The post-optimality analysis of a tetrahedral formation flying optimal control problem is considered. In particular, this four-spacecraft orbit insertion problem is transcribed to a nonlinear programming problem (NLP) using a direct method called the Gauss pseudospectral method. The Karush-Kuhn-Tucker (KKT) conditions for this NLP are then derived and are compared to the conditions obtained via...

abstract background: the use of coping strategies in reducing the adverse effects of stress can be helpful. nero‑linguistic programming (nlp) is one of the modern methods of psychotherapy. this study aimed to determine the effect of nlp on occupational stress in nurses working in critical care units of urmia. materials and methods: this study was carried out quasi‑experimentally (before–after) ...

This work deals with the optimal synthesis of groundwater remediation networks for the valorization of anionic pollutants by means of emulsion pertraction technology using hollow fiber modules (HFM). Superstructures that incorporate all possible design alternatives are proposed. The aim of this work is to obtain a minimum cost groundwater remediation network that allows treatment of groundwater...

The use of small aerial vehicles (SAVs) such as quadrotors for inspection and surveillance applications both indoors and out is well established, but motion planning techniques are needed which can be calculated in real-time and which result in provably safe vehicle motion in tightly constrained 3D environments. Applied to small quadrotor helicopters, our planning algorithm combines Probabilist...

Abstract. Many nonconvex nonlinear programming (NLP) problems of practical interest involve bilinear terms and linear constraints, as well as, potentially, other convex and nonconvex terms and constraints. In such cases, it may be possible to augment the formulation with additional linear constraints (a subset of Reformulation-Linearization Technique constraints) which do not affect the feasibl...

In this paper, we discuss the solution of linear and quadratic eigenvalue complementarity problems (EiCPs) using an enumerative algorithm of the type introduced by Júdice et al. [1]. Procedures for computing the interval that contains all the eigenvalues of the linear EiCP are first presented. A nonlinear programming (NLP) model for the quadratic EiCP is formulated next, and a necessary and suf...

Recent road trials have shown that guaranteeing the safety of driving decisions is essential for wider adoption autonomous vehicle technology. One promising direction to pose requirements as planning constraints in nonlinear, nonconvex optimization problems motion synthesis. However, many implementations this approach are limited by uncertain convergence and local optimality solutions achieved,...

The optimal operation model of AC/DC distribution network with energy router (ER) is essentially a nonconvex nonlinear programming (NLP) problem. In order to improve the feasibility solving model, convex approximation algorithm proposed in this work. steady-state ER developed considering loss characteristics and multiport coordinated control strategy. It embedded optimization formulations as ba...

We present a moving horizon estimation (MHE) application for multi-zone low-density (LDPE) polyethylene tubular reactors. The strategy incorporates a first-principles dynamic model comprised of large sets of nonlinear partial, differential and algebraic equations (PDAEs). It was found that limited temperature measurements distributed along the reactor are sufficient to infer all the model state...

In this paper, we survey the most recent methods that have been developed for the solution of semidefinite programs. We first concentrate on the methods that have been primarily motivated by the interior point (IP) algorithms for linear programming, putting special emphasis in the class of primal-dual path-following algorithms. We also survey methods that have been developed for solving large-s...