Keywords

Wind Turbines, Multivariable Control, Fatigue loads, Individual Pitch Control, Genetic algorithm Optimization, Control system Design

Abstract

This dissertation investigates advanced control strategies to improve performance and reduce fatigue loads in both land-based and floating offshore wind turbines. The proposed approaches target fatigue load mitigation at critical component frequencies while ensuring rotor speed regulation and efficient power generation. The control strategies are implemented and validated using both our in-house modeling and simulation platform, CRAFTS (Control Oriented Reconfigurable Acausal Floating Turbine Simulator), and the industry-standard OpenFAST model.

For land-based turbines, torque actuation and collective blade pitch control are incorporated into a nonlinear controller for rotor speed regulation and power generation. To address fatigue load reduction, individual pitch control (IPC) is employed. Since fatigue loads across turbine components are strongly coupled—where reducing one load can amplify another—a multivariable control framework based on relative gain array (RGA) analysis is developed. This framework determines optimal actuator orientations and input–output pairings, enabling simultaneous mitigation of multiple loads.

The nonlinear controller is further extended to floating offshore wind turbines, where additional platform degrees of freedom introduce new stability and performance challenges. A dynamic IPC allocation strategy within the multivariable control framework is designed to reduce platform motions and fatigue loads while maintaining rotor speed regulation.

Extensive simulations demonstrate that the proposed multivariable control framework with dynamically allocated IPC significantly reduces fatigue loads in land-based turbines and both fatigue loads and platform motions in floating offshore turbines. Importantly, these improvements are achieved without compromising the primary objectives of rotor speed regulation and power generation.

Completion Date

2025

Semester

Fall

Committee Chair

Tuhin Das

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Mechanical and Aerospace Engineering

Format

PDF

Identifier

DP0029715

Document Type

Thesis

Campus Location

Orlando (Main) Campus

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