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Sensitivity Analysis for Nonlinear Programming in CasADi

J A E Andersson (jandersson***at***wisc.edu)
J B Rawlings (james.rawlings***at***wisc.edu)

Abstract: We present an extension of the CasADi numerical optimization framework that allows arbitrary order NLP sensitivities to be calculated automatically and efficiently. The approach, which can be used together with any NLP solver available in CasADi, is based on a sparse QR factorization and an implementation of a primal-dual active set method. The whole toolchain is freely available as open-source software and allows generation of thread-safe, self- contained C code with small memory footprint. We illustrate the toolchain using three examples; a sparse QP, an optimal control problem and a parameter estimation problem.

Keywords: NLP, sensitivity, active set methods, code generation, algorithmic differentiation

Category 1: Optimization Software and Modeling Systems (Modeling Languages and Systems )

Category 2: Nonlinear Optimization (Quadratic Programming )

Citation: In Proc. 6th IFAC Conf. on Nonlinear Model Predictive Control (2018)

Download: [PDF]

Entry Submitted: 05/30/2018
Entry Accepted: 05/30/2018
Entry Last Modified: 07/18/2018

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