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Indirect adaptive control of a cyber-physical solid-oxide fuel cell hybrid energy system

Amoafo, Mychal (2023) Indirect adaptive control of a cyber-physical solid-oxide fuel cell hybrid energy system. Undergraduate Thesis, University of Pittsburgh. (Unpublished)

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The ability of a system to maintain its performance despite changes to its environment
is known as adaption. This type of behaviour is prevalent in biological systems and is
leveraged in control system to achieve optimal performance when the state variables of
a parameter changes. Adaptive control systems leverage system identification to update
controller parameter to ensure the stability of a system.

The ability to design optimal controllers by identifying changes in system model makes
adaptive control attractive for dispatchable energy systems. Dispatchable energy systems are
power systems capable of responding rapidly to grid fluctuations by providing or removing
power from the grid, enhancing grid resiliency. The solid-oxide fuel cell gas turbine (SOFCGT)
integrates a solid-oxide fuel cell stack with a micro-gas turbine. It can operate as an
dispatchable energy system. Due to highly coupled nature of the SOFC-GT system, the
dynamics are inherently nonlinear, and control with linear controller produces sub-optimal
control. Ensuring that SOFC-GT systems can undergo rapid-load transitions requires the use
of advances algorithms that can control critical process parameters like turbine speed, massflows,
pressures, temperature gradients across the SOFC stack, etc. Dispatchable energy
systems must also operate at off-design operating conditions (partial electric loads) where
the a controller designed for nominal operating conditions (full electric load) may perform
poorly. Adaptive control will allow the updating of controller gains throughout the entire
operating envelope of a dispatchable energy asset, capturing changes to a plant parameter
due to different system configures by leveraging system identification.

In highly coupled advanced power systems, like any other mechanical system, system
components degrade. For example, in a SOFC-GT system, the recuperator, a type of heat
exchanger, the insulation may degrade after multiple cycles. The degrading insulation decreases
the efficiency of the heat exchanger. In this scenario, to reach a target temperature
requires more heat needs to be provided to the heat exchanger, more fuel needs to be burned
compared. The promise of adaptive control is to account for this change in the system and
designed an optimal control law that reduces the required fuel to reach the target temperature.

This paper investigates the indirect adaptive control, specifically adaptive pole placement
control, where system identification and controller design are performed to ensure safe operating
conditions. This work implements recursive system identification and pole placement
for control design. The complete adaptive pole placement control is not implemented, the
updating controller coefficients are not used in the feedback loop. Although, the updated
controller is not in the feedback loop, insights about adaptive pole placement control can be
surmised from the preliminary results.

The feasibility of adaptive pole placement is discussed in this work. Issues in system
identifying and controller design are discussed. Potential solutions to overcome these issues
is discussed.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairBajaj, Nikhilnbajaj@pitt.edunbajaj
Committee MemberCole, Danieldgcole@pitt.edudgcole
Committee MemberClark, Williamwclark@pitt.eduwclark
Committee MemberTucker,
Date: 14 December 2023
Date Type: Publication
Defense Date: 8 December 2023
Approval Date: 14 December 2023
Submission Date: 8 December 2023
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 70
Institution: University of Pittsburgh
Schools and Programs: David C. Frederick Honors College
Degree: BSE - Bachelor of Science in Engineering
Thesis Type: Undergraduate Thesis
Refereed: Yes
Uncontrolled Keywords: Adaptive control, hybrid energy systems
Date Deposited: 14 Dec 2023 18:30
Last Modified: 14 Dec 2023 18:30


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