Powerful, Flexible, Process Modeling & Tuning Tools

Process Modeling from Available Plant Data

ExperTune's PID Loop Optimizer identifies a process model using advanced frequency response methods. ExperTune software develops a high-fidelity model from a variety of data. Examples of data sets ExperTune software uses to identify process models:

• Open loop step
• Closed loop step (controller in automatic)
• Open loop pulse
• Closed loop pulse (controller in automatic)
• Pseudo random data
• Open loop doublet pulse

See a presentation on "Plant Data to Use For Modeling and PID Tuning."

PID Loop Optimizer automatically chooses the best model structure for your process. Either:

• Dead time with gain
• First order with dead time and gain
• Second order with dead time and gain
• Second order over-damped with dead time (Imaginary roots) and gain
• Integrator with dead time
• Double Integrator with dead time
• Integrator with first order and dead time
• Inverse response process or shrink-swell: Integrator with first order, lead time, and dead time

With PID Loop Optimizer, you can force a model structure, and the software will fit the best parameters to that model.

Video: How to Automatically Find a Model of Your Process

Modeling tools: Drag & Drop Modeling Automatically Select Model Type & Constants Force Model Type as Desired Correct for Non-Linearities Export of DMC Vectors LaPlace and Frequency-Domain Models ExperTune has over 20 years of experience with modeling and tuning of PID control loops. Reliable, accurate models lead to good tuning results. Use PID Loop Optimizer's tools to get excellent results.
Case Studies Tuning Improvements for a Metals Furnace (pdf) See more case studies

Optional Drag & Drop Modeling

Drag & Drop modeling let's you manually adjust process models. Make adjustements to your models to get optimal PID Tuning, accurate simulated response to upsets, more accurate response to process noise, and better robustness analysis. Drag & Drop modeling puts you in control of the model fit. Using any bump test data, drag the model curve to match the actual response curve. Instantly, the software finds a dynamic process model that gives the visually designed response. Use this model to give optimal PID values, simulate responses to upsets and noise. Use Drag & Drop Modeling to: Tune, using imperfect data Fit many types of bump tests, not just step tests Work with incomplete or very noisy bump test data Make adjustments to the process model See how tuning would change if the process changes Video Presentation: How to Automatically Find a Model of Your Process Many Model Types Supported Drag & Drop Modeling supports modeling of First-Order, Second-Order, and even Integrating control loops.

Find the Best Tuning

Dial in the robustness you want

Get the best performance trade-off with ExperTune's unique Robustness Plot. The Robustness Plot shows how sensitive your loop is to the process changing. Drag the plot with the mouse to set the sensitivity you want. The required PID values and all the ExperTune analysis windows, including the Performance Summary, update—instantly! See the tutorial on Robustness Plots.

Choose the Tuning You Want

• Minimize Overshoot
• Respond Quickly
• Eliminate Errors
• Reduce Oscillation

Learn more:

• Video Tutorial on Robustness plots: Loop Stability—The Other Half of the PID Tuning Story
• Article that explains and uses robustness plots: "How to Control Processes with Large Dead Times", Control Engineering

Linearize Your Process For Optimal Performance At All Production Rates

Does your process oscillate near one end of the range and respond sluggishly at the other? ExperTune's characterizer, helps you linearize your process, so you get uniform performance across the entire range—run your production at its optimum rather than de-tuning for oscillations.

Use ExperTune's characterizer to linearize:

• flow loops
• jacket temperature in chemical reactors
• slave loops in cascades
• any loop where the setpoint changes
• valve characterization in MPC controllers
• hyperbolic linearizers in MPC controllers

• More details: How ExperTune's characterizer works
• Video: Linearize Your Process—Get Optimal Response at All Production Rates
• Read: Greg Shinskey's Advice for Characterizers

pH Control Needs Linearization, Too

Because of the inherently non-linear measurement, pH control loops need linearization, also.