{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/17753"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/17753","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Model predictive control with application to real-time hardware and guided parafoil","abstract":"Model Predictive Control (MPC) is a control strategy that is suitable for optimizing the performance of constrained systems. Constraints are present in all control systems due to the physical and environmental limits on plant operation. Through a systematical handling of constraints, MPC can improve the performance of a system by allowing it to safely operate near constraint boundaries. This thesis describes the mathematical background of MPC and develops two controllers. One controller is based on a linear model of the plant and is successfully applied to a real-time 3 degrees-of-freedom helicopter system, used to simulate helicopter-like motions in a laboratory setting. This system has a number of significant state and control constraints. The second controller uses a nonlinear model and is applied to a guided parafoil to identify the advantage of using a Doppler wind sensor. A method for reducing the computational load is also introduced that is applicable to both controllers.","abstract_html":"Model Predictive Control (MPC) is a control strategy that is suitable for optimizing the performance of constrained systems. Constraints are present in all control systems due to the physical and environmental limits on plant operation. Through a systematical handling of constraints, MPC can improve the performance of a system by allowing it to safely operate near constraint boundaries. This thesis describes the mathematical background of MPC and develops two controllers. One controller is based on a linear model of the plant and is successfully applied to a real-time 3 degrees-of-freedom helicopter system, used to simulate helicopter-like motions in a laboratory setting. This system has a number of significant state and control constraints. The second controller uses a nonlinear model and is applied to a guided parafoil to identify the advantage of using a Doppler wind sensor. A method for reducing the computational load is also introduced that is applicable to both controllers.","abstract_has_math":false,"creators":["Alaniz, Abran, 1980-"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.","school":null,"contributors":[],"advisors":["David W. 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