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RISS 인기검색어
- 검색키워드
- 저자 : Frank L. Lewis (검색결과 3 건)
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- 유료
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Neuro-based Canonical Transformation of Port Controlled Hamiltonian Systems
Aminuddin Qureshi,Sami El Ferik,Frank L. Lewis 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.12
In the literature of control theory, tracking control of port controlled Hamiltonian systems is generally achieved using canonical transformation. Closed form evaluation of state-feedback for the canonical transformation requires the solution of certain partial differential equations which becomes very difficult for nonlinear systems. This paper presents the application of neural networks for the canonical transformation of port controlled Hamiltonian systems. Instead of solving the partial differential equations, neural networks are used to approximate the closedform state-feedback required for canonical transformation. Ultimate boundedness of the tracking and neural network weight errors is guaranteed. The proposed approach is structure preserving. The application of neural networks is direct and off-line processing of neural networks is not needed. Efficacy of the proposed approach is demonstrated with the examples of a mass-spring system, a two-link robot arm and an Autonomous Underwater Vehicle (AUV).
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Multilayered Polymer-Coated Carbon Nanotubes To Deliver Dasatinib
Moore, Thomas L.,Grimes, Stuart W.,Lewis, Robert L.,Alexis, Frank American Chemical Society 2014 MOLECULAR PHARMACEUTICS Vol.11 No.1
<P>Multilayered, multifunctional polymer coatings were grafted onto carbon nanotubes (CNTs) using a one-pot, ring-opening polymerization in order to control the release kinetic and therapeutic efficacy of dasatinib. Biocompatible, biodegradable multilayered coatings composed of poly(glycolide) (PGA) and poly(lactide) (PLA) were polymerized directly onto hydroxyl-functionalized CNT surfaces. Sequential addition of monomers into the reaction vessel enabled multilayered coatings of PLA-PGA or PGA-PLA. Poly(ethylene glycol) capped the polymer chain ends, resulting in a multifunctional amphiphilic coating. Multilayer polymer coatings on CNTs enabled control of the anticancer drug dasatinib’s release kinetics and enhanced the in vitro therapeutic efficacy against U-87 glioblastoma compared to monolayer polymer coatings.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/mpohbp/2014/mpohbp.2014.11.issue-1/mp400448w/production/images/medium/mp-2013-00448w_0009.gif'></P>
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입출력 데이터 기반 Q-학습과 LMI를 이용한 선형 이산 시간 시스템의 모델-프리 H<SUB>∞</SUB> 제어기 설계
김진훈(Jin-Hoon Kim),Frank L. Lewis 대한전기학회 2009 전기학회논문지 Vol.58 No.7
In this paper, we consider the design of H∞ control of linear discrete-time systems having no mathematical model. The basic approach is to use Q-learning which is a reinforcement learning method based on actor-critic structure. The model-free control design is to use not the mathematical model of the system but the informations on states and inputs. As a result, the derived iterative algorithm is expressed as linear matrix inequalities(LMI) of measured data from system states and inputs. It is shown that, for a sufficiently rich enough disturbance, this algorithm converges to the standard H∞ control solution obtained using the exact system model. A simple numerical example is given to show the usefulness of our result on practical application.
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