Part I: System modeling

	Lecture notes	Dates	Supplementary material
1.	Introduction		Math prerequisites
2.	Linear mechanical systems
3.	Rotational mechanical systems
4.	Systems with kinematic constraints
5.	RLC circuits		Extra circuit problems + solutions
6.	Op amps
7.	DC motors
8.	Hydraulic systems

Part II: System analysis

	Lecture notes	Dates	Supplementary material
9.	Intro to Simulink
10.	Linear systems		Extra circuit problems + solutions
11.	The Laplace transform		Linearity and linearization
12.	More Laplace transforms
13.	Impedance analysis of circuits
14.	The impulse response
15.	Simulating LTI systems in Matlab
16.	Inverse Laplace transforms
17.	More inverse Laplace transforms
18.	First-order systems
19.	Second-order systems		DEMO: Second-order step response
20.	More second-order systems

Part III: Feedback control

	Lecture notes	Dates	Supplementary material
21.	Feedback and proportional control		Stability criteria
22.	Final Value Theorem		10-min video on PID control
23.	PID control		DEMO: Inverted pendulum PID control
24.	Root locus plots		Root locus cheat sheet
25.	RL dominant poles, effect of zeros		DEMO: Dominant poles
26.	RL design, pendulum on a cart		Dominant poles
27.	RL design, PID for a DC motor
28.	Frequency response
29.	Bode plot for 1st order systems		DEMO: 1st order forced response
30.	Bode plot for 2nd order or higher		DEMO: 2nd order forced response
31.	Bode design, stability margins
32.	Bode design with SISOtool

Part IV: Bonus material

Discrete-time control. Most plants have continuous-time dynamics (described by ODEs), whereas most sensors provide measurements at evenly spaced points in time (discrete time). Moreover, most controllers nowadays are implemented in software or on microcontrollers, which means the implementations must be digital (all time is discretized). So how does one carry out controller design for these sorts of hybrid systems that have a mixture of discrete and continuous parts?

• Discrete-time analysis and control

Balancing a stick, and the limits of human performance. This demonstration is inspired by John Doyle. See for example this series of papers or one of John’s many talks on YouTube. I adapted the demo to include connections to the course material, for example root locus plots and Bode plots. Here are my notes:

• Mathematical derivations
• Diagrams and figures

Textbook:

There is no required textbook for the class. However, I can recommend several excellent books as reference texts:

• Dorf, R.C. and Bishop, R.H., Modern Control Systems, Prentice Hall.
• Ogata, K., Modern Control Engineering, Prentice Hall.
• Kluever, C.A., Dynamic Systems, Modeling, Simulation, and Control, Wiley.
• Nise, N.S., Control Systems Engineering, Wiley.
• Astrom, Murray, Feedback Systems: An Introduction for Scientists and Engineers (free online)

You will not need these books. I’m only listing them in case you want to consult additional references.

Online references:

There are many excellent online references for classical control. My top recommendations are:

• Brian Douglas’s Classical Control Theory Course. Controls course designed for online learning. All videos are short (~10min) and exceptionally clear.
• Christopher Lum’s Control Theory Playlist. This series of videos covers all of classical controls in a more traditional lecture-based format. There are also detailed Matlab demos and worked examples.