FORCESPRO User Manual

• 1. Introduction
  • 1.1. Troubleshooting and support
  • 1.2. Licensing
  • 1.3. Citing FORCESPRO
  • 1.4. Product Life Cycle
  • 1.5. Release Notes
  • 1.6. Version history of manual
• 2. License Variants
  • 2.1. Variant Summary
  • 2.2. Variant S
  • 2.3. Variant M
  • 2.4. Variant L
• 3. Installation
  • 3.1. Obtaining FORCESPRO
  • 3.2. Installation of the MATLAB Client
  • 3.3. Installation of the Python Client
• 4. Backward Compatibility
  • 4.1. Determining Client Version
  • 4.2. Changes from Version 6.3.0
  • 4.3. Changes from Version 6.2.0
  • 4.4. Changes from Version 6.1.0
  • 4.5. Changes from Version 6.0.0
  • 4.6. Changes from Version 5.0.1
  • 4.7. Changes from Version 5.0.0
  • 4.8. Changes from Version 4.3.0
  • 4.9. Changes from Version 4.2.0
  • 4.10. Changes from Version 4.1.0
• 5. Y2F Interface
  • 5.1. Installing Y2F
  • 5.2. Generating a solver
  • 5.3. Calling the solver
  • 5.4. Solver info
  • 5.5. Performance
  • 5.6. Examples
• 6. MathWorks Linear MPC Plugin
  • 6.1. Different types of solvers
  • 6.2. Different algorithms
  • 6.3. Generating a QP solver from an MPC object
  • 6.4. Solving a QP from MPC online data
  • 6.5. Using the FORCESPRO MPC Simulink block
  • 6.6. Deploy to dSPACE MicroAutoBox II using the FORCESPRO MPC Simulink block
  • 6.7. Examples
• 7. MathWorks Nonlinear MPC Plugin
  • 7.1. Introduction
  • 7.2. The SQP Fast algorithm for nlmpc
  • 7.3. Defining a nonlinear model
  • 7.4. Generating an NLP solver
  • 7.5. Simulation in MATLAB and Simulink
  • 7.6. Code generation in MATLAB and Simulink
  • 7.7. Examples
• 8. Low-level interface
  • 8.1. Supported problem class
  • 8.2. Multistage struct
  • 8.3. Dimensions
  • 8.4. Cost function
  • 8.5. Equality constraints
  • 8.6. Lower and upper bounds
  • 8.7. Polytopic constraints
  • 8.8. Quadratic constraints
  • 8.9. Binary constraints
  • 8.10. Declaring parameters
  • 8.11. Declaring Solver Outputs
  • 8.12. Generating the solver
  • 8.13. Calling the generated low-level solver
  • 8.14. Debugging a formulation
  • 8.15. The QP_FAST algorithm
  • 8.16. Condensing (automatic state elimination)
• 9. High-level Interface
  • 9.1. Supported problems
  • 9.2. Expressing the optimization problem in code
  • 9.3. Generating a solver
  • 9.4. Calling the solver
  • 9.5. External function evaluations in C
  • 9.6. Calling the nonlinear functions from MATLAB or Python
  • 9.7. Mixed-integer nonlinear solver
  • 9.8. Sequential quadratic programming algorithm
  • 9.9. Differences between the MATLAB and the Python client
  • 9.10. Examples
• 10. Simulating your custom controller in Simulink®
  • 10.1. The S-Function interface
  • 10.2. The Coder interface
  • 10.3. S-Function vs Coder interface
  • 10.4. FORCESPRO Simulink® blocks
• 11. Examples
  • 11.1. How to
  • 11.2. Y2F interface: Basic example
  • 11.3. Y2F interface: Trajectory Optimization for Quadrotor Flight
  • 11.4. Low-level interface: Active Suspension Control
  • 11.5. Low-level interface: Robust estimation (Kalman filter)
  • 11.6. Low-level interface: Spacecraft Rendezvous
  • 11.7. Low-level interface: DC/DC converter
  • 11.8. High-level interface: Basic example
  • 11.9. High-level interface: Obstacle avoidance (MATLAB & Python)
  • 11.10. High-level interface: Indoor localization (MATLAB & Python)
  • 11.11. High-level interface: Path tracking example (MATLAB)
  • 11.12. High-level interface: Legacy path tracking example (MATLAB & Python)
  • 11.13. High-level interface: Rate Constraints
  • 11.14. High-level interface: Soft Constraints
  • 11.15. Controlling a crane using a FORCESPRO NLP solver
  • 11.16. Real-time SQP Solver: Robotic Arm Manipulator (MATLAB & Python)
  • 11.17. Controlling a DC motor using a FORCESPRO SQP solver
  • 11.18. Mixed-integer nonlinear solver: F8 Crusader aircraft
  • 11.19. High-level interface: Optimal EV charging and speed profile example (MATLAB & PYTHON)
  • 11.20. High-level interface: Extended optimal EV charging and speed profile example using a 2D motor efficiency map (MATLAB & PYTHON)
• 12. Parametric problems
  • 12.1. Defining parameters
  • 12.2. Example
  • 12.3. Parametric Quadratic Constraints
  • 12.4. Diagonal Hessians
  • 12.5. Sparse Parameters
  • 12.6. Special Parameters
  • 12.7. Python: Column vs Row Major Storage Format
• 13. Code Deployment
  • 13.1. Main Targets
  • 13.2. dSPACE MicroAutoBox II, AutoBox, MicroLabBox
  • 13.3. dSPACE MicroAutoBox III, SCALEXIO
  • 13.4. Speedgoat
  • 13.5. Speedgoat QNX
• 14. Multicore parallelization
  • 14.1. Internal parallelism
  • 14.2. External parallelism
  • 14.3. Combining external and internal parallelism
• 15. Licensing
  • 15.1. Machine Identification
  • 15.2. Static License
  • 15.3. License Files
  • 15.4. Floating Licenses
• 16. Autotuner
  • 16.1. Autotuner Options
  • 16.2. Collecting Tuning Data
  • 16.3. Validation
• 17. Solver Options
  • 17.1. Default options
  • 17.2. General options
  • 17.3. High-level interface options
  • 17.4. Convex branch-and-bound options
  • 17.5. Solve methods
• 18. Exitflags
  • 18.1. Exitflags and quality of the result
  • 18.2. Mixed integer Nonlinear Programming exitflags
• 19. Modelling Utilities
  • 19.1. Interpolations 1D (e.g. splines)
  • 19.2. Interpolations 2D (B-splines)
  • 19.3. Smooth Approximations
• 20. Dumping Problem Formulation and Data
  • 20.1. Why to use the dump tool?
  • 20.2. How to use the dump tool?
• 21. Webcompilers
  • 21.1. Webcompilers in FORCESPRO
  • 21.2. Webcompilers versioning
  • 21.3. Ensuring use of webcompiler version
• 22. Frequently asked questions
  • 22.1. Features of FORCESPRO
  • 22.2. Setting up a FORCESPRO problem formulation
  • 22.3. Issues during code generation
  • 22.4. Issues when running a generated solver
  • 22.5. Issues when using the Simulink interface
  • 22.6. Issues during code deployment
  • 22.7. Other topics