This 3 ½ day course is designed for process and control engineers who are applying DeltaV Model Predictive Control (MPC) to solve process control problems. It provides practical examples of how to determine the benefits of MPC application and how this control may be used to meet specific application requirements. Students will gain hands on experience through lab exercises based on realistic dynamic process simulations.
DeltaV Implementation I, Course 7009 and DeltaV Advanced Control, Course 7201.
• How to Justify an MPC Project - Evaluating the cost of process variation - Estimating the reduction in variation that is possible using MPC - Calculating the benefit of maximizing throughput when plant production is restricted by input limits or measurable constraint
• Evaluating Process Models - Configuring and commissioning a control module using the DeltaV MPC-Pro block - Evaluating the impact of model mismatch on controller performance - Testing a process to obtain a step response model - Examining model residuals for model inaccuracies • Tailoring Control Performance - Placing more emphasis on selected control or constraint parameters - Improving control performance when the process is deadtime dominant - Compensating for large changes in process gain or dynamics - Minimizing the impact of process noise on control performance
• Meeting Application Requirements - Ensuring disturbance inputs are independent of other process inputs - Meeting control requirements when the response times are very different - Understanding the design and testing of an integrating process
• DeltaV MPC-Plus block - Understanding the features of the MPC-Plus block - Configuring failure handling on the MPC-Plus block - Configuring the optimization objectives for the MPC Optimizer - Understanding the expert features of DeltaV PredictPro application - Tailoring the control performance of the MPC-Plus block (on-line tuning)