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Model Predictive Control (MPC) refers to a class of algorithms that optimize the future behavior of the plant subject to operational constraints. The merits of the class algorithms include its ability to handle imposed hard constraints on the system and perform on-line optimization. This thesis investigates design and implementation of continuous time model predictive control using Laguerre polynomials and extends the design approaches proposed in to include intermittent predictive control, as well as to include the case of the nonlinear predictive control. |
