Control Applications of Reduced SQP Methods
Reduced Successive Quadratic Programming (SQP) methods have been applied to various areas in optimization. In this paper we consider mainly applications from optimal control and neighboring areas. The convergence analysis in Hilbert spaces is reviewed and the main ingredients are filtered out for the design of reduced SQP methods. As applications we chose examples from control and parameter identification with partial differential equations, process optimization in chemical engineering, and aerodynamic shape optimization.
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