Nonlinear Feedback Linearization and LQG/LTR Control: A Comparative Study for a Single-Machine Infinite-Bus System

摘要

This paper presents a comparative study of three advanced control strategies for a single-machine infinite-bus (SMIB) system: the nonlinear feedback linearizing controller (NFLC), the integral-NFLC (INFLC), and the linear-quadratic-Gaussian/loop transfer recovery (LQG/LTR) control. The NFLC and INFLC techniques use exact feedback linearization to precisely cancel the SMIB system nonlinearities, enabling the use of decentralized, linear, and optimal controllers for the decoupled generator and turbine-governor systems while remaining unaffected by the SMIB system's internal dynamics and operating conditions. In contrast, the LQG/LTR approach employs an enhanced Kalman filter, designed using the LTR procedure and a detailed frequency-domain loop-shaping analysis, to achieve a reasonable trade-off between optimal performance, noise/disturbance rejection, robustness recovery, and stability margins for the SMIB system. We provide a control synthesis framework for constructing practical, verifiable, scalable, and resilient linear and nonlinear controllers for SMIB and multi-machine power systems by utilizing a high-fidelity plant model for validation, a reduced-order control-design model, and the correlations between the two models' control inputs. Rigorous simulations and comparative analysis of the proposed controllers and a full-state linear-quadratic regulator show the benefits, constraints, and trade-offs of each controller in terms of transient response, steady-state error, robustness, rotor angle stability, frequency control, and voltage regulation under different operating conditions. Ultimately, this study aims to guide the selection of appropriate control strategies for large-scale power systems, enhancing the overall resilience and reliability of the electric grid.