On changing the spaces in Lagrange multiplier rules for the optimal control of non-linear operator equations

In this paper it is shown, how Lagrange multiplier rules for nonlinear optimal control problems in Banach spaces can be transferred by a simple device from the initial space to a more useful Banach space, in order to avoid unhandy dual spaces. The method is applied to state-equations of the type x-K(x,u)= 0, where the Fréchet-derivative of K has a certain smoothing property which is typical for integral operators.     

A short proof of a general multiplier rule

A general multiplier rule obtained by Hestenes is shown to follow directly from the Lagrange multiplier rule by a simple compactness argument. A similar simplification is effected in the proof of Gittleman's extension of Hestenes' rule.     

The infinite dimensional Lagrange multiplier rule for convex optimization problems

In this paper an infinite dimensional generalized Lagrange multipliers rule for convex optimization problems is presented and necessary and sufficient optimality conditions are given in order to guarantee the strong duality. Furthermore, an application is presented, in particular the existence of Lagrange multipliers associated to the bi-obstacle problem is obtained.     

Optimal control problems for distributed parameter systems in Banach spaces

We consider the infinite-dimensional nonlinear programming problem of minimizing a real-valued functionf ₀ (u) defined in a metric spaceV subject to the constraintf(u) Y, wheref(u) is defined inV and takes values in a Banach spaceE and Y is a subset ofE. We derive and use a theorem of Kuhn-Tucker type to obtain Pontryagin's maximum principle for certain semilinear parabolic distributed parameter systems. The results apply to systems described by nonlinear heat equations and reaction-diffusion equations inL ¹ andL spaces.This work was supported in part by the National Science Foundation under Grant DMS-9001793.     

Optimal control problems with applications to the elimination of substrate diffusing and convecting through immobilized enzyme

Some optimization problems concerning a substrate in a fluid are considered. The concentration of the substrate is affected by diffusion, convection, and elimination by enzymes, and the problem is to find the optimal distribution of enzymes. In this paper, the rate of elimination and the transmission coefficient are optimized. Mathematically, these problems are optimal control problems, and they are analyzed by means of Pontryagin's maximum principle.     

A lagrange multiplier theorem for control problems with state constraints

We prove an existence theorem of Lagrange multipliers for an abstract control problem in Banach spaces. This theorem may be applied to obtain optimality conditions for control problems governed by partial differential equations in the presence of pointwise state constraints.     

Nonzero lagrange multipliers

Solutions of constrained minimization problems give rise to Lagrange multiplier rules. In this paper, we show that a simple condition on a specific constraint implies that the associated coefficient in the Lagrange multiplier rule is not zero. We conclude with an example which shows that such knowledge increases the information available about the solution of a problem of minimal curvature.This work supported in part by NSF Grant No. MCS-75-05581-A01.     

An optimal control problem in the study of liver kinetics

The enzyme activities in the liver are described by a system of ordinary differential equations. A certain substance in the blood is transformed twice by different kinds of enzymes. The mathematical problem is to determine the distribution of the enzymes along the blood flow so that the outflow concentration of the once-transformed form of the substance is as small as possible. This problem has been considered before and solved for particular types of enzyme kinetics. In this paper, we solve the problem for more general types of kinetics (including substrate- inhibition kinetics). The methods used are also different, in that the problem is considered as a problem of optimal control and Pontryagin's maximum principle is applied to derive necessary conditions.     

A maximum principle for optimal control problems with mixed constraints

Necessary conditions in the form of maximum principles are derivedfor optimal control problems with mixed control and state constraints.Traditionally, necessary condtions for problems with mixed constraintshave been proved under hypothesis which include the requirementthat the Jacobian of the mixed constraint functional, with respectto the control variable, have full rank. We show that it canbe replaced by a weaker ‘interiority’ hypothesis.This refinement broadens the scope of the optimality conditions,to cover some optimal control problems involving differentialalgebraic constraints, with index greater than unity.     

A proof of a general maximum principle for optimal controls via a multiplier rule on metric space

A unified proof is given of the maximum principle for optimal control with various kinds of constraints by using a multiplier rule on metric spaces.     

Simple proof of the Lagrange multiplier rule for the fixed endpoint problem in the calculus of variations

A new simple proof of the Lagrange multiplier rule is presented in this paper. The approach used involves simple analytical techniques that are very easy to follow and does not involve theorems on imbeddability in a one-parameter family of curves or matrix-rank analysis as do most of the existing techniques. The proof is here developed for the fixed-endpoint problem in a three-dimensional space.     

A new method for calculating general lagrange multiplier in the variational iteration method

In this article, a reliable technique for calculating general Lagrange multiplier operator is suggested. The new algorithm, which is based on the calculus of variations, offers a simple method for calculation of general Lagrange multiplier for all forms. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 27: 996–1001, 2011     

A Lagrange multiplier rule with small convex-valued subdifferentials for nonsmooth problems of mathematical programming involving equality and nonfunctional constraints

It is shown that a Lagrange multiplier rule involving the Michel-Penot subdifferentials is valid for the problem: minimizef ₀(x) subject tof _i (x) 0,i = 1, ,m;f _i (x) = 0,i = m + 1,,n;x Q where all functionsf are Lipschitz continuous andQ is a closed convex set. The proof is based on the theory of fans.     

A combination of penalty function and multiplier methods for solving optimal control problems

The properties of combined multiplier and penalty function methods are investigated using a second-order expansion and results known for the Riccati equation. It is shown that the lower bound of the values of the penalty constant necessary to obtain a minimum is given by a certain Riccati equation. The convergence rate of a common updating rule for the multipliers is shown to be linear.This work has been supported by the Swedish Institute of Applied Mathematics.     

A general multiplier rule

An extension of a general multiplier rule derived by Gittleman, which in turn is an extension of a theorem due to Hestenes, is proved. The extension requires a less complicated definition of derived set.     

Second-order optimality principle for singular optimal control problems

A new necessary condition for singular optimal control problems is presented in this paper. The condition is simpler to apply than existing conditions and is easily derived from a Taylor series expansion of the performance index.     

Maximum principle and second-order conditions for minimax problems of optimal control

In this paper, we study the optimal control problem of minimizing the functionalJ(x, u)=max_t1tt2(x(t),t). We formulate and prove necessary optimality conditions for this problem. We establish the equivalence between the initial minimax problem and a problem involving a terminal functional and phase constraints.     

Lagrange multiplier rules for extremals in linear spaces

The aim of this paper is to formulate extremals in real, linear spaces, and to derive necessary conditions in the form of Lagrange multiplier rules for the extremals. Using a separation of intrinsic cores in real, linear spaces, the multiplier rules are proved under some conditions.The author wishes to thank the referee for a number of valuable suggestions, particularly the proof of Theorem 3.1.     

A maximum principle for smooth optimal impulsive control problems with multipoint state constraints

A nonlinear optimal impulsive control problem with trajectories of bounded variation subject to intermediate state constraints at a finite number on nonfixed instants of time is considered. Features of this problem are discussed from the viewpoint of the extension of the classical optimal control problem with the corresponding state constraints. A necessary optimality condition is formulated in the form of a smooth maximum principle; thorough comments are given, a short proof is presented, and examples are discussed.