This paper presents an application of gain-scheduling (GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed. The turbine system with the dynamics variation is represented by a linear parameter-varying (LPV) model, which is derived by interpolating linearized models at various operating wind speeds. To achieve control objectives of regulating power capture and minimizing platform motions, both linear quadratic regulator (LQR) GS and LPV GS controller design techniques are explored. The designed controllers are evaluated in simulations with the NREL 5 MW wind turbine model, and compared with the baseline proportional-integral (PI) GS controller and non-GS controllers. The simulation results demonstrate the performance superiority of LQR GS and LPV GS controllers, as well as the performance trade-off between power regulation and platform movement reduction.
A frequency based data-driven control design considering mixed H2/H∞ control objectives is developed for multiple input-single output systems. The main advantage of the data-driven control over the model-based control is its ability to use the frequency response measurements of the controlled plant directly without the need to identify a model for the plant. In the proposed methodology, multiple sets of measurements can be considered in the design process to accommodate variations in the system dynamics. The controller is obtained by translating the mixed H2/H∞ control objectives into a convex optimization problem. The H∞ norm is used to shape closed loop transfer functions and guarantee closed loop stability, while the H2 norm is used to constrain and/or minimize the variance of signals in the time domain.The proposed data-driven design methodology is used to design a track following controller for a dual-stage HDD. The sensitivity decoupling structure[16] is considered as the controller structure. The compensators inside this controller structure are designed and compared by decoupling the system into two single input-single-output systems as well as solving for a single input-double output controller.Index Terms-Data-driven control design, Mixed H2/H∞ norms, Multiple input-single output systems, Hard disk drives, Trackfollowing controller, Sensitivity decoupling.
This paper studies possible robust control design methods in triple-stage actuation settings for achieving minimum position error signal (PES) while maintaining enough stability margins. Firstly, the sensitivity-decoupling design technique, is utilized to estimate the resulting increase in low frequency disturbance attenuation and servo bandwidth. A systematic tuning methodology based on μ-synthesis is then proposed for track-following servo design of triple-stage actuation systems. In this approach, the objective is to minimize the PES, by considering all constraints and uncertainties explicitly in the design. We describe a step by step Multi-Input Single-Output (MISO) controller design methodology which includes system modeling, noise characterization, control objective determination and controller synthesis and verification. In this methodology, servo bandwidth is not the only performance metric. Rather, the control objective will be to minimize the closed-loop system H∞ norm directly, while all stroke and control constraints are satisfied and enough stability margin is ensured. The proposed method is applied to design track-following feedback controllers for single-, dual- and triple-stage actuation systems. Simulation results show that compared to dual-stage actuation, triple-stage actuation enhances low frequency disturbance rejection by 6 dB at around 100Hz and increases servo bandwidth from ∼3kHz to ∼5kHz.
Input/ output feedback linearization and smoothed sliding control methods are used to control a floating offshore wind turbine on a barge platform in high wind speed in order to regulate the power capture. The model of the turbine has the blade pitch angle as the input, generator speed, platform pitch angle and its derivative as the measurements, and wind speed as a disturbance. The designed controllers have been applied to the simplified model of the plant which is used for controller design and also a more complex model which considers all six degrees of freedom for platform movements. Moreover, their performance is compared with the baseline controller for floating offshore wind turbines [1]. Both nonlinear controllers have improved the power fluctuation compared to the baseline controller. Also, sliding control has been shown to have better performance than the input/ output controller, since it can consider the uncertainty of the disturbance signal in the controller design.
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