93853 - Advanced Guidance and Control of Aircraft and Spacecraft

Learning outcomes

The objective of the course is to provide the students with modern guidance and control techniques which apply to all flying vehicles without distinction. The course is intended for students in aerospace engineering, oriented to both atmospheric and space flight. The focus is on the application of multivariable robust OPTIMAL CONTROL theory and INTELLIGENT CONTROL, based on Neural Networks and Machine Learning, for guidance and control of fixed/rotary wing aircraft, spacecraft, missiles and re-entry vehicles. The overall project of the autopilots currently implemented in commercial (airliner) and general aviation aircraft is proposed jointly with modern guidance and control systems for satellites, space stations, microsatellites, missiles and re-entry vehicles. An appealing feature of the course is the ready and extensive use of MATLAB®/Simulink® codes in the many solved examples illustrating guidance and control design, analysis and implementation. Furthermore, at the end of the course, the operation and programming of commercial autopilots are practically taught by using a certified flight simulator c/o an ENAC-certified flight school.

Course contents

1. Review of Linear Control Systems. Linear state-space models; Equilibrium solutions; Stability of equilibrium solutions. Internal and external stability; Controllability and stabilizability; State-feedback design by pole placement. 
2. Introduction to Nonlinear Control Systems. Nonlinear state-space models; Equilibrium solutions; Stability of equilibrium solutions; Lyapunov theory; Nonlinear control systems in affine form; Linearization; Stabilization via linear and non-linear state feedback. 
3. Rigid-Body Dynamics. Attitude Kinematics; Attitude parameterizations (Euler angles, unit quaternion, Modified Rodriguez parameters);  Euler Equation; Newton's laws; Translational kinematics; External forces and moments. 
4. Attitude Control. Stabilization of the angular velocity dynamics; Moment-exchanging devices; Satellite de-tumbling via linear and non-linear feedback;  Attitude error parameterization; Linear set-point control; Passivity-based set-point attitude control; Attitude tracking control via back-stepping methods. 
5. CTOL Fixed-Wing Aircraft. Aircraft models; Stability-axes and wing-axes representations. Trimming; Steady-state trajectories; Linearized models; Longitudinal and lateral dynamics; Handling qualities; Control and stability augmentation. 
6. Flight Control Design for CTOL FWA using Linear Methods. Linear -quadratic regulator; Inversion; Tracking control; Model-following design. Gain-scheduling. 
7. Flight Control Design for CTOL FWA using Nonlinear Methods. Dynamic inversion (aka, linearization by feedback); Back-stepping design
8. V/STOL Aircraft. Tail-sitters MAVs and quad-copters models; Hierarchical control: inner-loop and outer-loop controllers; Linear control design; Nonlinear control design.
9. Control Allocation. Input-redundant systems; Static control allocation methods; Dynamic control allocation.
10. Adaptive Control. Model-reference adaptive control (MRAC) for linearized aircraft models; Adaptive augmentation; Adaptive dynamic inversion.
11. Case Study: Highly-Maneuverable Aircraft. Simulation model (SM) and control-design model (CDM); Control objectives; System inversion; Adaptive inner-loop control: Airspeed control; Attitude control; Robust outer-loop control: lateral velocity and vertical velocity control; Control reconfiguration.

Readings/Bibliography

Lecture Notes: 

• Andrea Serrani, Lecture Notes on Advanced Flight Control Systems Design,  2025. 

Lecture notes on selected topics will be made available to the students. These are by no means to be considered exhaustive to achieve proficiency in the subject matter of the course.

Main Textbook:

• Stevens, B. L., Lewis, F. L., & Johnson, E. N. (2016). Aircraft Control and Simulation (Third Edition). John Wiley & Sons.

Auxiliary Textbooks:

• Lavretsky, E., & Wise, K. A. (2024). Robust and Adaptive Control: With Aerospace Applications, Second Edition. Springer Verlag.

• Kellett, C. M., & Braun, P. (2023). Introduction To Nonlinear Control - Stability, Control Design, and Estimation. Princeton University Press. 

• Isidori, A., Marconi, L., & Serrani, A. (2003). Robust Autonomous Guidance - An Internal Model Approach. Springer Verlag.

Useful Readings:

• Kaminer, I., Pascoal, A., Hallberg, E., & Silvestre, C. (1998). Trajectory tracking for autonomous vehicles: An integrated approach to guidance and control. Journal of Guidance, Control, and Dynamics, 21(1), 29–38.

• Roberts, A., & Tayebi, A. (2009). Adaptive position tracking of VTOL UAVs. IEEE Transactions on Robotics, 27(1), 129–142.

• Hua, M., Hamel, T., & Samson, C. (2013). Feedback Control of Underactuated VTOL Vehicles. IEEE Control Systems, 61–75.

• Lane, S. H., & Stengel, R. F. (1988). Flight control design using non-linear inverse dynamics. Automatica, 24(4), 471–483.

• Bodson, M. (2002). Evaluation of optimization methods for control allocation. Journal of Guidance, Control, and Dynamics, 25(4), 703–711.

• Johansen, T. A., & Fossen, T. I. (2013). Control allocation—A survey. Automatica, 49(5), 1087–1103.

 

 

 

 

Teaching methods

In-person lectures.

Assessment methods

The assessment of the student's proficiency consists in an individual or group final project (depending on the size of the class) and an individual comprehensive oral exam. 

The individual or group project consists in an open-ended design problem for a specific vehicle configuration. Typically the student(s) will be asked to:

• Derive and implement the vehicle model on Simulink
• Find the trim condition corresponding to a desired set-point
• Find the exact or approximate inverse corresponding to a desired steady-state trajectory. 
• Find the linearized equations of motion around a trim condition
• Develop and implement a linear controller or a gain-scheduled family of linear controller to cover a given range of operating conditions
• Develop and implement a nonlinear controller to cover a given range of operating conditions. 

The individual oral exam will comprise questions on all aspects of the individual or group project and questions on the topics of the course. 

Teaching tools

• Lectures
• Examples and recitation sessions.
• Case studies.
• Homework problems.
• Computer-aided design tools (MATLAB & SIMULINK)

Office hours

See the website of Andrea Serrani