Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

maximum power point tracking in photovoltaic systems using model reference adaptive control

Zhang, Qinhao (2013) maximum power point tracking in photovoltaic systems using model reference adaptive control. Master's Thesis, University of Pittsburgh. (Unpublished)

Submitted Version

Download (1MB) | Preview


This thesis proposes adaptive control architecture for maximum power point tracking (MPPT) in photovoltaic systems. Photovoltaic systems provide promising ways to generate clean electric power. MPPT technologies have been used in photovoltaic systems to deliver the maximum power output to the load under changes of solar insolation and solar panel's temperature. To improve the performance of MPPT, this thesis proposes a two-layer adaptive control architecture that can effectively handle the uncertainties and perturbations in the photovoltaic systems and the environment. The first layer of control is ripple correlation control (RCC), and the second layer is model reference adaptive control (MRAC). By decoupling these two control algorithms, the control system achieves the maximum power point tracking with shorter time constants and overall system stability. To track the maximum power point as the solar insolation changes, the RCC algorithm computes the corresponding duty cycle, which serves as the input to the MRAC layer. Then the MRAC algorithm compensates the under-damped characteristics of the power conversion system: the original transfer function of the power conversion system has time-varying parameters, and its step response contains oscillatory transients that vanish slowly. Using the Lyapunov approach, an adaption law of the controller is derived for the MRAC system to eliminate the under-damped modes in power conversion.


Social Networking:
Share |


Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMao, Zhi-Hong
Committee MemberStanchina, William
Committee MemberReed, Gregory
Thesis AdvisorMao, Zhi-Hong
Date: 31 January 2013
Date Type: Publication
Defense Date: 19 November 2012
Approval Date: 31 January 2013
Submission Date: 26 November 2012
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 58
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Electrical Engineering
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Photovoltaic system, maximum power point tracking, model reference adaptive control and ripple correlation control.
Date Deposited: 31 Jan 2013 20:50
Last Modified: 15 Nov 2016 14:07


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item