Nonlinear Equality Constraints in Feasible Sequential Quadratic Programming

dc.contributor.authorLawrence, Craig T.en_US
dc.contributor.authorTits, A.L.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:58:22Z
dc.date.available2007-05-23T09:58:22Z
dc.date.issued1995en_US
dc.description.abstractA simple scheme is proposed for handling nonlinear equality constraints in the context of a previously introduced sequential quadratic programming (SQP) algorithm for inequality constrained problems, generating iterates satisfying all constraints. The key is an idea due to Mayne and Polak (Math. progr., vol. 11, pp 67- 80, 1976) by which nonlinear equality constraints are treated as ﳣﱠtype constraints to be satisfied by all iterates, thus precluding any positive value, and an exact penalty term is added to the objective function which penalizes negative values. Mayne and Polak obtain a suitable value of the penalty parameter by iterative adjustments based on a test involving estimates of the KKT multipliers. We argue that the SQP framework allows for a more effective estimation of these multipliers, and we provide convergence analysis of the resulting algorithms. Numerical results, obtained with the FSQP/CFSQP code, are reported.en_US
dc.format.extent732259 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5597
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1995-2en_US
dc.subjectconstrained optimizationen_US
dc.subjectnonlinear equality constraintsen_US
dc.subjectsequential quadratic programmingen_US
dc.subjectfeasibilityen_US
dc.subjectIntelligent Control Systemsen_US
dc.titleNonlinear Equality Constraints in Feasible Sequential Quadratic Programmingen_US
dc.typeTechnical Reporten_US

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