Reference Info for R1


SOLVING OPTIMAL CONTROL PROBLEMS USING SIMSCAPE MODELS FOR STATE DERIVATIVES

D. R. Herber


[url] [pdf] [code]

Text Reference:

D. R. Herber. 'Solving optimal control problems using Simscape models for state derivatives.' Technical report, Engineering System Design Lab, UIUC-ESDL-2014-01, Urbana, IL, USA, Jul 2014.

BibTeX Source:

@techreport{Herber2014b,
  author      = {Herber, Daniel R},
  title       = {Solving optimal control problems using {Simscape} models for state derivatives},
  type        = {Technical Report},
  institution = {Engineering System Design Lab},
  number      = {UIUC-ESDL-2014-01},
  address     = {Urbana, IL, USA},
  month       = jul,
  year        = {2014},
  url         = {http://hdl.handle.net/2142/50015},
  pdf         = {https://www.engr.colostate.edu/%7Edrherber/files/Herber2014b.pdf},
}

Abstract:

This technical report outlines an approach to calculate derivative functions for Simscape models and use them to solve optimal control problems. Although this approach is less efficient than analytic expression for the derivatives, not every problem will have these directly available due to a variety of reasons, including multidomain, multibody, large-scale, automatically generated, or proprietary models. A step-by-step procedure is presented to assist utilizing this approach. The canonical Bryson-Denham state-constrained double integrator optimal control problem is used as a test optimal control problem. A number of control formulations are compared to demonstrate the computational expense of this approach compared to analytic expressions of the state derivatives and additional benefits including improved final solutions and execution time over more traditional formulations. In particular, direct transcription solutions are decidedly more efficient than the common shooting approach. Coupled with an optimal control toolbox, the user will no longer need to worry about expressing complex derivative equations or the implementation details of their optimal control problem, allowing the focus to be shifted towards solving more complex problems.