Date & Time
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Description
This full-day workshop will be a practical guide for those considering the use of first principles
models for control of processes. First-principles models do not seek full rigor, and they are fully accepted in engineering design, process analysis, and learning. First principles models are phenomenological (mechanistic) and mathematically express a specific mechanism, as opposed to being generically empirical. But they might use empirical data to determine coefficient values. Fundamental control concepts will be revealed, and the participants should take away the ability to implement several of the simple and effective methods for either SISO or MIMO applications.
The workshop will cover SISO versions of Generic Model Control (with steady state models), which become easy-to-implement output-characterized PI control. Then move to Process-Model Based Control and Predictive Functional Control (with dynamic models). It will start with simple unconstrained versions, and progress to constrained nonanalytic applications and on-line model adaptation. Then the course will cover the use of nonlinear models in a MIMO, constraint-handling MBC structure. These are chosen for their utility within the process environment and because they represent the fundamentals of most approaches. All have been credibly demonstrated in real full-scale applications.
Course examples will represent diverse applications which should be understood by any engineering disciplines. Participants will receive course notes and software that provides exercises and access to code. Exercises and code can be implemented in any environment, but Excel/VBA will be used as in-workshop examples and exercises. Participants are invited to bring a computer with Excel version 2010 or higher for in-class exploration. Participants have permission to directly apply the provided software to their specific problems. The workshop material is an expansion of material and software on the companion web site www.r3eda.com.
Simulation applications will include automobile speed control, and pH control as nonlinear SISO examples and hot and cold mixing as a nonlinear 2x2 example. Any STEM graduate should be able to relate to the processes and issues.
Intended Audience: The workshop is designed for those needing to understand nonlinear control applications. This is a practical guide on the use of best practices from conventional methods, with
examples to illustrate the choices and techniques. Supporting theory will be addressed, but the take-away will be the ability to specify determine adequacy of a model, design a controller, and handle constraints. The intended audience includes engineering employees, students, and faculty who want to use nonlinear control techniques.
Prerequisite skills: Any undergraduate engineering or mathematics program should have provided the participant with an adequate experience in calculus, linear algebra, and computer
programming. The course will review essential topics that are commonly un-remembered from undergraduate courses – including first-principles modeling, and optimization.
Schedule
Session 1
- Concepts, Issues, Conventional Solutions
- Rational
- Block Diagram of Elements and Options for Each
- Models – Steady State and Dynamic
- Models – Obtaining, Sufficiency, Calculation Forward and Inverse
Break
Session 2
- SISO/MISO – GMC, PFC, PMBC
- Simulation Examples
- Constraints – Soft and Hard, Equal Concern Weighting
- SISO/MISO – with optimization solutions
- Simulation Examples
Lunch
Session 3
- Incremental Model Adjustment and Examples
- Measurement Validity and Data Reconciliation
- Steady State Identification and Examples
Break
Session 4
- MIMO – PMBC in MBC Structure (Horizon Predictive, Constraint Handling)
- Simulation Examples
Closing
Date & Time
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