# Parametric Analysis of Control Techniques for 15 MW Semi-Submersible Floating Wind Turbine
###### Abstract
As the reasons for achieving a better system performance of floating wind turbines have become more important, studies based on modern control theories have also been conducted. Using state observers and a linear quadratic regulator (LQR), the root mean square error (RMSE) of the platform pitch motion and the generator speed were able to be reduced by 16% and 32%, respectively [15]. Additionally, state control of floating platforms using a model predictive control (MPC) demonstrated a significant reduction in the platform motions [16]. However, the modern control algorithms proposed in the literature required a complete replacement of the classical multiple SISO (Single Input Single Output) loop-based blade pitch and generator torque control structures with a full-state feedback control structure to address multiple inputs. Accordingly, replacing the conventional classical control algorithms, which have demonstrated stable performance over long periods, with modern control algorithms remains challenging for the industry to readily accept, due to the costs, time for field testing, and compatibility issues with existing control systems. Accordingly, composite control algorithms combining classical control-based techniques with various objectives have been recently proposed for floating offshore wind turbines. In the study by [PERSON] et al., adding the tower damper, nacelle feedback, and peak shaving to the baseline controller resulted in a 22% reduction in the fore-aft tower fatigue loads, while the blade pitch rate was reduced by 4% [17]. In the study by [PERSON] et al., adding the nacelle feedback and the peak shaving to the baseline controller reduced the platform pitch motion by 15.4% and 29.1%, respectively, and also reduced the tower-base load by 24.4% and 48.2%, respectively [18]. However, despite the superior performance of the feedforward control in reducing the rotor speed and power fluctuations and the IPC in reducing the blade loads in previous studies, composite control algorithms based on the classical control methods proposed in the literature have primarily focused on reducing the platform motion or tower loads. Additionally, the effect of changes in control parameters on the performance of power production, load reduction, and motion reduction has not been sufficiently addressed. Therefore, the objectives of this study are to develop an optimal controller based on the classical control method that incorporates feedforward, IPC, peak shaving, and nacelle feedback to achieve all the control goals--power production, load reduction, and motion reduction--of the target FOWT. A performance comparison is then conducted according to the control parameters. By achieving control objectives for FONTs, such as power production, load reduction, and motion mitigation, it is expected that operational and maintenance costs for the target FOWT will decrease, the lifespan of critical components will extend, and the levelized cost of energy (LCoE) could be reduced. Analogously, [PERSON] et al. demonstrated that the integration of advanced technologies can improve energy efficiency and sustainability while evaluating the viability of microturbines in water networks [19]. The structure of the paper is as follows. Section 2 provides an overview of the target floating wind turbine. Section 3 describes the proposed composite control algorithm. Section 4 analyzes the results of the parametric study. Section 5 discusses control techniques that can be further considered for the target floating wind turbine. Section 6 wraps up the study.