MPC Controller Skill
Expert skill for Model Predictive Control implementation and tuning
Best use case
MPC Controller Skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Expert skill for Model Predictive Control implementation and tuning
Teams using MPC Controller Skill should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/mpc-controller/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How MPC Controller Skill Compares
| Feature / Agent | MPC Controller Skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Expert skill for Model Predictive Control implementation and tuning
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# MPC Controller Skill ## Overview Expert skill for designing, implementing, and tuning Model Predictive Controllers for robotic systems, including both linear and nonlinear MPC. ## Capabilities - Derive kinematic and dynamic robot models - Formulate MPC optimization problems (QP, NLP) - Configure CasADi for symbolic differentiation - Set up ACADO code generation for real-time MPC - Implement constraint handling (velocity, acceleration, collision) - Configure cost function weights (tracking, control effort) - Implement warm starting for fast convergence - Set up NMPC for nonlinear systems - Configure terminal constraints and costs - Optimize solver parameters for real-time execution ## Target Processes - mpc-controller-design.js - trajectory-optimization.js - dynamic-obstacle-avoidance.js - path-planning-algorithm.js ## Dependencies - CasADi - ACADO Toolkit - OSQP - qpOASES - Ipopt ## Usage Context This skill is invoked when processes require advanced model-based control, trajectory tracking with constraints, or real-time optimization-based control strategies. ## Output Artifacts - MPC formulation code - CasADi symbolic models - ACADO generated code - QP/NLP solver configurations - Cost function tuning parameters - Constraint specifications
Related Skills
labview-instrument-controller
LabVIEW instrument control skill for DAQ systems, hardware integration, and real-time data acquisition
plasma-etch-controller
Plasma etching skill for anisotropic nanostructure patterning with selectivity and profile control
nanoimprint-process-controller
Nanoimprint Lithography skill for high-throughput nanopatterning with template management and demolding optimization
fib-mill-controller
Focused Ion Beam milling skill for site-specific nanofabrication and cross-section preparation
ebl-process-controller
Electron Beam Lithography skill for high-resolution nanopatterning with dose optimization and proximity effect correction
dsa-process-controller
Directed Self-Assembly skill for block copolymer lithography and nanoparticle templating
cvd-pvd-process-controller
Chemical/Physical Vapor Deposition skill for thin film and nanostructure deposition optimization
cleanroom-metrology-controller
Nanofabrication metrology skill for process control with CD-SEM, ellipsometry, and profilometry
ald-process-controller
Atomic Layer Deposition skill for conformal thin film deposition with atomic-level thickness control
fifo-lifo-controller
Automated inventory rotation management skill ensuring proper product flow based on expiration, production, or receipt dates
process-builder
Scaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
babysitter
Orchestrate via @babysitter. Use this skill when asked to babysit a run, orchestrate a process or whenever it is called explicitly. (babysit, babysitter, orchestrate, orchestrate a run, workflow, etc.)