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35	Use of Quadratic Programming to Design Multivariable Controllers (Model Predictive Control) Targets (set points) selected by real-time optimization software based on current operating and economic conditions Minimize square of deviations between predicted future outputs and specific reference trajectory to new targets using QP Framework handles multiple input, multiple output (MIMO) control problems with constraints on manipulated and controlled variables. Dynamics obtained from transfer function model.
36	Successive Quadratic Programming Considered by some to be the best general nonlinear programming algorithm Repetitively approximates nonlinear objective function with quadratic function and nonlinear constraints with linear constraints Uses line search rather than QP step for each iteration Inequality constrained Quadratic Programming (IQP) keeps all inequality constraints Equality constrained Quadratic Programming (EQP) only keeps equality constraints by utilizing and active set strategy SQP is an Infeasible Path method
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