dynopt is a set of MATLAB functions for determination of optimal control trajectory by given description of the process, the cost to be minimised, subject to equality and inequality constraints, using orthogonal collocation on finite elements method. The actual optimal control problem is solved by complete parametrisation both the control and the state profile vector. That is, the original continuous control and state profiles are approximated by a sequence of linear combinations of some basis functions. It is assumed that the basis functions are known and optimised are the coefficients of their linear combinations. In addition, each segment of the control sequence is defined on a time interval whose length itself may also be subject to optimisation. It is assumed, that the optimised dynamic model is described by a set of ordinary differential equations. This collection of functions extend the capability of the MATLAB Optimisation Toolbox, specifically of the constrained nonlinear minimisation routine fmincon.
author | = | {M. {\v{C}}i\v{z}niar and M. Fikar and M. A. Latifi}, |
title | = | {MATLAB Dynamic Optimisation Code DYNOPT. User's Guide}, |
year | = | {2006}, |
keyword | = | {dynamick\'a optimaliz\'acia, ortogon\'alna kolok\'acia}, |
organization | = | {KIRP FCHPT STU}, |
address | = | {Bratislava}, |
month | = | {2006}, |
annote | = | {dynopt is a set of MATLAB functions for determination of optimal control trajectory by given description of the process, the cost to be minimised, subject to equality and inequality constraints, using orthogonal collocation on finite elements method. The actual optimal control problem is solved by complete parametrisation both the control and the state profile vector. That is, the original continuous control and state profiles are approximated by a sequence of linear combinations of some basis functions. It is assumed that the basis functions are known and optimised are the coefficients of their linear combinations. In addition, each segment of the control sequence is defined on a time interval whose length itself may also be subject to optimisation. It is assumed, that the optimised dynamic model is described by a set of ordinary differential equations. This collection of functions extend the capability of the MATLAB Optimisation Toolbox, specifically of the constrained nonlinear minimisation routine fmincon.}, |
url | = | {https://www.uiam.sk/assets/publication_info.php?id_pub=271} |