neqsim-advanced-control-mpc-and-virtual-sensing

neqsim-advanced-control-mpc-and-virtual-sensing is a skill for Claude Code, Codex from equinor/neqsim. It costs 89 tokens per session (3,358 once invoked), scanned A, original, Apache-2.0.

A process-control and measurement toolkit for connecting a process model to controller calculations and estimated measurements. MPC, or model-predictive control, calculates future control moves within limits; a soft sensor estimates a value that is not directly measured.

In plain words
What is it for?
Use it to linearize a process, export controller models, calculate bounded control moves, estimate flow or properties, detect steady state, and reconcile measurements with material balances.
Why use it?
It helps when a plant has limited measurements or needs a controller-facing model, while making clear that estimates are not custody-transfer instruments and the controller is not a full control-room emulator.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to linearize a process, export controller models, calculate bounded control moves, estimate flow or properties, detect steady state, and reconcile measurements with material balances.

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Install with agentmods
npx agentmods add skills/equinor/neqsim/neqsim-advanced-control-mpc-and-virtual-sensing
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add equinor/neqsim --skill neqsim-advanced-control-mpc-and-virtual-sensing
Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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Your own site
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Your own site · 80×15
<a href="https://agentmods.dev/skills/equinor/neqsim/neqsim-advanced-control-mpc-and-virtual-sensing"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-advanced-control-mpc-and-virtual-sensing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,358 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00089 $0.03358
Opus 5.5 $0.00036 $0.01343
Sonnet 5.5 $0.00018 $0.00672
Haiku 4.5 $0.00009 $0.00336

Measured 12d ago against content hash 45fef1161a16, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

neqsim-advanced-control-mpc-and-virtual-sensing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.github/skills/neqsim-advanced-control-mpc-and-virtual-sensing/SKILL.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Advanced Control, MPC, and Virtual Sensing

When to use this

Use this skill when NeqSim's existing dynamic/process model needs a controller-facing model, bounded receding-horizon control, a physics-based soft measurement, or steady-state data reconciliation.

  • ProcessLinkedMPC links configured manipulated, controlled, disturbance, and state variables to one existing ProcessSystem; it identifies local dynamics and computes/apply moves.
  • ProcessLinearizer, StepResponseGenerator, StateSpaceExporter, IndustrialMPCExporter, and SubrModlExporter create model-identification and integration artifacts.
  • ModelPredictiveController is a controller-device implementation with a first-order prediction model, constraints, feed-quality prediction, and optional moving-horizon estimation. It is not a DCS emulator.
  • VirtualFlowMeter and SoftSensor estimate quantities/properties from a stream's fluid and supplied operating conditions. They are screening/model estimates, not custody-transfer instruments.
  • SteadyStateDetector and DataReconciliationEngine screen input data and reconcile measured values against declared linear balance constraints.

Keep each layer distinct: dynamic simulation models process response (neqsim-dynamic-simulation); controllability/operability maps feasible envelopes (neqsim-controllability-operability); calibration and plant-data workflows select and qualify measurements (neqsim-model-calibration-and-data-reconciliation, neqsim-plant-data). Compressor minimum-speed/recycle coordination belongs to neqsim-compressor-antisurge-recycle.

Class map

Class or family Package What it does Key methods verified
ProcessLinkedMPC neqsim.process.mpc Binds MVs/CVs/DVs/SVRs to a ProcessSystem, identifies its model and performs repeated control calculations. Constructor (String, ProcessSystem); addMV, addCV, addCVZone, addDV, addSVR, identifyModel, calculate, applyMoves, getLastMoves, getLinearizationResult, exportModel
ProcessLinearizer, variable classes neqsim.process.mpc Computes local finite-difference gains for configured manipulated/controlled/disturbance variables. ProcessLinearizer(ProcessSystem), addMV, addCV, addDV, linearize, setDefaultPerturbationSize
StepResponseGenerator, StepResponse, NonlinearPredictor, derivative calculator neqsim.process.mpc Builds step-response models, finite-difference process responses, and optional nonlinear prediction inputs. StepResponse constructor and response getters are documented in MPCIntegrationTest; verify a generator method before use
State-space and industrial exporters neqsim.process.mpc Exports local linear model to discrete state-space, Industrial MPC, SubrModl, soft-sensor, and controller data-exchange formats. StateSpaceExporter(LinearizationResult), toDiscreteStateSpace, getA, getB, getC, getD; createIndustrialExporter, createSubrModlExporter
ModelPredictiveController neqsim.process.controllerdevice Standalone first-order, receding-horizon controller device with linear quality constraints and feed disturbance handling. Constructors (), (String); setPredictionHorizon, setControllerSetPoint, setTransmitter, getResponse
Controller benchmarks and metrics/events neqsim.process.controllerdevice Records controller benchmark scenarios, performance metrics, and events for comparative assessment. APIs vary by object; inspect source before assuming metric units or benchmark acceptance
Logic/sequence/transfer-function blocks neqsim.process.controllerdevice Provides logic blocks, sequential function charts, and transfer-function structures. Use their public interfaces and transition/update APIs from source; these are not a plant DCS runtime
Cascade, feed-forward, override, ratio, split-range, minimum-speed recycle neqsim.process.controllerdevice.structure Composes controller outputs for common multiloop, selector, and recycle-coordination patterns. Minimum-speed integration is detailed in neqsim-compressor-antisurge-recycle
VirtualFlowMeter, VFMResult, UncertaintyBounds neqsim.process.measurementdevice.vfm Estimates gas/oil/water rates and simple uncertainty bounds from stream fluid, pressure drop, choke opening, and calibration factor. VirtualFlowMeter(String, StreamInterface), calculateFlowRates, setMeasurementUncertainties; getOilFlowRate, getGasFlowRate, getWaterFlowRate, getQuality, uncertainty getters
SoftSensor neqsim.process.measurementdevice.vfm Estimates supported fluid properties by flashing a cloned stream fluid at supplied P/T. SoftSensor(String, StreamInterface, PropertyType), setInput, setInputs, estimate
SteadyStateDetector, SteadyStateVariable neqsim.process.util.reconciliation Tests incoming variable histories with a sliding-window steady-state detector before reconciliation/calibration. SteadyStateDetector(int), addVariable, updateVariable, evaluate
DataReconciliationEngine, ReconciliationVariable, ReconciliationResult neqsim.process.util.reconciliation Applies weighted least squares to measurement values under caller-defined linear equality balances; reports statistical flags. addVariable, addConstraint(double[]), setGrossErrorThreshold, reconcile; isConverged, getErrorMessage, getVariables, getChiSquareStatistic, getGrossErrors

Read the full file on GitHub · 169 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 169 lines · 89 tokens per session scan A 45fef1161a16

Subscribe to this mod's changes

neqsim-advanced-control-mpc-and-virtual-sensing is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 89 tokens to every session and 3,358 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-05.

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