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

Upon successful completion of the course, students will have acquired knowledge of guidance and control systems for aerospace vehicles, including both atmospheric and space-flight applications. The course covers modern methods for the analysis and design of linear and nonlinear control systems, with emphasis on robust and adaptive control techniques.

At the end of the course, students will be able to:

• derive mathematical models of aircraft and spacecraft suitable for guidance and control design;
• analyze the stability and performance of linear and nonlinear aerospace control systems;
• design linear, nonlinear, robust, and adaptive flight-control systems for fixed-wing aircraft, rotary-wing aircraft, and spacecraft;
• design guidance and control architectures for over-actuated aerospace vehicles, including control allocation strategies;
• implement and validate guidance and control algorithms using MATLAB® and Simulink®;
• critically evaluate alternative control methodologies and select appropriate design techniques for different aerospace applications.

The course combines theoretical developments with design examples implemented in MATLAB®/Simulink®.

Outline

1. Foundations of Modern Flight Control. Review of linear state-space models, stability, controllability, and state-feedback design. Nonlinear systems, Lyapunov stability, linearization, and nonlinear state-feedback stabilization.
   
2. Dynamics of Aerospace Vehicles Rigid-body dynamics and kinematics. Attitude representations. Mathematical models of fixed-wing aircraft, spacecraft, and VTOL vehicles. Trim conditions and linearized models for control design.
   
3. Flight-Control Design. Attitude control. Linear-quadratic regulation. Dynamic inversion. Model-following control. Gain scheduling. Backstepping methods. Adaptive flight control.
   
4. Advanced Flight-Control Architectures. Hierarchical control of VTOL vehicles. Control allocation for over-actuated systems. Robust and adaptive flight-control architectures. Control reconfiguration.

Readings/Bibliography

Lecture notes

Andrea Serrani, Lecture Notes on Advanced Flight Control Systems Design, 2026.

Lecture notes covering selected topics will be made available to the students. These notes are intended to complement the lectures and should not be considered a substitute for the recommended textbooks.

Primary references

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

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

Supplementary references

Kellett, C. M., & Braun, P., Introduction to Nonlinear Control: Stability, Control Design, and Estimation, Princeton University Press, 2023.

Isidori, A., Marconi, L., & Serrani, A., Robust Autonomous Guidance: An Internal Model Approach, Springer, 2003.

Selected journal articles

Kaminer, I., Pascoal, A., Hallberg, E., & Silvestre, C., "Trajectory Tracking for Autonomous Vehicles: An Integrated Approach to Guidance and Control," Journal of Guidance, Control, and Dynamics, 1998.

Roberts, A., & Tayebi, A., "Adaptive Position Tracking of VTOL UAVs," IEEE Transactions on Robotics, 2009.

Hua, M., Hamel, T., & Samson, C., "Feedback Control of Underactuated VTOL Vehicles," IEEE Control Systems Magazine, 2013.

Lane, S. H., & Stengel, R. F., "Flight Control Design Using Nonlinear Inverse Dynamics," Automatica, 1988.

Bodson, M., "Evaluation of Optimization Methods for Control Allocation," Journal of Guidance, Control, and Dynamics, 2002.

Johansen, T. A., & Fossen, T. I., "Control Allocation—A Survey," Automatica, 2013.

Teaching methods

The course consists of in-person lectures complemented by worked examples, case studies, and classroom discussions. Use is made of MATLAB® and Simulink® for analysis, simulation, and controller design.

Assessment methods

The assessment of the student's proficiency consists of an individual or group final design project (depending on the class size) and an individual comprehensive oral examination. There are no intermediate examinations.

The project is intended to assess the student's ability to formulate, analyze, and solve realistic guidance and control problems using the theoretical methods presented during the course. Depending on the assigned aerospace vehicle configuration, students may be required to:

• derive a mathematical model suitable for control-system design;
• implement the model in MATLAB®/Simulink®;
• determine equilibrium (trim) conditions corresponding to prescribed operating points;
• derive linearized models around equilibrium conditions;
• design linear, gain-scheduled, nonlinear, or adaptive controllers satisfying given performance specifications;
• validate the proposed control architecture through numerical simulation;
• analyze the closed-loop performance and discuss the limitations of the adopted design.

Projects may be assigned either incrementally during the semester or as a single comprehensive assignment. Incremental assignments are intended to encourage continuous progress and provide students with the opportunity to progressively develop a complete flight-control system. Although intermediate submissions are not formally graded, students are encouraged to discuss their work during office hours and receive feedback throughout the semester.

The oral examination consists of two complementary parts.

During the first part, students are asked to discuss the project and the corresponding design choices. Questions are intended to verify the student's understanding of the adopted modeling assumptions, the rationale underlying the selected control architecture, the interpretation of the simulation results, and the individual contribution to the project whenever the work has been carried out in groups. Students may also be asked to propose alternative design solutions or discuss possible extensions of the developed controller.

The second part consists of questions covering the theoretical topics presented during the course that were not directly addressed during the project discussion. These questions assess the student's understanding of the mathematical foundations of guidance and control, the ability to compare alternative design methodologies, and the capability to select appropriate techniques for different classes of aerospace control problems. Questions may involve analytical derivations, conceptual discussions, interpretation of simulation or experimental results, and critical comparison between different control strategies.

The final grade reflects the student's overall level of proficiency demonstrated throughout the assessment. In particular, the evaluation considers:

• correctness and rigor of the mathematical developments;
• ability to formulate engineering problems using appropriate mathematical models;
• effectiveness of the proposed guidance and control design;
• capability to interpret and critically discuss simulation results;
• depth of understanding of the theoretical concepts;
• clarity, precision, and technical accuracy of the presentation, including the appropriate use of engineering terminology and mathematical notation.

Students are expected not only to apply established design procedures, but also to justify their modeling assumptions, motivate their design decisions, and critically evaluate the advantages and limitations of the adopted methodologies. Particular emphasis is placed on the ability to integrate concepts from different parts of the course into a coherent engineering solution.

The examination is conducted entirely in English. Students are expected to demonstrate not only technical proficiency but also the ability to communicate engineering concepts effectively using appropriate scientific terminology.

Active participation during lectures and recitation sessions is strongly encouraged, although attendance does not directly contribute to the final grade.

Teaching tools

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

Office hours

See the website of Andrea Serrani