A Practical Guide to Control Theory

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1IntroductionMotivation, learning path, how to use this guide
2Digital Signal ProcessingFrequency domain, Laplace/Fourier transforms, LPF, complementary & notch filters
3System DescriptionTransfer functions, state-space, poles & zeros, stability analysis
4Classical ControlPID (single/cascade/parallel), tuning, feedforward, trajectory generation
5Discretization & ImplementationZOH, Tustin, matched Z-transform, MCU implementation
6Modern ControlLQR, Kalman filter, EKF, quaternion EKF, LQG, linear MPC
7Future ProspectsData-driven control, reinforcement learning, iLQR/DDP, neural networks + control
AAppendix: C++ ModulesHeader-only, embedded-ready implementations of all algorithms

Undergraduate students (year 1-3) with basic calculus and linear algebra. If derivatives don't scare you, you're ready.

Organized by engineering workflow, not mathematical abstraction. Every concept answers: "What is this for when the robot hits the field?"

Header-only C++ modules in the appendix -- no heap allocation, no exceptions, ISR-safe. Copy into your project and go.

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