Adaptive Sliding Mode Control for a Double Fed Induction Generator Used in an Oscillating Water Column System

Abstract

Wave power conversion systems are nonlinear dynamical systems that must endure strong uncertainties. Efficiency is a key issue for these systems, and the application of robust control algorithms can improve it considerably. Wave power generation plants are typically built using variable speed generators, such as the doubly fed induction generator (DFIG). These generators, compared with fixed speed generators, are very versatile since the turbine speed may be adjusted to improve the efficiency of the whole system. Nevertheless, a suitable speed controller is required for these systems, which must be able to avoid the stalling phenomenon and track the optimal reference for the turbine. This paper proposes a sliding mode control scheme aimed at oscillating water column (OWC) generation plants using Wells turbines and DFIGs. The contributions of the paper are (1) an adaptive sliding mode control scheme that does not require calculating the bounds of the system uncertainties, (2) a Lyapunov analysis of stability for the control algorithm against system uncertainties and disturbances, and (3) a validation of the proposed control scheme through several simulation examples with the Matlab/Simulink suite. The performance results, obtained by means of simulations, for a wave power generation plant (1) evidence that this control scheme improves the power generation of the system and (2) prove that this control scheme is robust in the presence of disturbances.

Optimal wave energy extraction for oscillating water columns using second‐order sliding mode control

“…To test the controllers under practical conditions, the simulations are conducted utilising the full order model of the OWC system (8)- (12), incorporating uncertainties up to 15% with respect to the electrical and aerodynamic parameters. The parameters of the Wells turbine, chamber and the 7.5 kW DFIG generator are shown in Table 1.…”

“…In [10] and, more recently, in [7,11], researchers have obtained very good results to increase wave energy extraction by regulating the rotational speed, computing the reference speed to avoid turbine stall. Another interesting approach has been introduced in [5,12], where energy extraction enhancement is successfully achieved by operating at the flow coefficient of maximum turbine efficiency, which results in variable rotational speed operation. Then, the novel criterion developed in this paper naturally arises as a continuation of the aforementioned contributions, focusing on maximising the wave energy extraction, by considering the mechanical system as a whole.…”

Sliding Mode-Based Robust Control for Piezoelectric Actuators with Inverse Dynamics Estimation

“…In the experiments, the values for the controllers' parameters were experimentally tuned, taking into account the influence of these parameters in the controller performance. In the selection of these parameters, the following rules should be taken into account [24]. An increase in parameter η results in an increase in the absolute value of the control signal, but also increases the oscillation of the signal.…”

“…Reducing η made the amplitude in the chattering smaller, as seen with η = 3, but it was still present. However, reducing η too much (η = 0.2) will end up making the control signal insufficient, resulting in a worse system response, as seen when the reference changes, with a reduction in the compensation of uncertainties [24][25][26].…”

Special Issue “Offshore Renewable Energy: Ocean Waves, Tides and Offshore Wind”

“…This paper established a relationship between the interference effect and electric powers from wave energy converters. A sliding mode control scheme aimed at oscillating water column (OWC) generation plants using Wells turbines and DFIGs (Doubly Fed Induction Generators) was proposed in [12]. The papers discussed an adaptive sliding mode control scheme that does not require calculating the bounds of the system uncertainties, a Lyapunov analysis of stability for the control algorithm against system uncertainties and disturbances, and a validation of the proposed control scheme through numerical simulations.…”