UBC Theses and Dissertations
Parameters estimation based on recursive extended least-squares method in dc distribution systems and interior permanent magnet synchronous motors Xu, Jiayue
Adaptive control is widely used in modern control systems to maintain optimal system performance when the plant parameters are unknown and/or varying with time. Various system identification methods have been developed to estimate the system parameters in real time, which allows a parameter-related adaptive controller to be accordingly calibrated under parameter variation conditions. In this thesis, two practical applications of online parameters estimation are introduced: one the online source impedance identification for self-stabilizing controller design in dc distribution systems; and the adaptive controller design in interior permanent magnet synchronous motor (IPMSM) drive systems. In dc distribution systems, the parameters of source impedances are crucial for load controller design to guarantee the stability of source-load interface. Since the source impedance may vary when the system configuration changes, the online impedance estimation is necessary for designing advanced self-stabilizing controllers with “plug-n-play” functionality. In this thesis, an innovative technique is proposed for parametric estimation of source impedance using the recursive extended least-squares (RELS) method in conjunction with impulse and pseudo-random binary sequence (PRBS) injections. Rigorous simulation studies demonstrate that the proposed technique yields direct results while providing advantages over traditional ac sweep and commonly used discrete Fourier transform (DFT) techniques. To further verify the feasibility of the proposed method in the real-time environment, the proposed online parameters estimator is implemented and validated on the Typhoon and Opal-RT hardware-in-the-loop (HIL) platform. Moreover, the proposed methodology is extended to parameter-estimation-based adaptive control to mitigate the impact of parameter variations on the maximum torque per ampere (MTPA) operation of IPMSM drive systems. Specifically, a parameter estimator that exploits the RELS algorithm is established to accurately estimate the main parameters of the machine in real time, which enables calibration of the optimal current vector angle that is critical in the MTPA operation of IPMSMs. Extensive simulation studies have been carried out to verify the effectiveness and robustness of the proposed strategy.
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