Course schedule
Classes 1--13 contain the main course content. Classes 14--15 are reserved for later release.
| Class | Theme | Core topics | Lab outcome | Slides |
|---|---|---|---|---|
| Class 1 | Course Overview and Control Fundamentals | Motivation for control engineering and AI-enabled control; Open-loop and closed-loop systems | Understand the course workflow, software tools, and final project expectations. | Download PDF |
| Class 2 | Linear Dynamical Systems and Transfer Functions | Linear time-invariant system models; Transfer functions and block diagrams | Build simple transfer-function simulations and interpret system responses. | Download PDF |
| Class 3 | Closed-Loop Stability and Root Locus | Closed-loop characteristic equations; Stability and pole locations | Analyze closed-loop stability and tune simple feedback controllers. | Download PDF |
| Class 4 | Frequency Response, State Space, and RL Introduction | Frequency response and Bode-plot interpretation; State variables and state-space representation | Connect transfer-function and state-space viewpoints through examples. | Download PDF |
| Class 5 | CartPole Reinforcement Learning and DQN Practice | CartPole dynamics and observation/action spaces; Markov decision process formulation | Run DQN training and evaluate a CartPole control policy. | Download PDF |
| Class 6 | Overview of Autonomous Quadrotor UAV Research | UAV applications and low-altitude economy; basic quadrotor dynamics and underactuation; differential flatness; localization, perception, SLAM, planning, PX4, and AI-based autonomous flight | Understand the autonomy stack of quadrotor UAVs and connect perception, planning, and control modules. | Download PDF |
| Class 7 | RIP Hardware Introduction and Dynamic Analysis | RIP mechanical structure, rotary arm, pendulum link, DC motor, and driver; Potentiometer and encoder signals for angle measurement | Inspect the RIP hardware platform, identify sensor and actuator connections, derive the main state variables, and connect the physical system to its dynamic model. | Download PDF |
| Class 8 | Hardware Assembly, Sensor Test, and Bellman Bridge | PC--STM32--TB6612--motor--sensor wiring; Potentiometer and encoder signal tests | Run sensor and motor tests and collect calibrated experimental data. | Download PDF |
| Class 9 | Optimal Control Experiments on RIP | State feedback and LQR design; MPC prediction model and constraints | Run LQR and MPC experiments and compare time-domain responses. | Download PDF |
| Class 10 | State Observers for RIP Control | Measured and estimated states; Luenberger observer | Compare direct numerical derivatives with observer-estimated states. | Download PDF |
| Class 11 | DQN, PPO, and TD3 RIP Simulation Training | DQN, PPO, and TD3 algorithm overview; Custom RIP simulation environment | Train and evaluate RL policies in simulation. | Download PDF |
| Class 12 | RL Sim-to-Real Deployment | Policy export and embedded deployment; STM32 firmware integration | Deploy trained policies and record sim-to-real experimental data. | Download PDF |
| Class 13 | Hybrid Control, Sim-to-Real Improvement, and Final Demo | Hybrid control architecture; Model-based controller and RL policy comparison | Complete the final demonstration and compare control strategies. | Download PDF |
| Class 14 | Reserved Session | Additional experiment or project discussion; To be announced | Reserved for later release. | Reserved |
| Class 15 | Reserved Session | Final extension or presentation session; To be announced | Reserved for later release. | Reserved |