Introduction to ARPM

In this introductory workshop, you will learn to use ARPM for process simulation and equipment performance monitoring. Attendees are expected to have a working knowledge of steady-state process simulation. The course is a mixture of lecture and hands-on problem solving. Class exercises will guide the user through the processes of simulation, data reconciliation, and performance monitoring of an NGL Chiller plant.

Topics Covered Include:
• Overview of Equipment Performance Monitoring application building
• Overview of ARPM architecture
• Fundamentals of open-equation based modeling
• Calculation of algorithms
• Flowsheet modeling in ARPM
• Data reconciliation in ARPM
• Customization in ARPM
• Troubleshooting techniques
• The External Data Interface (EDI)
• Overview of the ARPM solver: OPERA
• The Real-Time System (RTS)

Introduction to ROMeo

In this introductory workshop, you will learn to use ROMeo for process simulation and on-line optimization. Attendees are expected to have a working knowledge of steady-state process simulation. The course is a mixture of lecture and hands-on problem solving. Class exercises will guide the user through the processes of simulation, data reconciliation, and optimization of an NGL Chiller plant.

Topics Covered Include:
• Overview of real-time optimization application building
• Overview of ROMeo architecture
• Fundamentals of open-equation based modeling
• Calculation of algorithms
• Flowsheet modeling in ROMeo
• Data reconciliation in ROMeo
• Customization in ROMeo
• Troubleshooting techniques
• The External Data Interface (EDI)
• Overview of the ROMeo solver: OPERA
• The Real-Time System (RTS)

Fundamentals of Connoisseur

In this introductory course, you will learn the principle of model-predictive process control and how it is implemented by the Connoisseur software package. Attendees should have an understanding of conventional process control techniques as implemented by typical modern distributed control systems. No prior knowledge of process modeling or predictive control and optimization techniques is required. The class has a strong hands-on element, using realistic process case studies.

Topics Covered Include:
• Interfacing to process control systems
• Process response testing
• Dynamic model identification
• Predictive controller design and simulation
• On-line controller implementation
• Controller tuning and adaptation
• Real-time calculations
• Steady-state LP optimization

Connoisseur in Practice

In this course, you will learn how to leverage the advanced features of Connoisseur to maximize operating benefits. The class attempts to bridge the gap between classroom education and the "in-plant" experience. A DCS-resident process simulation is used to allow full exposure to all aspects of the application development process. Attendees will develop a complete model-predictive control and optimization strategy for the simulated process, including operator interface. A basic knowledge of Connoisseur and on-line applications is assumed.

Topics Covered Include:
• Model-building strategies
• Handling integrating processes
• Secure supervisory control
• Operator interface and interaction
• Robust adaption strategies
• Inferential estimation using both linear and neural net models
• Implementation of rule-based fuzzy controllers
• Integration of a composite LP optimizer with MPC sub-controllers