東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Optimal Control of Weakly Forced Non...

Dasanayake, Isuru Sammana.

Linked to FindBook

Google Book

Amazon

博客來

Optimal Control of Weakly Forced Nonlinear Oscillators.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimal Control of Weakly Forced Nonlinear Oscillators./
Author:	Dasanayake, Isuru Sammana.
Description:	141 p.
Notes:	Source: Dissertation Abstracts International, Volume: 74-08(E), Section: B.
Contained By:	Dissertation Abstracts International74-08B(E).
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3558067
ISBN:	9781303023200

Optimal Control of Weakly Forced Nonlinear Oscillators.
Dasanayake, Isuru Sammana.

Optimal Control of Weakly Forced Nonlinear Oscillators. - 141 p.

Source: Dissertation Abstracts International, Volume: 74-08(E), Section: B.

Thesis (Ph.D.)--Washington University in St. Louis, 2013.

Optimal control of nonlinear oscillatory systems poses numerous theoretical and computational challenges. Motivated by applications in neuroscience, we develop tools and methods to synthesize optimal controls for nonlinear oscillators described by reduced order dynamical systems. Control of neural oscillations by external stimuli has a broad range of applications, ranging from oscillatory neurocomputers to deep brain stimulation for Parkinson's disease. In this dissertation, we investigate fundamental limits on how neuron spiking behavior can be altered by the use of an external stimulus (control). Pontryagin's maximum principle is employed to derive optimal controls that lead to desired spiking times of a neuron oscillator, which include minimum-power and time-optimal controls. In particular, we consider practical constraints in such optimal control designs including a bound on the control amplitude and the charge-balance constraint. The latter is important in neural stimulations used to avoid from the undesirable effects caused by accumulation of electric charge due to external stimuli. Furthermore, we extend the results in controlling a single neuron and consider a neuron ensemble. We, specifically, derive and synthesize time-optimal controls that elicit simultaneous spikes for two neuron oscillators. Robust computational methods based on homotopy perturbation techniques and pseudospectral approximations are developed and implemented to construct optimal controls for spiking and synchronizing a neuron ensemble, for which analytical solutions are intractable. We finally validate the optimal control strategies derived using the models of phase reduction by applying them to the corresponding original full state-space models. This validation is largely missing in the literature. Moreover, the derived optimal controls have been experimentally applied to control the synchronization of electrochemical oscillators. The methodology developed in this dissertation work is not limited to the control of neural oscillators and can be applied to a broad class of nonlinear oscillatory systems that have smooth dynamics.

ISBN: 9781303023200Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Optimal Control of Weakly Forced Nonlinear Oscillators.
LDR:03022nam a2200289 4500 001 1960746
005 20140624210000.5
008 150210s2013 ||||||||||||||||| ||eng d
020 $a 9781303023200
035 $a (MiAaPQ)AAI3558067
035 $a AAI3558067
040 $a MiAaPQ $c MiAaPQ
100 1 $a Dasanayake, Isuru Sammana. $3 2096456
245 1 0 $a Optimal Control of Weakly Forced Nonlinear Oscillators.
300 $a 141 p.
500 $a Source: Dissertation Abstracts International, Volume: 74-08(E), Section: B.
500 $a Adviser: Jr-Shin Li.
502 $a Thesis (Ph.D.)--Washington University in St. Louis, 2013.
520 $a Optimal control of nonlinear oscillatory systems poses numerous theoretical and computational challenges. Motivated by applications in neuroscience, we develop tools and methods to synthesize optimal controls for nonlinear oscillators described by reduced order dynamical systems. Control of neural oscillations by external stimuli has a broad range of applications, ranging from oscillatory neurocomputers to deep brain stimulation for Parkinson's disease. In this dissertation, we investigate fundamental limits on how neuron spiking behavior can be altered by the use of an external stimulus (control). Pontryagin's maximum principle is employed to derive optimal controls that lead to desired spiking times of a neuron oscillator, which include minimum-power and time-optimal controls. In particular, we consider practical constraints in such optimal control designs including a bound on the control amplitude and the charge-balance constraint. The latter is important in neural stimulations used to avoid from the undesirable effects caused by accumulation of electric charge due to external stimuli. Furthermore, we extend the results in controlling a single neuron and consider a neuron ensemble. We, specifically, derive and synthesize time-optimal controls that elicit simultaneous spikes for two neuron oscillators. Robust computational methods based on homotopy perturbation techniques and pseudospectral approximations are developed and implemented to construct optimal controls for spiking and synchronizing a neuron ensemble, for which analytical solutions are intractable. We finally validate the optimal control strategies derived using the models of phase reduction by applying them to the corresponding original full state-space models. This validation is largely missing in the literature. Moreover, the derived optimal controls have been experimentally applied to control the synchronization of electrochemical oscillators. The methodology developed in this dissertation work is not limited to the control of neural oscillators and can be applied to a broad class of nonlinear oscillatory systems that have smooth dynamics.
590 $a School code: 0252.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, System Science. $3 1018128
650 4 $a Applied Mathematics. $3 1669109
690 $a 0544
690 $a 0790
690 $a 0364
710 2 $a Washington University in St. Louis. $b Electrical Engineering. $3 1679873
773 0 $t Dissertation Abstracts International $g 74-08B(E).
790 $a 0252
791 $a Ph.D.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3558067