform-pitch motions. The best results were achieved detuning the blade-pitch PI control gains. Great reductions in the platform-pitch motion and in the mechanical component loads were achieved. However, the generator speed regulation quickness was degraded.Several Linear Quadratic Regulator (LQR) based controller designs are compared with the baseline blade-pitch PI controller in [12]. The LQR Gain-Scheduling (GS) and the Linear Parameter-Varying (LPV) GS State-Feedback (SF) control techniques show the best results. The LQR GS control provides the best power regulation, whereas the LPV GS SF provides the best platform-pitch damping. The baseline blade-pitch PI controller used for the comparison is tuned with those blade-pitch PI gains used for onshore wind turbines. Unfortunately, a mechanical load analysis is missing to verify the impact of the proposed controllers on the mechanical components.A comparison between the Individual Pitch Control (IPC) and the Collective Pitch Control (CPC) is presented in [13]. The IPC is based on three modules: the Disturbance Accommodating Control (DAC) aimed at eliminating the wind disturbances, the Model Predictive Control (MPC) to remove the influence of wave disturbances, and the fuzzy control module to combine both these algorithms. Both IPC and CPC techniques improve the power productio...

Hardware-in-the-loop Active control a b s t r a c tThe self-excited vibrations due to the regenerative effect, commonly known as chatter, are one of the major problems in machining processes. They cause a reduction in the surface quality and in the lifetime of mechanical elements including cutting tools. Furthermore, the experimental investigations of chatter suppression techniques are difficult in a real machining environment, due to repeatability problems of hard to control parameters like tool wear or position dependent dynamic flexibility. In this work, a mechatronic hardware-in-the-loop (HIL) simulator based on a flexible structure is proposed for dimensionless study of chatter in orthogonal cutting. Such system reproduces experimentally, on a simple linear mechanical structure in the laboratory, any stability situation which can be used to test and optimise active control devices. For this purpose, a dimensionless formulation is adopted and the delay related to the phase lag of the actuator and the controller employed on the HIL is compensated.