Qinmin Yang’s research while affiliated with Zhejiang University and other places

Floating wind turbines (FWTs) hold significant potential for the exploitation of offshore renewable energy resources. Nevertheless, prior to the construction of FWTs, it is imperative to tackle several critical challenges, especially the issue of performance degradation under combined wind and wave loads. This study initiates with the development of a simplified nonlinear dynamical model for a semi-submersible FWT. In particular, both the rotor dynamics and the finite rotations of the platform are considered in presented modeling approach, thereby effectively capturing the complex interplay between the platform, tower, nacelle, and rotor under combined wind and wave loads. Subsequently, based on the developed FWT model, a novel adaptive nonlinear pitch controller is formulated with the goal of striking a trade-off between regulating power generation and reducing platform motion. Notably, the proposed control strategy adopts a continuous control approach, strategically beneficial in circumventing the chattering phenomenon commonly associated with sliding mode control. Furthermore, the controller integrates an online approximator and a robust integral of the sign of the tracking error, facilitating real-time learning of system unknown dynamics while compensating for bounded disturbances. Finally, both the accuracy of the established nonlinear FWT model in predicting key dynamics and the superiority of the presented pitch controller are validated through comprehensive comparative studies.

This paper concentrates on the resilient control issue in multi-agent systems (MASs) with the time-varying delay subjected to denial of service (DoS) attacks. To eliminate the impact of DoS attacks, a novel resilient control framework is constructed for MASs, where a variable following the Bernoulli distribution process is utilized to denote the behaviors of the attacker. Besides, we design a novel reduced-order (RO) observer with internal time-varying delay to estimate the unknown output of the system and compensate for lost data in the channels. Different from the general observers, the designed observer can ensure both the reduced-order observation errors and the full-order ones can converge to zero. Furthermore, an RO observer-based distributed protocol is devised such that the consensus errors of the closed-loop systems asymptotically converge to zero. Simulation comparisons are provided to validate the efficiency and superiority of our approach.

Blade pitch actuators for traditional onshore wind turbines primarily serve the purposes of regulating generated power to the rated value in high wind speed regions. Yet, when considering the floating offshore wind turbines (FOWTs) subject to wind and wave disturbances, it can be observed that improving power regulation often comes at the expense of exacerbating motion in the floating platform, leading to elevated platform loads. To address this issue, this paper proposes a novel robust nonlinear pitch controller specifically designed to achieve power production regulation while simultaneously mitigating platform pitch motion for FOWTs. Moreover, to tackle the challenge posed by unknown dynamics under wind-wave joint loads, the presented controller integrates a two-layer neural network (NN) for real-time learning of these unknown system dynamics. Meanwhile, a robust continuous term is introduced to alleviate the effects of residual reconstruction errors from the NN and external disturbances. Finally, the viability and efficacy of the proposed scheme are clearly demonstrated through comprehensive comparative studies with traditional pitch controllers conducted on the National Renewable Energy Laboratory (NREL) FAST platform. Note to Practitioners —This paper is motivated by the challenge of achieving the competing objectives between power regulation and load mitigation for floating offshore wind turbines (FOWTs) in high speed region. FOWTs have garnered significant interest in the field of renewable energy due to their advantages, including the ability to install high-powered wind turbines and reduced costs in deeper waters. However, there exist some limitations that existing FOWT controllers face including inefficiency in directly applying onshore WT control schemes, typically depend on precise turbine models and lack adaptability to potential uncertainties and errors encountered in practical situations. To tackle these limitations, this paper proposes a novel robust nonlinear controller for FOWTs considering the platform motion, which has the ability to simultaneously achieve power production regulation while platform stabilization. A two-layer neural network for real-time learning is developed to capture potential changes in system dynamics, while a robust continuous term is introduced to alleviate potential errors in the control scheme. This naturally provides adaptability and robustness against uncertainties while enhancing overall control performance. The effectiveness of the proposed control scheme is validated through simulation results.

Control of turbo‐generator is facing great challenges resulting from more renewable energies injected into power systems, and it is still a challenging task to improve the accuracy and convergence speed when the operation point changes. In this paper, an adaptive finite‐time controller design is proposed for turbo‐generators in the presence of bounded disturbances and unknown system dynamics. Compared with existing methods, the finite‐time stability rather than asymptotic stability or uniformly ultimately bounded (UUB) can be guaranteed and prescribed transient performance can be achieved. First, the constant constraints on the system states and terminal sliding mode (TSM) manifold are proposed to enhance the transient performance. Furthermore, the uncertainties of the system are overcome by the neural network (NN), and both the bounded external disturbances and the reconstruction error of NN are handled by an adaptive term and a robust term. In addition, the important chattering‐free property could be achieved by the boundary layer. Finally, the finite‐time stability of the output in the system is rigidly proved via Lyapunov analysis, and the effectiveness of the theoretical result is substantiated by extensive simulations.