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Adaptive pattern recognition approach for dynamic system control using neural networks

Lee, Dennis Tak-Fat
http://rave.ohiolink.edu/etdc/view?acc_num=case1059488640

Abstract Details

1991, Doctor of Philosophy, Case Western Reserve University, Electrical Engineering.
An adaptive pattern recognition approach implemented using neural networks for control is proposed, and its performance is compared with other conventional and modern approaches. The new design utilizes self-organization and predictive estimation capabilities of neural-net computing. Real-time adaptation is facilitated by the error-based, on-line learning scheme implemented on a cluster-wise segmented associative memory system. The goals of a neural network control system are to be able to manipulate a large number of input and output variables, follow input commands, stabilize the system and satisfy multiple control objectives. Experimental investigation using computer simulation for case studies of the single area megawatt-frequency and megavar-voltage control problem is presented. It is demonstrated that the neural network system is capable of modeling highly nonlinear systems, detecting changes in the dynamic process conditions and stabilizing the system.
Yoh-Han Pao (Advisor)
141 p.
Adaptive pattern recognition approach; Neural networks

Recommended Citations

Citations

  • Lee, D. T.-F. (1991). Adaptive pattern recognition approach for dynamic system control using neural networks [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1059488640

    APA Style (7th edition)

  • Lee, Dennis. Adaptive pattern recognition approach for dynamic system control using neural networks. 1991. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1059488640.

    MLA Style (8th edition)

  • Lee, Dennis. "Adaptive pattern recognition approach for dynamic system control using neural networks." Doctoral dissertation, Case Western Reserve University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=case1059488640

    Chicago Manual of Style (17th edition)

case1059488640
929
© 1991, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.