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Robust Position Sensorless Model Predictive Control for Interior Permanent Magnet Synchronous Motor Drives

This thesis focuses on utilizing the persistent voltage vector injections by finite control
set model predictive control (FCSMPC) to enable simultaneous estimations of
both position and parameters in order to realize robust sensorless interior permanent
magnet synchronous machine (IPMSM) drives valid at the entire operating region
including no-load standstill without any additional signal injection and switchover.
The system (here, IPMSM) needs to meet certain observability conditions to
identify the parameters and position. Moreover, each combination of the parameters
and/or position involves different observability requirements which cannot be
accomplished at every operating point. In particular, meeting the observability for
parameters and position at no-load standstill is more challenging. This is overcome
by generating persistent excitation in the system with high-frequency signal injection.
The FCSMPC scheme inherently features the persistent excitation with voltage vector
injection and hence no additional signal injection is required. Moreover, the persistent
excitation always exists for FCSMPC except at the standstill where the control
applies the null vectors when the reference currents are zero. However, introducing
a small negative d axis current at the standstill would be sufficient to overcome this
situation.The parameter estimations are investigated at first in this thesis. The observability is analyzed for the combinations of two, three and four parameters and experimentally
validated by online identification based on recursive least square (RLS) based adaptive
observer. The worst case operating points concerning observability are identified and
experimentally proved that the online identification of all the parameter combinations
could be accomplished with persistent excitation by FCMPC. Moreover, the effect
of estimation error in one parameter on the other known as parameter coupling is
reduced with the proposed decoupling technique.
The persistent voltage vector injections by FCSMPC help to meet the observability
conditions for estimating the position, especially at low speeds. However, the
arbitrary nature of the switching ripples and absence of PWM modulator void the
possibility of applying the standard demodulation based techniques for FCSMPC.
Consequently, a nonlinear optimization based observer is proposed to estimate both
the position and speed, and experimentally validated from standstill to maximum
speed. Furthermore, a compensator is also proposed that prevents converging to
saddle and symmetrical ( ambiguity) solutions.
The robustness analysis of the proposed nonlinear optimization based observer
shows that estimating the position without co-estimating the speed is more robust
and the main influencing parameters on the accuracy of the position estimation are d
and q inductances. Subsequently, the proposed nonlinear optimization based observer
is extended to simultaneously estimate the position, d and q inductances. The experimental
results show the substantial improvements in response time, and reduction
in both steady and transient state position errors.
In summary, this thesis presents the significance of persistent voltage vector injections
in estimating both parameter and position, and also shows that nonlinear
optimization based technique is an ideal candidate for robust sensorless FCSMPC. / Thesis / Doctor of Philosophy (PhD)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/22850
Date January 2018
CreatorsNalakath, Shamsuddeen
ContributorsEmadi, Ali, Electrical and Computer Engineering
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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