Introduction to Nonlinear Controllers Using Aspen Process Controller Builder

Learn non-linear control methodology and practice through the Aspen Control Platform. Learn how to simulate and tune a nonlinear controller, including best practices and general commissioning rules. Learn how to transition from off-line to on-line control.


  • Engineers who are designing or implementing new Aspen Nonlinear controllers
  • Engineers who are maintaining existing DMCplus controllers
  • Anyone involved in a technical evaluation of the product

Training Details

  • Course Id:


  • Duration:

    3 day(s)

  • CEUs Awarded:


  • Level:



  • Develop skills required to assist with the execution of Aspen Nonlinear Control projects
  • Understand the benefits of using Aspen Nonlinear Controller for managing operating point transitions
  • Appreciate the benefits of a 'single model philosophy' with nonlinear model predictive control


  • An introduction to Aspen Nonlinear Controller, a universal nonlinear multivariable predictive controller
  • Basic nonlinear multivariable control concepts are introduced
  • Introduction to all model types used by the Nonlinear Controller (General Equation, State-Space BDN, Linear, Ramps etc.)
  • Introduce the new engineering workflow for controller design in Aspen Process Statistical Analyzer (Aspen IQmodel Powertools)
  • Process of creating a controller is explained, as is the process of controller simulation and tuning
  • Hands-on exercises using real industrial applications consolidates knowledge and skills
  • Introduction to Production Control Web Server and Web-based Operator Interfaces


Aspen Nonlinear Controller® Introduction
  • Identify and explain the nonlinear multivariable control of processes with interacting multivariate process nonlinearities
  • Review various types of process nonlinearities and models
  • Describe the structure of Aspen Nonlinear Controller interface

Aspen Process Statistical Analyzer (APSA) Intro
  • Create a controller project from scratch
  • Register a Master Dataset with the project for initial usage
  • Show how to use the Tag Manager to:
  • Enter Tag properties and definitions
  • Introduce Transforms
  • Re-order Tags
  • Register a Model with the project to setup a working model
  • Show how to develop Calibration Datasets and to:
  • Register a calibration dataset with a model
  • Create a calibration dataset from multiple datasets

Building Dynamics
  • Review the Nonlinear Model architecture
  • Configure Variable Deadtimes to establish process boundaries
  • Identify and configure the search limits to define the Dynamics
  • Import existing Dynamic DMCplus Model Files
  • Build Generic Ratio Models using the registered data

State Space Bounded Derivative Network (BDN)
  • Identify and explain the requirements for Nonlinear Process Control
  • Discuss the limitations of Neural network models and why they are not suitable for Process Control
  • Show how Boundary Derivative Networks (BDNs) compare with Neural Networks
  • Review how to develop and calibrate BDNs
  • List the parameters for calibrating BDNs
  • Workshop:  Building a Model.

Model Gain Analysis
  • Conduct nonlinear gain analysis of the developed models
  • Adjust and modify BDN gains if needed
  • Workshop: Creating a Controller.

Creating a Controller
  • Create the control matrix from the MISO models
  • Develop the Nonlinear Controller and create a simulation
  • Simulate the Nonlinear Controller using the application interface
  • Workshop Creating a Controller.

Model Update
  • Identify and explain the model update mechanism (Kalman Filter)
  • Discuss how to tune the typical disturbance size and noise ratio parameters in the simulator

Steady State Optimizer
  • Define the priorities of the steady-state optimizer, ranking and infeasibility
  • Describe the tuning parameters of the steady-state optimizer
  • Navigate through the optimizer dialog to set the tuning parameters
  • Discuss the diagnostic flag and show how to use it to provide detailed output information

Path Optimizer
  • Define how the Path (Dynamic) Optimizer works
  • Describe the tuning parameters of the path optimizer
  • Navigate through the optimizer dialog to set the tuning parameters
  • Describe the parameters in the Cost Function
  • Describe the rules of thumb for selecting the tuning parameters

Custom Models
  • List the custom models (elements and layers)
  • Show how to construct custom models
  • Workshop: Custom Model example for Nonlinear Controller Builder.

Introduction to the Onlines
  • Identify and explain the Nonlinear Controller Architecture, the various software modules and the File Directory Structure
  • Create an online Nonlinear Controller application
  • Discuss the troubleshooting techniques for diagnosing and solving typical controller problems

  • Discuss the IO mapping for an external database/DCS using the Config software module
  • Discuss and show how to create controller calculations
  • Show how to use templates and the replacement editor to improve IO mapping task efficiency
  • Workshop: Configuring a Controller.

Web Viewer
  • Describe the Web Viewer's permission and security roles
  • Show how to navigate through the Web Viewer
  • Manage controller applications via the Web Viewer
  • Define Column Sets for viewing controller data
  • Show how to use Filters for Controller Messages and the displayed Controller Information for diagnostics
  • Workshop Simulating a controller using Production Control Web Server (PCWS).

  • Discuss the different integrator models (ramps) and show how the steady-state optimizer works with ramps
  • Define key terms like programmed imbalance, max number of imbalances, ramp handling logic etc.
  • Show how to tune the ramp rotation factor
  • Workshop:  Industrial Case Study - Build models and simulate a controller based on the models and given data.

Operator Interfaces
  • Show various operator interfaces and navigate through application screens
  • Show how to schedule a transition in PCWS and monitor the transition through the activity list
  • Show how to use custom menus, trends and faceplates
  • Describe the interface between the controller and lab analysis feedback

Onlines Installation and Administration
  • Describe the Online Supporting Software Modules and the functionality of DAIS
  • Show how to install Aspen Nonlinear Controller Online and configure/test Aspen Cim-IO communications
  • Show how to start/shutdown online nonlinear controller applications

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Aspen Technology, Inc. awards Continuing Education Units (CEUs) for training classes conducted by our organization. One CEU is granted for every 10 hours of class participation.