Dynamic sliding mode control of pitch blade wind turbine using sliding mode observer

Abstract

In a wind turbine (WT), the maximum power can be achieved using a suitable and smooth signal, which should be applied to the pitch angle of the blades (PABLE). On the contrary, the uncertainties of the WT models cause the fatigue due to the mechanical stresses. To overcome these two problems, dynamic sliding mode control (D-SMC) is used because it is robust against uncertainties and can suppress the chattering by providing smooth signals. In D-SMC, an integrator is located before the actuator, as a low-pass filter, to suppress the high-frequency chattering. Then, the states number of the overall augmented system is one more than the states number of the actual system. To control such an augmented system, the added state variable needs to be estimated and hence, a novel sliding mode observer (SMO) is proposed. A trusty comparison is also presented using the conventional sliding mode control (C-SMC) with the proposed SMO. To implement D-SMC and C-SMC, a new state feedback is applied to the turbine at first. Therefore, a linear model with uncertainty is obtained, where its input is the PABLE. Lyapunov theory is used to proof the stability of the proposed SMO, D-SMC, and also the C-SMC. The presented comparison demonstrates the advantages of the D-SMC with respect to the C-SMC in removing the chattering and simplicity in concept and in implementation.

Higher Order Sliding Mode Control of MIMO Induction Motors: A New Adaptive Approach

“…DSMC can remove the chattering completely using an integrator. The integrator would remove high switching without using a large gain [17]. But this approach needs Mathematics 2023, 11, 4558 2 of 16 an observer [17].…”

“…The integrator would remove high switching without using a large gain [17]. But this approach needs Mathematics 2023, 11, 4558 2 of 16 an observer [17]. HOSMC can remove chattering [18], because it transfers the switching to the higher order derivatives of the sliding surface or output [9,19,20].…”

Lateral Trajectory Tracking of Self-Driving Vehicles Based on Sliding Mode and Fractional-Order Proportional-Integral-Derivative Control

“…Various advanced control methods have been explored by researchers, and the sliding mode control (SMC) method is a control method that has been studied by many scholars and has been applied in many fields [19][20][21][22][23][24][25][26]. Since the SMC control method has the advantages of being a more robust, fast system response, and does not require an accurate model, many scholars have applied it to transverse controllers [27,28].…”