| name | MPC Controller Skill |
| description | Expert skill for Model Predictive Control implementation and tuning |
| slug | mpc-controller |
| category | Control |
| allowed-tools | ["Bash","Read","Write","Edit","Glob","Grep"] |
| graph | {"domains":["domain:robotics"],"specializations":["specialization:robotics-simulation"],"skillAreas":["skill-area:motion-planning","skill-area:sensor-fusion"],"roles":["role:research-engineer"]} |
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