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mpc-configurator

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

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updated:March 4, 2026
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SKILL.md Frontmatter
namempc-configurator
descriptionModel Predictive Control configuration skill for MPC model identification, tuning, and implementation
allowed-toolsRead,Write,Glob,Grep,Edit,Bash
metadata[object Object]

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

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