ReddRadar
Agent skill
MPC Controller Skill
Expert skill for Model Predictive Control implementation and tuning
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/robotics-simulation/skills/mpc-controller
SKILL.md
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
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
a5c-ai/babysitter
gsd-tools
Central utility skill for GSD operations. Provides config parsing, slug generation, timestamps, path operations, and orchestrates calls to other specialized skills. Acts as the unified entry point that the original gsd-tools.cjs provided via its lib/ modules (commands, config, core, init).
a5c-ai/babysitter
model-profile-resolution
Resolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.
a5c-ai/babysitter
verification-suite
Plan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.
a5c-ai/babysitter
state-management
STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.
a5c-ai/babysitter
git-integration
Git commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.
a5c-ai/babysitter
frontmatter-parsing
YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.
Didn't find tool you were looking for?