Control Systems / Operations Research Engineer – Constrained Optimization (Python)

Posted last week

Worldwide

Summary

We are building an Open-Loop Advisory mathematical engine for an industrial client. Your objective is to build a constrained Model Predictive Control (MPC) algorithm that optimizes a 4-variable control vector while strictly adhering to two dynamic physical constraints. You will also deliver a fully automated retrain script for scheduled model calibration. You are building the mathematical engine only. To prove you are a human Operations Research engineer, start your proposal with the answer to this exact question: In a constrained Model Predictive Control (MPC) algorithm, if a state variable is rapidly approaching a hard physical constraint, exactly how do you mathematically formulate the penalty in the objective function to prevent a breach without causing severe control-loop oscillation?

  • $8,000.00

    Fixed-price
  • Expert
    Experience Level
  • Remote Job
  • One-time project
    Project Type
Skills and Expertise
Mandatory skills
RESTful API
Python
Operations Research
Activity on this job
  • Proposals:20 to 50
  • Last viewed by client:6 days ago
  • Interviewing:
    0
  • Invites sent:
    0
  • Unanswered invites:
    0
About the client
Member since Nov 29, 2017
  • Switzerland
    Bern2:05 AM
  • $41K total spent
    9 hires, 0 active
  • 2,078 hours
  • Mid-sized company (10-99 people)

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