Abstract
A new method for optimal control design of distributed parameter systems is presented in this paper. The concept of proper orthogonal decomposition is used for the model reduction of distributed parameter systems to form a reduced order lumped parameter problem. The optimal control problem is then solved in the time domain, in a state feedback sense, following the philosophy of ''adaptive critic'' neural networks. The control solution is then mapped back to the spatial domain using the same basis functions. Numerical simulation results are presented for a linear and nonlinear one-dimensional heat equation problem in an infinite time regulator framework.
Recommended Citation
R. Padhi and S. N. Balakrishnan, "Proper Orthogonal Decomposition Based Feedback Optimal Control Synthesis of Distributed Parameter Systems Using Neural Networks," Proceedings of the 2002 American Control Conference, Institute of Electrical and Electronics Engineers (IEEE), Jan 2002.
The definitive version is available at https://doi.org/10.1109/ACC.2002.1025337
Meeting Name
2002 American Control Conference
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
1D Heat Equation Problem; Distributed Parameter Systems; Heat Conduction; Model Reduction; Neural Nets; Neural Networks; Optimal Control; Orthogonal Decomposition; Reduced Order Lumped Parameter; Reduced Order Systems; State Feedback; Time Domain Analysis
International Standard Serial Number (ISSN)
0743-1619
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2002 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2002
