By Topic

Optimization and Simplification of System Models Characterizing an R&d Process

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)

Recent developments in modern control theory and high-speed computation techniques have enabled extensive treatment of complex processes. A method is presented for building a model of an R& D process utilizing the state space approach. The specific model described in this paper contains 21 state variables and a control vector of 6 components. Its formulation leads to the Mayer's problem with inequality constraints imposed on the control vector. An algorithm based on the adjoint system technique is used for simultaneous optimization and simplification. The computation for the preceding model lasts 2.5 min and is completed within 5 iterations. It results in an improvement factor of three for the chosen index of performance. Simplification of the model reduces the 21 state variables and 6 control components into 1 state variable and 1 control component.

Published in:

Systems, Man and Cybernetics, IEEE Transactions on  (Volume:SMC-2 ,  Issue: 3 )