Fault-tolerant optimal pitch control of wind turbines using dynamic weighted parallel firefly algorithm.

With steadily increasing interest in utilizing wind turbine (WT) systems as primary electrical energy generators, fault-tolerance has been considered decisive to enhance their efficiency and reliability. In this work, an optimal fault-tolerant pitch control (FTPC) strategy is addressed to adjust the pitch angle of WT blades in the presence of sensor, actuator, and system faults. The proposed scheme incorporates a fractional-calculus based extended memory (EM) of pitch angles along with a fractional-order proportional-integral-derivative (FOPID) controller to enhance the performance of the WT. A dynamic weighted parallel firefly algorithm (DWPFA) is also proposed to tune the controller parameters. The efficiency of the proposed algorithm is evaluated on the test functions adopted from 2017 IEEE congress on evolutionary computation (CEC2017). The merits of the proposed fault-tolerant approach are tested on a 4.8-MW WT benchmark model and compared to conventional PI and optimal FOPID approaches. Corresponding comparative simulation results validate the effectiveness and fault-tolerant capability of the proposed control paradigm, where it is observed that the proposed control scheme tends to be more consistent in the power generated at a given wind speed.

Robust adaptive fractional-order nonsingular terminal sliding mode stabilization of three-axis gimbal platforms.

This paper proposes an adaptive fractional-order nonsingular terminal sliding mode (AFNTSMC) control scheme combined with the independent joint control approach for trajectory tracking of three-axis gimbal platforms (GPs) mounted on a moving vehicle subjected to external disturbances. To achieve accurate images taken by the camera mounted on the GP, the motions and vibrations of the vehicle must be isolated from the camera. Thus, precise mathematical modeling of a three-axis GP with considering the external disturbances is studied, such that the GP tracks the target accurately and holds the line of sight stationary. Various tests with different vehicle conditions are performed to collect the movement data to be considered as the desired input for the GP. Thanks to the utilization of AFNTSMC, fast convergence together with simultaneous accurate trajectory tracking and strong robustness can be ensured. Corresponding comparative simulation results validate the effectiveness of the theoretical design results and superiorities of the proposed method over the existing methods.