This paper investigates the effects power oscillation damping (POD) controller could have on a wind turbine structural system. Most of the published work in this area has been done using relatively simple aerodynamic and structural models of a wind turbine which cannot be used to investigate the detailed interactions between electrical and mechanical components of the wind turbine. Therefore, a detailed model that combines electrical, structural and aerodynamic characteristics of a grid-connected Doubly Fed Induction Generator (DFIG) based wind turbine has been developed by adapting the NREL (National Renewable Energy Laboratory) 5 MW wind turbine model within FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code. This detailed model is used to evaluate the effects of POD controller on the wind turbine system. The results appear to indicate that the effects of POD control on the WT structural system are comparable or less significant as those caused by wind speed variations. Furthermore, the results also reveal that the effects of a transient three-phase short circuit fault on the WT structural system are much larger than those caused by the POD controller.

To overcome the adverse effects of time-varying parametric uncertainties and strong disturbances in aircraft antiskid braking systems (ABS), achieving efficient antiskid braking control and shortening the braking distance. This article proposes a modified super-twisting sliding mode control (MSSMC)-based aircraft ABS controller with gain adaptive schedule and disturbance compensation. In this article, MSSMC is obtained by substituting the discontinuous term in the conventional super-twisting sliding mode control (SSMC) with a continuous fractional power term, which can alleviate the chattering and improve the tracking performance. The developed controller is derived by effectively integrating MSSMC, extended state observer (ESO) and gain adaptive techniques, preserving the advantages of these approaches while effectively overcoming their practical performance limitations. The time-varying disturbances and unmodeled dynamics in aircraft ABS are estimated by ESO and compensated in a feedforward way, which significantly decreases the residual uncertainties handled by the MSSMC, thus alleviating the burden on the MSSMC and avoiding the high-gain feedback. In addition, a novel gain adaptive protocol for MSSMC is proposed, which can minimize the control gain and the chattering amplitude without the prerequisite of uncertain upper boundary required for conventional SSMC. Theoretical analysis based on the Lyapunov approach shows that the designed ABS controller ensures that the sliding variable converges to the desired accuracy near the origin in a finite time. Comparative experimental results demonstrate the effectiveness of the proposed approach.

We investigate the aeroelastic and trajectory control of an High Altitude Long Endurance (HALE) aircraft model in the presence of gust and turbulence disturbances. The model is derived from geometrically-nonlinear beam theory using intrinsic degrees of freedom and linear unsteady aerodynamics, which results in a coupled structural dynamics, aerodynamics and flight dynamics description. The control design employs a two-loop PI/LADRC (linear active disturbance rejection control) and H$\infin$ control scheme in both the longitudinal and lateral channels, based on a reduced-order linearised model. In each channel, the outer loop (position control) employs a PI/LADRC technique to track the desired flight routes and generate attitude command to the inner loop, while the inner loop (attitude control) uses H$\infin$ control to track the attitude command generated from the outer loop and computes the control inputs to the corresponding control surfaces. A Particle Swarm Optimization algorithm is employed for parameter optimization of the weighting matrices in the H$\infin$ control design. The simulation tests conducted on the full-order nonlinear model show that the aeroelastic and trajectory control system achieves good performance with respect to robustness, trajectory tracking and disturbance rejection

This paper aims to handle the optimal attitude tracking control tasks for rigid bodies via a reinforcement learning-based control scheme, in which a constrained parameter estimator is designed to compensate system uncertainties accurately. This estimator guarantees the exponential convergence of estimation errors and can strictly keep all instant estimates always within pre-determined bounds. Based on it, a critic-only adaptive dynamic programming (ADP) control strategy is proposed to learn the optimal control policy with respect to a user-defined cost function. The matching condition on reference control signals, which is commonly employed in relevant ADP design, is not required in the proposed control scheme. We prove the uniform ultimate boundedness of the tracking errors and critic weight's estimation errors under finite excitation conditions by Lyapunov-based analysis. Moreover, an easy-to-implement initial control policy is designed to trigger the real-time learning process. The effectiveness and advantages of the proposed method are verified by both numerical simulations and hardware-in-loop experimental tests.