Introduction to Nonlinear Controllers Using Aspen Process Controller Builder

Course Id:  APC185   |   Duration:  3.00 day(s)   |   CEUs Awarded:  2.1   |   Level:  Introductory


Course Objective

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.

Course Overview

  • Effectively use the Aspen Nonlinear Controller application to build a Nonlinear Controller project
  • Formulate a Nonlinear Control objective function to define the economic benefits
  • Simulate and tune a Nonlinear Controller
  • Describe best practice and general commissioning rules for establishing online deployment
  • Discuss the capabilities of the Steady State Optimizer and the Dynamic Move Path Optimizer
  • Show how to make custom models
  • Discuss the online configuration parameters and architecture
  • Simulate with the online PCWS (web viewer)
  • Discuss the special handling of Integrating Variables
  • Show how to use the different operator interfaces for the PCWS application
  • Show how to configure, install and deploy Aspen Nonlinear Controller
  • Setup and define PCWS account roles, permission, privileges and security access

Benefits

  • 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

Audience

  • 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

Approach

  • 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

Class Schedule

Class Agenda

APC185: Introduction to Nonlinear Controllers Using Aspen Process Controller Builder

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

Configuration
  • 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).

Integrators
  • 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

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.