{"id":{"repo_id":"calgary","oai_identifier":"oai:ucalgary.scholaris.ca:1880/116930"},"canonical_url":"https://search.dev.ndltd.org/etd/calgary/oai:ucalgary.scholaris.ca:1880/116930","repository":{"repo_id":"calgary","name":"University of Calgary","base_url":"https://ucalgary.scholaris.ca/server/oai/request"},"display":{"title":"First Order Dynamic Sliding Mode Control of a Wind Turbine with Optimized Tip Speed Ratio","abstract":"This thesis explores a novel sliding mode control method to boost power from wind turbines, focusing on the power optimization region. The controller, designed for a 3rd-order system with generator torque input and rotor torque disturbance, is tested using a simple wind turbine model and FAST for validation. The first objective is to identify the optimal tip-speed-ratio (TSR) for maximum power using the Recursive Least Squares (RLS) method. The RLS generates a polynomial connecting the TSR and power coefficient, defining the wind turbine's operating point. A forgetting factor is incorporated in the RLS method for system adaptability to changing conditions. The other objective utilizes a first-order dynamic sliding mode controller with integration (FODSMCI) to control the wind turbine, keeping it at the optimal TSR for maximum power without chattering. The study revealed the RLS's effectiveness in determining optimal TSR on wind turbine models. The FODSMCI enables a balance between controller performance and rotor speed tracking, yielding a chatter-free response.","abstract_html":"This thesis explores a novel sliding mode control method to boost power from wind turbines, focusing on the power optimization region. The controller, designed for a 3rd-order system with generator torque input and rotor torque disturbance, is tested using a simple wind turbine model and FAST for validation. The first objective is to identify the optimal tip-speed-ratio (TSR) for maximum power using the Recursive Least Squares (RLS) method. The RLS generates a polynomial connecting the TSR and power coefficient, defining the wind turbine's operating point. A forgetting factor is incorporated in the RLS method for system adaptability to changing conditions. The other objective utilizes a first-order dynamic sliding mode controller with integration (FODSMCI) to control the wind turbine, keeping it at the optimal TSR for maximum power without chattering. The study revealed the RLS's effectiveness in determining optimal TSR on wind turbine models. The FODSMCI enables a balance between controller performance and rotor speed tracking, yielding a chatter-free response.","abstract_has_math":false,"creators":["Padmanabhuni, Nishanth"],"institution":"Graduate Studies","degree_name":"Master of Science (MSc)","degree_level":null,"degree_discipline":"Engineering – Mechanical & Manufacturing","degree_department":null,"school":null,"contributors":[],"advisors":["Pieper, Jeff"],"committee_chairs":[],"committee_members":["Simon li, Ignacio Galiano Zurbriggen"],"year":2023,"date_issued":"2023-08-31","date_published":"2023-08-31","updated_at":"2026-07-24T01:30:36Z","subjects":["Wind turbines","Renewable energy","Robust Control"],"languages":["en"],"rights":["University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. 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The first objective is to identify the optimal tip-speed-ratio (TSR) for maximum power using the Recursive Least Squares (RLS) method. The RLS generates a polynomial connecting the TSR and power coefficient, defining the wind turbine's operating point. A forgetting factor is incorporated in the RLS method for system adaptability to changing conditions. The other objective utilizes a first-order dynamic sliding mode controller with integration (FODSMCI) to control the wind turbine, keeping it at the optimal TSR for maximum power without chattering. The study revealed the RLS's effectiveness in determining optimal TSR on wind turbine models. 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