Control Theory
Feedback, stability, optimal control, and stochastic control.
Control Theory. Feedback, stability, optimal control, and stochastic control. The literature on control theory divides naturally along several axes: the foundational structures that organise the subject, the techniques that drive proofs and computations, the questions about classification or representation that animate current research, and the bridges to neighbouring areas of mathematics and science. The references below trace those axes through the canonical textbook treatments and recent technical contributions.
Foundations and canonical references
The standard treatments of control theory approach the subject from complementary angles. Sontag, Mathematical Control Theory: Deterministic Finite Dimensional Systems (1998) is the anchor reference for the subject and lays out the core definitions, theorems, and worked examples that practitioners return to. Chen, Linear System Theory and Design (1999) gives a parallel, more proof-oriented exposition of the same material and is widely used as a graduate text. Franklin, Feedback Control of Dynamic Systems (2014) offers an alternative presentation that complements the primary references and is useful for triangulating definitions and proof techniques.
Open methodological questions for control theory include sharpening the bridges between foundational theory and computational practice, extending classical results to broader or more structured settings, and integrating the techniques surveyed above with adjacent mathematical disciplines. The references listed in this page are the entry points that current work builds on.
Prerequisites
Sources
- textbook · primary · 1998Mathematical Control Theory: Deterministic Finite Dimensional Systemssontag-1998
- textbook · primary · 1999Linear System Theory and Designchen-chitsong-1999
- textbook · supporting · 2014Feedback Control of Dynamic Systemsfranklin-2014, powell-2014, emami-naeini-2014
In context
Where this topic sits in the prerequisite graph. Click any node to jump.
Explore
- 01
Linear Control Theory
LQR, LQG, controllability, and observability.
- 02
Nonlinear Control
Lyapunov methods, feedback linearization, and sliding mode.
- 03
Optimal Control
Pontryagin's maximum principle and dynamic programming.
- 04
Stochastic and Robust Control
H-infinity, risk-sensitive, and adaptive control under uncertainty.
- 05
Model Predictive Control
Receding-horizon control with constraints.
- 06
Distributed and Networked Control
Multi-agent control, consensus, and event-triggered communication.
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