Self-tuning proportional-derivative pitch control for internal fault-tolerance in wind turbine benchmark

Abstract

ABSTRACT The wind turbine (WT) dynamics are affected by wind variations and system parameter changes as well. To deal with the pitch control problem a Self-Tuning Controller (STC) with Proportional-Derivative (PD) structure has been proposed for the benchmark model (BM). This BM also models some sensors, actuators and system faults. The STC design herein is pivoted on a second-order auto-regressive exogenous (ARX) model. At first, three identification methods for the ARX model are presented: Recursive Least Square method (RLS), RLS with exponential forgetting (RLS-EF) and RLS with adaptive directional forgetting (RLS-ADF). In comparison, the performance of RLS-ADF is better than the rest two. The STC PD controller supersedes contemporary adaptive control approaches to fix up the generated power to its rating for above-rated wind. Secondly, on analysis, the proposed STC PD controller is fault-tolerant for nine types of faults. In the third stage, in extensive Monte Carlo Simulation (MCS), the sensitivity test to system parameter variation is carried out including the sensor faults. The result in the presence of a fault, as well as parameter variation, shows minimal deviation from normal conditions indicating the suitability of the STC PD controller to keep the system intact except in case of multiple faults.