Saturday, November 14, 2026
Atlas Prediction Control Releases CLPM Suite with Model Predictive Control and PID Tuning for Chemical Plants
South Charleston, United States - August 30, 2026 /Atlas Prediction Control/
United States, South Charleston - August 28, 2026 — Atlas Prediction Control has launched a suite of process control solutions encompassing three distinct engagement models designed to address control loop degradation, optimize constraint management, and improve performance across industrial chemical plants.
The new service suite - built around Atlas Advisor™, Remote Resident™, and Project-Based Engagements - gives plant operators structured access to Advanced Process Control (APC), PID tuning and control loop performance monitoring (CLPM), and model predictive control capabilities, without requiring facilities to maintain a full-time in-house control engineering team.
Atlas Prediction Control structured its new offerings around the recognition that no two facilities carry the same mix of control challenges, staffing capacity, or capital availability.
The Atlas Advisor™ model provides continuous advisory and diagnostic oversight, allowing plant engineers to access ongoing monitoring, loop performance assessments (CLPM), and root-cause diagnostics on a subscription-style basis. This engagement is designed for facilities that want persistent visibility into control system health without committing to a fixed project scope.
The Remote Resident™ model takes a deeper operational role, operating in a fractional engineer or fractional control engineer capacity. Under this arrangement, a dedicated control engineer from Atlas Prediction Control functions as an embedded resource for the client facility — working remotely but maintaining consistent oversight of DCS integration, controller performance, and constraint management. This model is specifically structured to replicate the functional presence of an on-site resident engineer while reducing the overhead associated with full-time staffing.
Project-Based Engagements address targeted implementation needs. These engagements are scoped around discrete objectives — deploying an Advanced Process Control strategy for a specific unit, conducting a comprehensive PID tuning and CLPM campaign across a problematic section of a plant, or completing a root-cause diagnostic study for chronic loop instability. Each project carries defined deliverables and a fixed scope, making it compatible with facilities operating under capital project frameworks.
At the center of the new suite is Atlas Advisor™, an AI-powered engineering advisor built to close a gap that shows up on nearly every shift: engineers moving between APC diagnostics, historian data, and separate engineering tools to piece together what is changing in a process and why. That work is time-consuming and experience-dependent today, and it produces inconsistent answers depending on who is on shift.
Atlas Advisor™ is built as an AI-native application: small language models purpose-built for process control data, engineered specifically for plant-floor deployment. The system continuously monitors plant stability and deviations, correlates APC, CLPM, and historian signals to isolate issues faster, and delivers engineering guidance based on current plant conditions. It integrates directly with DCS, APC, and CLPM systems alongside a facility's existing engineering tools, and supports drift detection, root-cause identification, corrective-action recommendations, multilingual use, and on-premises deployment with no internet access (isolated on-prem PCN) for facilities that require it.
The result is faster diagnosis and a consistent standard of interpretation, regardless of which engineer is on shift or how many years of experience they carry. Additional detail on Atlas Advisor™ is available at atlasprx.com/advisor.
Facilities that have not yet defined a specific project scope typically enter through one of two diagnostic offerings before an engagement model is selected. A Plant Performance Scan is a single-day, on-site assessment that scores a facility across six operational dimensions, giving plant leadership a fast, structured read on where control performance stands today.
For facilities that want a fuller picture, a Plant Audit goes deeper. The audit begins with a pre-visit data request so Atlas Prediction Control engineers arrive with process context already in hand, followed by a full day on-site that includes control room observation, an equipment walk-through, and structured interviews across the facility's process areas. Findings are scored after the visit and presented back to the client in a focused findings session that leads with what the results mean operationally and closes with a short, prioritized list of next steps.
That structured diagnostic path is what informs the right engagement model for a given facility, whether that turns out to be ongoing Atlas Advisor™ support, an embedded Remote Resident™ engineer, or a scoped Project-Based engagement to solve a specific problem.
Across all three engagement models, Atlas Prediction Control delivers a consistent set of technical capabilities. PID tuning services address controller detuning, oscillatory behavior, and interaction between loops — problems that compound over time when left unaddressed and directly erode product quality, energy efficiency, and throughput stability. Control Loop Performance Monitoring (CLPM) continuously tracks loop health across the facility and flags and prioritizes degradation before it compounds.
The Advanced Process Control offerings extend beyond basic regulatory control, incorporating dynamic constraint management and multivariable coordination. Model predictive control applications are deployed where process interactions, time delays, or hard operating constraints require coordinated controller action across multiple inputs and outputs simultaneously. DCS integration support ensures that deployed control strategies align with the specific historian, control platform, and operator interface environment in use at each facility.
These capabilities are increasingly supported by machine learning and AI-based tools, including the AI-native, small-language-model-driven diagnostics built into Atlas Advisor™. These tools are designed to interpret plant data alongside engineering context, supporting the judgment of the control engineer on shift.
Root-cause diagnostics form a foundational element of the suite. Before implementing new control strategies, Atlas Prediction Control engineers identify the underlying sources of variability — whether those sources are mechanical, procedural, or control-design related — so that corrective measures target the actual failure mechanism driving the variability.
Control loop degradation is a documented and ongoing problem in continuous process industries. Studies of operating chemical plants have consistently found that a substantial fraction of control loops perform below design intent at any given time, contributing to unnecessary process variability and off-specification production.
> “Our goal with these engagement models is to give plant teams a practical path to eliminating that variability — one that fits their actual operational structure,” said Madhur Bedre, Founder and President of Atlas Prediction Control. “Whether a facility needs ongoing advisory support, a dedicated remote presence, or a focused project to solve a specific control problem, the technical work centers on the same objective: getting controllers to perform the way the process requires, and keeping them there.”
Atlas Prediction Control provides process control engineering services to industrial facilities, with a focus on Advanced Process Control, PID tuning, model predictive control, CLPM, root-cause diagnostics, and AI-native engineering tools including small language models. The company delivers its work through three structured engagement models — Atlas Advisor, Remote Resident, and Project-Based Engagements — and supports clients across DCS integration and dynamic constraint management. Atlas Prediction Control is headquartered at 1740 Union Carbide Dr, South Charleston, WV 25303.
Learn more at Atlas Prediction Control
Contact Information:
Atlas Prediction Control
1740 Union Carbide Dr, South Charleston, WV 25303
South Charleston, WV 25303
United States
Madhur Bedre
+1-304-205-9527
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