Advanced Process Control moves a unit to its most profitable constraint and holds it there. Cerasus delivers the whole cycle — benefit study, step testing, model identification, controller build, commissioning — and the maintenance that keeps the benefits from decaying.
Model predictive control (MPC) uses a dynamic model of the unit to predict where controlled variables are heading and to move several manipulated variables together, subject to constraints, to keep the process at its limits. It sits above the regulatory (PID) layer and typically delivers 2–5 % capacity or energy improvement.
Benefits decay when models drift, instruments fail or operators lose trust. Maintenance — service factor tracking, model re-identification, tuning and operator engagement — is what keeps APC on.
Quantified benefits; base-layer, instrument and analyser readiness.
Manual or automated (closed-loop) plant tests with minimum disruption.
MV/CV/DV structure, models, tuning and constraint handling.
Staged turn-on, operator training and benefit verification.
Service-factor monitoring, model updates, tuning care, annual health checks.
Experience across major MPC platforms and open-source alternatives; CeraControl analytics workbench.
Benefit study; base-layer and instrumentation audit.
Step tests; identify models; design controller.
Turn on in stages; train operators; verify benefits.
Monitor service factor; re-identify and re-tune as the plant changes.
API RP 554 (Parts 1–3)Process control systems — design, functions, project executionISA-95 / IEC 62264Levels and integration of control and MESISA-101HMI design for APC operator displaysISA-18.2Alarm interaction with APCOPC UA / OPC DAController–DCS connectivityClient APC standardsCompany-specific benefit and service-factor criteriaSend a short brief — plant, service of interest and what you need to achieve — and a Cerasus engineer will respond with a proposed scope and next steps.
Prefer email or phone? sales@cerasus.ai · +974 5506 2743