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MPC Configurator Skill

Model Predictive Control configuration skill for MPC model identification, tuning, and implementation

Installable skillMITBy a5c-aiUpdated Oct 30, 2026
INTENDED FORClaude CodeCodexOpenClawCursorInstall in a listed agent.

instructions.md

---
name: mpc-configurator-2346098dded4
description: Model Predictive Control configuration skill for MPC model identification, tuning, and implementation
allowed-tools:
  - Read
  - Write
  - Glob
  - Grep
  - Edit
  - Bash
metadata:
  specialization: chemical-engineering
  domain: science
  category: Process Control
  skill-id: CE-SK-021
graph:
  domains: [domain:chemical-engineering]
  skillAreas: [skill-area:mathematical-reasoning, skill-area:physics-simulation, skill-area:dynamic-programming]
  workflows: [workflow:experiment-design]
  roles: [role:research-engineer, role:systems-integration-engineer]
---

# MPC Configurator Skill

## Purpose

The MPC Configurator Skill supports Model Predictive Control implementation including model identification, controller configuration, and performance tuning.

## Capabilities

- Step test design and execution
- Dynamic model identification
- MPC model validation
- CV/MV/DV selection
- Constraint configuration
- Objective function tuning
- Prediction/control horizon selection
- Move suppression tuning
- Performance monitoring

## Usage Guidelines

### When to Use
- Implementing new MPC applications
- Retuning existing MPC controllers
- Identifying process models
- Optimizing MPC performance

### Prerequisites
- Regulatory control stable
- Step test data available
- Process constraints identified
- Economic objectives defined

### Best Practices
- Ensure quality step test data
- Validate models thoroughly
- Start with conservative tuning
- Monitor controller performance

## Process Integration

This skill integrates with:
- Model Predictive Control Implementation
- Control Strategy Development
- PID Controller Tuning

## Configuration

```yaml
mpc-configurator:
  platforms:
    - DMCplus
    - RMPCT
    - Pavilion
    - Honeywell-RMPCT
  identification-methods:
    - step-response
    - subspace
    - prediction-error
```

## Output Artifacts

- Process models
- Controller configuration
- Tuning parameters
- Validation reports
- Performance metrics

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Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.