MPC course applied to satellites
About our
The MPC Applied to Satellites course focuses on the application of Model Predictive Control (MPC) in the design and operation of satellite systems. Advanced control strategies for satellite guidance and stabilization are explored, considering physical limitations and mission requirements. The course covers the development of accurate mathematical models, trajectory optimization, and resource management, including orbital perturbation analysis and power management. Participants will acquire skills in implementing MPC algorithms, simulations, and performance evaluation in realistic scenarios, optimizing the efficiency and durability of space missions. This course provides essential tools for control engineers, satellite designers, and systems analysts, preparing them to meet the challenges of the space age by improving the accuracy and reliability of on-orbit operations. Case studies and practical exercises are included to solidify knowledge of orbital dynamics, satellite kinematics, and telemetry, using specialized simulation and modeling software.
MPC course applied to satellites
- Format: Hybrid
- Duration: 3 months
- Hours: 300 H
- Language: English / Spanish
- Registration date: 23-10-2026
- Start date: 12-12-2026
- Available places: 2
399 $
Competencies and results
What you will learn
1. MPC Mastery for Satellites: Trajectory, Control and Optimization
Here is the requested content:
Understand the architecture and operation of satellites, including key subsystems such as the platform, payload, and power systems.
Master the fundamental concepts of Model Predictive Control (MPC) and its application to satellite attitude and orbit control.
Learn to model satellite dynamics and perturbations, including Earth’s gravity, solar pressure, and atmospheric drag.
Develop skills to design and simulate MPC controllers for satellites, considering actuator and sensor constraints.
Optimize satellite orbital trajectories using MPC techniques, including maneuver planning and fuel management.
Analyze and evaluate the performance of MPC controllers, including stability, accuracy, and robustness to perturbations.
Gain practical experience using simulation and analysis software for the design and validation of MPC control systems for satellites.
Study real-world case studies of MPC applications in space missions, including Earth observation, communications, and navigation satellites.
Explore future trends in satellite control with MPC, including artificial intelligence, machine learning, and distributed control.
Apply the acquired knowledge to practical projects, such as simulating a satellite’s trajectory, designing an MPC controller, or optimizing a space mission.
2. Analysis and Improvement of the Performance of Satellite Systems with MPC
Here’s a summary of what you’ll learn in the course “Analysis and Performance Improvement of Satellite Systems with MPC”:
1. In-depth Modeling and Simulation of Satellite Systems:
* Master the use of Model Predictive Control (MPC) for performance optimization.
* Learn to model orbital dynamics and satellite attitude.
* Simulate complex operating scenarios, including environmental disturbances.
2. Application of MPC for Attitude and Orbit Control:
* Design robust MPC controllers for satellite attitude stabilization.
* Implement control strategies for orbit correction and maintenance.
* Optimize fuel consumption and satellite lifespan using MPC.
3. Analysis and Mitigation of Disturbances and Limitations:
* Identify and analyze the main sources of disturbances (e.g., gravitational gradient, solar pressure). * Develop control strategies to compensate for the effects of disturbances.
* Consider limitations of actuators and sensors in the MPC controller design.
4. Validation and Experimentation:
* Simulate the MPC controller’s performance in realistic environments.
* Evaluate the controller’s robustness and stability against parameter variations.
* Interpret simulation results and adjust the controller design.
5. Implementation and Practical Considerations:
* Learn to implement MPC controllers on satellite hardware.
* Understand real-time considerations and computational limitations.
* Analyze case studies of real satellite missions and MPC applications.
3. Comprehensive user-oriented design and validation (from modeling to manufacturing)
You will learn to integrate the entire product development process, from initial model conception to final validation, applying user-centered methodologies. You will develop skills in parametric design, ergonomics, simulation, sustainable materials, 3D visualization, and manufacturing management, ensuring efficient, safe solutions that meet current industry standards.
4. Predictive Control with MPC: Simulations, Design and Satellite Validation
4. Predictive Control with MPC: Simulations, Design, and Satellite Validation
- Fundamentals of Predictive Control (MPC): Understand the basic principles, architecture, and advantages of MPC in control systems.
- System Modeling for MPC: Learn to develop accurate models of dynamic systems, including model identification and the selection of relevant variables.
- MPC Controller Design: Master the techniques for designing MPC controllers, including formulating the optimization problem, selecting prediction and control horizons, and managing constraints.
- MPC Simulation: Use simulation tools to evaluate the performance of MPC controllers in different scenarios, including stability and robustness analysis.
- MPC Implementation: Explore the practical considerations for implementing MPC on hardware and software platforms, including selecting optimization algorithms and managing computational complexity.
- Applications of MPC in Satellite Systems: Study case studies of MPC in attitude control, navigation, and power management in satellites.
- Validation of MPC: Learn to validate the performance of MPC controllers through simulation and test bench testing.
- Optimization of Orbits and Trajectories: Apply MPC to optimize satellite trajectories, considering fuel, time, and safety constraints.
- Design and Analysis of Satellite Control Systems: Integrate MPC with other control algorithms to design complete and efficient satellite control systems.
- Development of Practical Projects: Participate in practical projects involving the simulation, design, and validation of MPC controllers for satellite applications.
5. MPC Control in Orbit: Design, Simulation and Satellite Application
5. MPC Control in Orbit: Design, Simulation, and Satellite Application
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Fundamentals of Model Predictive Control (MPC): Understanding the key principles, mathematical formulation, and essential elements of MPC.
- Satellite System Modeling: Acquiring skills to model satellite orbital and attitude dynamics, including perturbations and constraints.
- MPC Controller Design: Learning to design MPC controllers specific to satellite applications, including horizon selection, cost functions, and constraints.
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Simulation and Validation: Developing the ability to simulate the performance of MPC controllers in complex orbital environments and validate their effectiveness.
- Satellite Applications: Exploring practical applications of MPC in navigation, attitude control, orbit optimization, and other key satellite tasks.
- Implementation and Practical Considerations: Understand the practical considerations for implementing MPC controllers in satellite hardware, including real-time computing and resource management.
- Software Tools: Become familiar with specialized software tools for the design, simulation, and implementation of MPC controllers for satellites.
- Stability and Robustness Analysis: Acquire the ability to analyze the stability and robustness of MPC controllers in the presence of uncertainties and disturbances.
- Orbital Trajectory Optimization: Learn how to use MPC to optimize satellite orbital trajectories, considering fuel, time, and maneuvering constraints.
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Case Studies: Analyze real-world case studies and examples of successful MPC applications in satellite missions.
6. Implementation of MPC in Satellites: Modeling, Control and Performance
6. Implementation of Predictive Control Modeling (PCM) in Satellites: Modeling, Control, and Performance
- Fundamentals of Predictive Control Modeling (PCM) and its application in satellite systems.
- Development of accurate mathematical models for satellite dynamics, including orbital kinematics and dynamics.
- Design and implementation of PCM algorithms for satellite attitude and orbit control, considering constraints and perturbations.
- Analysis of PCM performance in simulated scenarios, evaluating accuracy, robustness, and computation time.
- Advanced techniques for optimizing PCM performance, such as control horizon selection and reduction of computational complexity.
- Application of PCM to different satellite subsystems, such as power control, thermal control, and propulsion management.
- Study of limitations
- MPC and alternatives for satellite control in complex situations.
- Integration of MPC with other satellite control and management systems.
- Evaluation of the feasibility and benefits of MPC in real space missions.
- Case studies and practical examples of MPC implementation in satellites.
Who this program is for:
MPC course applied to satellites
- Graduates in Aerospace Engineering, Mechanical Engineering, Industrial Engineering, Automation Engineering, or related fields.
- Professionals in OEM rotorcraft/eVTOL, MRO, consulting, and technology centers.
- Flight Testing, certification, avionics, control, and dynamics seeking specialization.
- Regulators/authorities and UAM/eVTOL professionals requiring compliance skills.
Recommended requirements: foundation in aerodynamics and control and structures; ES/EN B2+/C1. We offer bridging tracks if you need them.
- Standards-driven curriculum: you will work with CS-27/CS-29, DO-160, DO-178C/DO-254, ARP4754A/ARP4761, ADS-33E-PRF from the first module.
- Accreditable laboratories (EN ISO/IEC 17025) with rotor bench, EMC/Lightning pre-compliance, HIL/SIL, vibrations/acoustics.
- Evidence-oriented TFM: safety case, test plan, compliance dossierand operational limits.
- Mentored by industry: teachers with experience in rotorcraft, tiltrotor, eVTOL/UAM and flight test.
- Flexible modality (hybrid/online), international cohorts and support from SEIUM Career Services.
- Ethics and security: safety-by-design approach, cyber-OT, DIH and compliance as pillars.
1.1 Introduction to Predictive Control (MPC) in satellite systems.
1.2 Fundamentals of orbital dynamics and satellite kinematics.
1.3 Mathematical modeling of satellite trajectories.
1.4 Design of MPC controllers for trajectory tracking.
1.5 Optimization of satellite trajectories with MPC.
1.6 Constraints and limitations in satellite control.
1.7 Simulation and analysis of system response.
1.8 Implementation of MPC in satellite flight simulators.
1.9 Optimization techniques for real-time MPC.
1.10 Case studies: Applications of MPC in specific satellite missions.
2.2 Satellite System Modeling: Orbital Dynamics and Perturbations
3.2 Parameter Identification and State Estimation in Satellite Systems
4.3 Performance Analysis: Key Metrics and KPIs for Satellites
5.4 Performance Optimization: Strategies to Improve Satellite Performance
6.5 Sensitivity Analysis: Impact of Parameters on Performance
7.6 Validation and Verification: Techniques to Ensure Satellite Performance
8.7 Simulations and Testing: Tools to Evaluate System Performance
9.8 Failure Analysis: Identification and Mitigation of Potential Failures
20.9 Life Cycle Assessment: Long-Term Performance and Sustainability
22.20 Case Studies: Analysis of Real Satellite Systems
3.3 Introduction to MPC Implementation in Space Systems
3.2 Modeling Satellite Systems for MPC
3.3 Designing the MPC Controller for Satellites
3.4 Parameter Selection and MPC Tuning
3.5 Implementing the MPC in Simulation Environments
3.6 Validating the MPC in Orbit Simulations
3.7 Implementing the MPC in Hardware: Considerations
3.8 Testing and Evaluating MPC Performance in the Laboratory
3.9 Integrating the MPC into the Attitude Control Subsystem
3.30 Case Studies: MPC Implementation in Satellite Missions
4.4 Satellite System Modeling for MPC Simulation
4.2 Design of Satellite Simulations for MPC
4.3 Selection and Configuration of Simulation Software
4.4 Validation of Satellite Models
4.5 Design of MPC Controllers for Satellite Systems
4.6 Simulation of Satellite Control Scenarios with MPC
4.7 Stability and Performance Analysis of MPC Controllers
4.8 Verification of Satellite Requirements and Specifications
4.9 Optimization Techniques in MPC Simulation and Design
4.40 Case Study: Validation of an MPC Controller on a Real Satellite
5.5 Fundamentals of Orbital Mechanics and Satellite Trajectories
5.5 Mathematical Modeling of Satellite Dynamics
5.3 Introduction to Predictive Control (MPC) Applied to Space Systems
5.4 Design of MPC Controllers for Satellite Trajectories
5.5 Trajectory Optimization with MPC
5.6 Simulation and Performance Analysis of MPC Control
5.7 Practical Implementation of MPC in Satellite Simulations
5.8 Case Studies: MPC Applications in Satellite Missions
5.5 Review of MPC Fundamentals in Satellite Systems
5.5 Performance Analysis Techniques: Metrics and KPIs
5.3 Identification and Mitigation of Limitations in MPC Performance
5.4 Optimization of MPC Performance through Parameter Tuning
5.5 Sensitivity and Robustness Analysis in Satellite Systems with MPC
5.6 Simulation Tools for Performance Analysis
5.7 Case Studies: Performance Improvement in Different Missions
5.8 Comparative Evaluation of MPC vs. Classical Control
3.5 Review of Predictive Control (MPC) for Satellites
3.5 Hardware and Software Considerations for MPC Implementation
3.3 Design and Implementation of an Embedded MPC Control System
3.4 Integration of MPC into a Satellite Architecture
3.5 Verification and Validation of MPC Software
3.6 Implementation Testing in Simulation Environments
3.7 Safety and Reliability Considerations in MPC
3.8 Deployment and Operation of Satellite Systems with MPC
4.5 Review of MPC Principles and Fundamentals
4.5 Development of Dynamic Models for Satellite Simulation
4.3 Simulation of Satellite Systems using MPC
4.4 Design of Constraint-Based MPC Controllers
4.5 Validation of MPC Controllers Through Simulation
4.6 General-Purpose Simulation Tools for MPC
4.7 MPC Performance Analysis in Simulations
4.8 Design and Simulation of Satellite Mission Case Studies
5.5 Review of MPC Concepts and Their Orbital Application
5.5 Design of MPC Controllers for Orbital Attitude Control
5.3 Design of MPC Controllers for Orbital Position Control
5.4 Simulation of MPC Performance in Orbital Environments
5.5 Stability and Robustness Analysis in Orbital Systems
5.6 Implementation and Tuning of MPC in Orbital Simulations
5.7 MPC Applications in Different Types of Satellite Missions
5.8 Case Study: MPC Control in High-Precision Missions
6.5 Review of MPC Fundamentals for Space Systems
6.5 Dynamic Satellite Modeling for MPC
6.3 Design of MPC Controllers with Restrictions
6.4 Implementation of MPC in Real-Time Systems
6.5 Stability and Performance Analysis
6.6 MPC Performance Optimization
6.7 Case Studies: Applications in Specific Missions
6.8 Validation and Verification of the MPC Control System
7.5 Review of Predictive Control (MPC) Concepts
7.5 Advanced Modeling Techniques for Satellite Systems
7.3 Optimization Methods for Satellite Control
7.4 Trajectory and Control Optimization
7.5 Practical Applications of MPC in Satellite Missions
7.6 Case Studies: Control Optimization in Missions
7.7 Design and Simulation of Control Systems
7.8 Evaluation of MPC Robustness and Performance
8.5 Review of Dynamic Modeling Concepts
8.5 Advanced Modeling Techniques for Satellites
8.3 Simulation of Satellite Systems with MPC
8.4 Design of Advanced MPC Controllers
8.5 Implementation of Advanced MPC in Simulations
8.6 Performance and Stability Analysis
8.7 Practical Applications of Advanced MPC
8.8 Case Studies and Future Applications
6.6 Fundamentals of Satellite Trajectory: Orbits, perturbations, and orbital elements.
6.2 Dynamic Modeling of Satellites: Equations of motion and rotational dynamics.
6.3 Introduction to Predictive Control (PCC): Concepts, principles, and advantages.
6.4 Design of the PCC Controller for Satellites: Problem formulation, objective functions.
6.5 Implementation of PCC: Hardware, software, and real-time considerations.
6.6 Trajectory Optimization: Strategies and algorithms.
6.7 Case Studies: Applications of PCC in satellite control.
6.8 Simulation and Validation: Testing and performance analysis.
6.9 Attitude and Orbit Control: Design and application of PCC.
6.60 Deployment of Solar Panels and Antennas: Predictive control strategies.
2.6 Satellite Performance Metrics: Definition and analysis of key indicators.
2.2 Satellite System Modeling: Creation of models for simulation.
2.3 Scenario Simulation: Impact of MPC in different operational scenarios.
2.4 System Response Analysis: Evaluation of stability and robustness.
2.5 Identification of Weak Points: Problem detection and optimization.
2.6 Performance Optimization: Parameter and strategy adjustment.
2.7 Data Analysis: Information collection and processing.
2.8 Results Validation: Comparison with real and simulated data.
2.9 Case Studies: Performance analysis with different configurations.
2.60 Reporting: Documentation and communication of results.
3.6 Space System Architecture: Platforms and subsystems.
3.2 Hardware and Software Considerations: Selection and configuration. 3.3 Real-Time MPC Implementation: Design and Programming
3.4 MPC Controller Fine-Tuning: Parameter Tuning and Optimization
3.5 Integration Testing: Verification of System Functionality
3.6 Validation in Simulated Environments: Comprehensive Testing
3.7 Safety Considerations: Protection Against Failures and Errors
3.8 Upgrading and Maintenance: Strategies for System Management
3.9 Case Studies: Practical Experiences and Lessons Learned
3.60 Documentation and Reporting: Creation and Management of Technical Documentation
4.6 Simulation Fundamentals: Tools and Techniques
4.2 MPC Controller Design: Formulation and Optimization
4.3 Satellite System Modeling: Dynamics and Constraints
4.4 Simulation Implementation: Environments and Software 4.5 Design Validation: Stability and Performance Analysis.
4.6 Design of Experiments: Planning and Execution.
4.7 Results Analysis: Data Interpretation and Conclusions.
4.8 Hardware-in-the-Loop (HIL) Design: Realistic Testing.
4.9 Case Studies: Design and Simulation in Different Scenarios.
4.60 Reporting: Documentation and Effective Communication.
5.6 Orbit Design: Trajectory Selection and Optimization.
5.2 Modeling of Systems in Orbit: Dynamics and Perturbations.
5.3 Formulation of the MPC for Orbital Control: Design and Optimization.
5.4 Simulation and Validation: Testing in Simulated Environments.
5.5 Hardware Implementation: Considerations and Challenges.
5.6 Practical Application: Attitude and Orbit Control. 5.7 Constraint Management: Physical and operational limitations.
5.8 Case Studies: Applications in different missions.
5.9 Sensitivity Analysis: Robustness assessment.
5.60 Results Presentation: Documentation and communication.
6.6 Satellite Modeling: Creation of accurate models.
6.2 MPC Controller Design: Formulation and optimization.
6.3 MPC Implementation: Hardware and software.
6.4 Performance Analysis: Evaluation of key metrics.
6.5 System Optimization: Parameter and strategy tuning.
6.6 Constraint Management: Design considerations.
6.7 Case Studies: Applications in different satellite missions.
6.8 Testing and Validation: Functional verification.
6.9 Safety Considerations: Failures and errors.
6.60 Documentation and Reporting: Presentation and communication.
7.6 Optimization Fundamentals: Methods and Algorithms
7.2 Application of MPC: Controller Design and Tuning
7.3 Satellite System Modeling: Dynamics and Constraints
7.4 Practical Applications: Attitude and Orbit Control
7.5 Performance Optimization: Parameter Tuning and Strategies
7.6 Case Studies: Applications in Real Missions
7.7 Simulation and Validation: Testing and Analysis
7.8 Experimental Design: Planning and Execution
7.9 Results Analysis: Interpretation and Conclusions
7.60 Reporting: Documentation and Communication
8.6 Advanced Modeling: Techniques and Tools
8.2 Satellite System Simulation: Environments and Software
8.3 MPC Design: Formulation and Optimization 8.4 Advanced Predictive Control: Strategies and Algorithms
8.5 Applications in Real-World Missions: Case Studies
8.6 MPC Integration: Hardware and Software
8.7 Performance Optimization: Analysis and Improvement
8.8 Scenario Simulation: Testing and Validation
8.9 Results Analysis: Interpretation and Conclusions
8.60 Reporting: Documentation and Communication
- Hands-on methodology: test-before-you-trust, design reviews, failure analysis, compliance evidence.
- Software (depending on licenses/partners): MATLAB/Simulink, Python (NumPy/SciPy), OpenVSP, SU2/OpenFOAM, Nastran/Abaqus, AMESim/Modelica, acoustics tools, planning toolchains DO-178C.
- SEIUM Laboratories: scale rotor bench, vibrations/acoustics, EMC/Lightning pre-compliance, HIL/SIL for AFCS, data acquisition with strain gauging.
- Standards and compliance: EN 9100, 17025, ISO 27001, GDPR.
Capstone-type projects
Admissions, fees, and scholarships
- Profile: Background in Computer Engineering, Mathematics, Statistics, or related fields; practical experience in NLP and valued information retrieval systems.
- Documentation: Updated CV, academic transcript, SOP/statement of purpose, project examples or code (optional).
- Process: Application → Technical evaluation of profile and experience → Technical interview → Review of case studies → Final decision → Enrollment.
- Fees:
- Single payment: 10% discount.
- Payment in 3 installments: No fees; 30% upon registration + 2 equal monthly payments of the remaining 35%.
Monthly payment: available with a 7% commission on the total; annual review.
Scholarships: based on academic merit, financial need, and promoting inclusion; agreements with companies in the sector for partial or full scholarships.
See “Calendar & Calls for Applications,” “Scholarships & Grants,” and “Fees & Financing” in the SEIUM mega-menu.
Do you have any questions?
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F. A. Q
Frequently asked questions
Yes, we have international certification
Yes: experimental models, real data, applied simulations, professional environments, real case studies.
It is not mandatory. We offer leveling tracks and tutoring.
Completely. It covers e-propulsion, integration, and emerging regulations (SC-VTOL).
Recommended. There are also internal challenges and consortiums.
Yes. Online/hybrid modality with planned labs and visa support (see “Visa & Residence”).