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This dissertation presents a Nonlinear Model Predictive Control (NMPC) framework utilizing quasi-Linear Parameter Varying (quasi-LPV) models to enhance online nonlinear optimization efficiency and establish less conservative stability conditions. The approach allows for the effective handling of input constraints in fast nonlinear systems, making it comparable in complexity to linear MPC. Additionally, it introduces a velocity algorithm for NMPC, simplifying design and implementation while maintaining stabi

Author

Harsh Pandey

Language

EN