Low-Gain Integral Control for Nonlinear Systems
Provides stability certificates and design methods for integral control applied to stable nonlinear systems.
Professor John W. Simpson-Porco
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John W. Simpson-Porco, Ph.D. Associate Professor, Department of Electrical and Computer Engineering Email: jw.simpson [at] utoronto [dot] ca |
I study feedback control theory, control engineering, and applications of control in modernized energy systems. We develop rigorous approaches for designing reliable controllers for complex, uncertain systems under tight performance constraints.
Research Themes
Control Theory and Engineering
Analysis and design tools for feedback systems, with emphasis on stability, robustness, performance, and practicality.
linear, nonlinear, and stochastic control · robust stability · low-gain design
Optimization-Based Control
Control architectures that optimize the dynamic, steady-state, and economic operation of an engineering system.
feedback-based optimization · predictive control · optimal steady-state control
Advanced Power System Control
From fast control of bulk power systems with IBRs, to optimal DER coordination in distribution systems, to remote microgrids.
frequency/voltage control · inverter-based resources · power system operations · hierarchical control
Data-Driven Control
Methods that use data directly for prediction, optimization, and control when models are uncertain or unavailable.
data-driven control · stochastic MPC · tuning regulators
Recent News
May 2026: New paper on frequency-aware power system restoration planning.
March 2026: New paper on robust D-stability and decentralized integral control.
February 2026: Our paper on data-driven stochastic control is accepted to IEE TAC.
January 2026: Our paper on steady-state cascade operators has been published in IEEE TAC.
November 2025: New submission on estimator-enhanced feedback-based optimization to ECC 2026.
Selected Contributions
Microgrid Stability Definitions, Analysis, and Examples
A widely used task-force reference organizing stability concepts and modeling issues for modern microgrids.
A Theory of Solvability for Lossless Power Flow Equations
A deep dive into the power flow equation solution space, including solvability conditions and numerical algorithms with guarantees.
Linear-Convex Optimal Steady-State Control
Connects control design and steady-state optimization, giving a framework for controllers that regulate while optimizing.
Feedback-Based Optimization for Distribution Grids
A multi-area hierarchical control architecture to coordinate and optimize DERs in distribution grids, scalable to thousands of devices.
Data-Driven Fast Frequency Control with Inverter-Based Resources
Fast frequency controller designs to capitalize on the speed of inverter-based resources; no models, just data.
News Archive
Older announcements and travel notes are available in the news archive.