Project Sherlock

Engineering

Control Systems Engineering

Making a system behave, despite disturbance and uncertainty.

12 topics · 14 curated works

Topics

  • 01Foundations & Overviews1
  • 02Feedback Control1
  • 03PID Control1
  • 04State Space Methods1
  • 05Frequency Response Methods2
  • 06Stability Analysis1
  • 07Optimal Control2
  • 08Adaptive Control1
  • 09Robust Control1
  • 10Nonlinear Control1
  • 11Kalman Filtering1
  • 12System Identification1

Reading in Control Systems Engineering

14

A way in

  1. Start here

    No prior grounding assumed.

    Electronic Feedback Systems

    James K. Roberge (MIT OpenCourseWare) · 1985

    Builds classical feedback control design from a real operational amplifier's behaviour rather than an abstract block diagram, arguing that intuition…

  2. Then

    Assumes you know the vocabulary.

    Stabilized Feed-Back Amplifiers

    H. S. Black · 1934

    Deliberately throwing away gain and feeding the output back in opposition buys stability, linearity and bandwidth — the paper that made long-distance…

    +1 more at this level

  3. Go deeper

    Primary sources and full treatments.

    Regeneration Theory

    Harry Nyquist · 1932

    Shows that a feedback amplifier's stability can be read directly from how its open-loop response encircles a single point in the complex plane,…

    +10 more at this level

12 of 14 works

Series1985

Electronic Feedback Systems

James K. Roberge (MIT OpenCourseWare)

Builds classical feedback control design from a real operational amplifier's behaviour rather than an abstract block diagram, arguing that intuition for stability, noise and nonlinearity is best built from a physical circuit before it is generalised.

link checked 17 Sept 2026
Paper1932

Regeneration Theory

Harry Nyquist

Shows that a feedback amplifier's stability can be read directly from how its open-loop response encircles a single point in the complex plane, without ever solving the closed-loop equations.

link checked 17 Sept 2026
Paper1954

The Theory of Dynamic Programming

Richard Bellman

States a principle of optimality — an optimal policy has the property that, whatever the initial decision, the remaining decisions must be optimal for the resulting state — and uses it to turn multistage decision problems into a recursive functional equation.

link checked 17 Sept 2026
Paper1971

System Identification—A Survey

Karl Johan Åström & Peter Eykhoff

Surveys the methods then available for estimating a dynamic model from input-output data and organises them by the assumptions each makes about noise, giving system identification its first common framework and vocabulary.

Book1989

Adaptive Control

Karl Johan Åström & Björn Wittenmark

Treats adaptive control as controller design where the plant model itself is estimated online, and argues the central design question is not whether to adapt but how fast, since adapting too quickly destabilises what adapting too slowly leaves uncorrected.

Book1992

Feedback Control Theory

John C. Doyle, Bruce A. Francis & Allen R. Tannenbaum

Develops loop-shaping feedback design directly from the algebra of closed-loop transfer functions, treating performance and robustness to model uncertainty as one trade-off expressed in the same equations rather than as separate design steps.

link checked 17 Sept 2026

In order written

1932 – 2008
  1. 1932Regeneration TheoryHarry Nyquist
  2. 1942Optimum Settings for Automatic ControllersJ. G. Ziegler & N. B. Nichols
  3. 1971System Identification—A SurveyKarl Johan Åström & Peter Eykhoff
  4. 1985Electronic Feedback SystemsJames K. Roberge (MIT OpenCourseWare)
  5. 1989Adaptive ControlKarl Johan Åström & Björn Wittenmark
  6. 1992Feedback Control TheoryJohn C. Doyle, Bruce A. Francis & Allen R. Tannenbaum
  7. 1992Nonlinear SystemsHassan K. Khalil
  8. 2008Feedback Systems: An Introduction for Scientists and EngineersKarl Johan Åström & Richard M. Murray

Elsewhere in Engineering