Euler Discretization and Inexact Restoration for Optimal Control

Abstract A computational technique for unconstrained optimal control problems is presented. First, an Euler discretization is carried out to obtain a finite-dimensional approximation of the continuous-time (infinite-dimensional) problem. Then, an inexact restoration (IR) method due to Birgin and Martínez is applied to the discretized problem to find an approximate solution. Convergence of the technique to a solution of the continuous-time problem is facilitated by the convergence of the IR method and the convergence of the discrete (approximate) solution as finer subdivisions are taken. The technique is numerically demonstrated by means of a problem involving the van der Pol system; comprehensive comparisons are made with the Newton and projected Newton methods.

[1]  J. B. Rosen The Gradient Projection Method for Nonlinear Programming. Part I. Linear Constraints , 1960 .

[2]  J. B. Rosen The gradient projection method for nonlinear programming: Part II , 1961 .

[3]  M. Hestenes Calculus of variations and optimal control theory , 1966 .

[4]  J. C. Heideman,et al.  Sequential gradient-restoration algorithm for the minimization of constrained functions—Ordinary and conjugate gradient versions , 1969 .

[5]  A. V. Levy,et al.  Modifications and extensions of the conjugate gradient-restoration algorithm for mathematical programming problems , 1971 .

[6]  Michael R. Osborne,et al.  Numerical solution of boundary value problems for ordinary differential equations , 1995, Classics in applied mathematics.

[7]  W. Hager Rates of Convergence for Discrete Approximations to Unconstrained Control Problems , 1976 .

[8]  B.Sh. Mordukhovich On difference approximations of optimal control systems: PMM vol. 42, n≗ 3, 1978, pp. 43–440 , 1978 .

[9]  H. Sirisena,et al.  Convergence of the control parameterization Ritz method for nonlinear optimal control problems , 1979 .

[10]  Edward Michael Sims Sequential gradient-restoration algorithm for mathematical programming problems with inequality constraints , 1983 .

[11]  Arne Drud,et al.  CONOPT: A GRG code for large sparse dynamic nonlinear optimization problems , 1985, Math. Program..

[12]  Richard A. Tapia,et al.  The Projected Newton Method Has Order $1 + \sqrt 2 $ for the Symmetric Eigenvalue Problem , 1988 .

[13]  Eugene Isaacson,et al.  Numerical Solution of Boundary Value Problems for Ordinary Differential Equations (Uri M. Ascher, Robert M. M. Mattheij, and Robert D. Russell) , 1989, SIAM Rev..

[14]  Kok Lay Teo,et al.  A Unified Computational Approach to Optimal Control Problems , 1991 .

[15]  O. V. Stryk,et al.  Numerical Solution of Optimal Control Problems by Direct Collocation , 1993 .

[16]  P. Berck,et al.  Calculus of variations and optimal control theory , 1993 .

[17]  Robert D. Russell,et al.  Numerical solution of boundary value problems for ordinary differential equations , 1995, Classics in applied mathematics.

[18]  Asen L. Dontchev,et al.  An a priori Estimate for Discrete Approximations in Nonlinear Optimal Control , 1996 .

[19]  Vladimir M. Veliov,et al.  On the Time-Discretization of Control Systems , 1997 .

[20]  Rein Luus,et al.  Iterative dynamic programming , 2019, Iterative Dynamic Programming.

[21]  J. M. Martínez,et al.  Inexact-Restoration Algorithm for Constrained Optimization1 , 2000 .

[22]  William W. Hager,et al.  Runge-Kutta methods in optimal control and the transformed adjoint system , 2000, Numerische Mathematik.

[23]  William W. Hager,et al.  Uniform Convergence and Mesh Independence of Newton's Method for Discretized Variational Problems , 2000, SIAM J. Control. Optim..

[24]  Walter Alt Mesh-Independence of the Lagrange–Newton Method for Nonlinear Optimal Control Problems and their Discretizations , 2001, Ann. Oper. Res..

[25]  William W. Hager,et al.  The Euler approximation in state constrained optimal control , 2001, Math. Comput..

[26]  J. M. Martínez,et al.  Inexact-Restoration Method with Lagrangian Tangent Decrease and New Merit Function for Nonlinear Programming , 2001 .

[27]  J. Stoer,et al.  Introduction to Numerical Analysis , 2002 .

[28]  C. Kaya,et al.  Computational Method for Time-Optimal Switching Control , 2003 .

[29]  Helmut Maurer,et al.  Second Order Sufficient Conditions for Time-Optimal Bang-Bang Control , 2003, SIAM J. Control. Optim..

[30]  C. Kaya,et al.  Computations for bang–bang constrained optimal control using a mathematical programming formulation , 2004 .

[31]  J. M. Martínez,et al.  Local Convergence of an Inexact-Restoration Method and Numerical Experiments , 2005 .

[32]  C. Yalçin Kaya,et al.  Leapfrog for Optimal Control , 2008, SIAM J. Numer. Anal..