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

TL;DR
This study compares nonlinear feedback linearization and LQG/LTR control strategies for a power system, analyzing their effectiveness in stability, robustness, and performance through simulations.
Contribution
It provides a comprehensive control synthesis framework and comparative analysis for nonlinear and linear control methods applied to power systems.
Findings
NFLC and INFLC precisely cancel nonlinearities, enabling linear control.
LQG/LTR offers a balanced trade-off between performance and robustness.
Simulations highlight the strengths and limitations of each control approach.
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Control Systems Optimization · Iterative Learning Control Systems
