Control Theory

Feedback, stability, optimal control, and stochastic control.


foundation tier

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 · 1998
    Mathematical Control Theory: Deterministic Finite Dimensional Systems
    sontag-1998
  • textbook · primary · 1999
    Linear System Theory and Design
    chen-chitsong-1999
  • textbook · supporting · 2014
    Feedback Control of Dynamic Systems
    franklin-2014, powell-2014, emami-naeini-2014

In context

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Explore

  1. 01

    Linear Control Theory

    LQR, LQG, controllability, and observability.

  2. 02

    Nonlinear Control

    Lyapunov methods, feedback linearization, and sliding mode.

  3. 03

    Optimal Control

    Pontryagin's maximum principle and dynamic programming.

  4. 04

    Stochastic and Robust Control

    H-infinity, risk-sensitive, and adaptive control under uncertainty.

  5. 05

    Model Predictive Control

    Receding-horizon control with constraints.

  6. 06

    Distributed and Networked Control

    Multi-agent control, consensus, and event-triggered communication.


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