First order control for low-thrust interplanetary vehicles
First order control for low thrust interplanetary vehicles based on calculus of variations and Weierstrass E-function
FIRST ORDER EQUATION↗
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Necessary conditions for a multistage bolza- mayer problem involving control variables and having inequality and finite equation constraints
A multiplier rule and analogues of the Weierstrass and Clebsch conditions are developed for a multistage Bolza-Meyer calculus of variations problems. The number of stages is fixed, but partition points defining state boundaries are variable. Discontinuities are allowed in variables finite equations and inequalities, as well as differential equations, all of which involve control variables. An appendix summarizes some of the results obtained by C. H. Denbow, as modified by R. W. hunt, for a generalized Bolza problem. The appendix is independent of the rest of the paper.
Differential equation↗
The latent variable proximal point algorithm for variational problems with inequality constraints
The latent variable proximal point (LVPP) algorithm is a framework for solving infinite-dimensional variational problems with pointwise inequality constraints. The algorithm is a saddle point reformulation of the Bregman proximal point algorithm. At the continuous level, the two formulations are equivalent, but the saddle point formulation is more amenable to discretization because it introduces a structure-preserving transformation between a latent function space and the feasible set. Working in this latent space is much more convenient for enforcing inequality constraints than the feasible set, as discretizations can employ general linear combinations of suitable basis functions, and nonlinear solvers can involve general additive updates. LVPP yields numerical methods with observed mesh-independence for obstacle problems, contact, fracture, plasticity, and others besides; in many cases, for the first time. The framework also extends to more complex constraints, providing means to enforce convexity in the Monge–Ampère equation and handling quasi-variational inequalities, where the underlying constraint depends implicitly on the unknown solution. Here, in this paper, we describe the LVPP algorithm in a general form and apply it to ten problems from across mathematics.
Inequality constraints↗