MON300: Control Quality Performance Monitoring and Adaptive Control
Contact Us Today: info@PiControlSolutions.com, Tel: (832) 495 6436
Duration: 2 Days Classroom or 20 hours Online
Audience: Process Control Engineers, Advanced Process Control Engineers, Instrument Engineers, Lab Technicians, DCS/PLC Technicians, Managers and Supervisors.
Prerequisites: 2-year or 4-year degree in engineering or operations and/or a few months of plant/ engineering experience is desirable, but not required.
Course Material: Software used: Apromon and Pitops. Also custom training slides.
Course Description and Objectives::Chemical plants can have anywhere from about 50 PIDs in small plants to over 2000 PIDs in large refineries and integrated petrochemical complexes. In addition to simple PIDs, there are cascades, override controllers, model-based controllers and multivariable controllers.
As time goes by, even well-tuned PIDs and other controllers can slowly start to deteriorate. As deterioration progresses, process oscillations can start with small amplitudes and can grow large over time costing the plant significant monetary and/or quality losses. Or conversely, PIDs could become sluggish because of changes in process and operating conditions, once again causing the control quality to deteriorate.
This course covers the technology and application of a control performance monitoring software (Apromon) that identifies poorly controlling PIDs (includes single, cascade, override and complex PIDs). Apromon runs online using OPC and calculates several control criteria and generates control quality reports. Integrated with Apromon is a novel, breakthrough algorithm called TAD (True Amplitude Detection) that accurately isolates oscillating or sluggish controllers. This course shows how to improve and maintain the plant’s primary and advanced control system and increase the plant’s profits.
This course explains how to identify control problems in an online/real-time manner and take immediate corrective action using online adaptive control. The course also shows how to implement true adaptive control inside the DCS by connecting the control quality monitoring software using OPC technology to the DCS/PLC and by designing special DCS/PLC-resident logic for triggering automatic control action.
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At the end of the course, attendees will be skilled in understanding process control quality monitoring criteria and statistics. They will be skilled in the application, installation and use of real-time software products for process control quality monitoring at any plant.
Attendees will also be skilled on the application of online adaptive control technology using the control quality monitoring software and then linking it with closed-loop DCS based-adaptive control schemes. Using the knowledge, attendees on their own can build closed-loop adaptive control schemes at their plant inside the DCS/PLC using OPC connectivity.
Attendees will be able to significantly improve control quality at their plants, move the plant more stably and reliably in the direction of increasing profits with fewer shutdowns and fewer abnormal events. The plant will also see a reduction in the number of alarms and a reduced need for operator intervention.
- Modern process control in plants
- Process interactions because of mass balance and heat balance integration Potential for process cycling and sustained oscillations
- Causes of process oscillations
- Pitops simulations illustrating different oscillation cases
- Pitops simulations illustrating excessive control valve movement Pitops simulations illustrating sluggish control
- Definition of various process control quality performance criteria Explanation of special new terms – crimp, cheat, vacillation, rope length etc. Component breakdown of PID contributions
- Use of process control monitoring software – Apromon-Excel Run example cases on Apromon-Excel
- More explanation of process control quality performance monitoring criteria
- Conduct what-if studies on example using Apromon-Excel
- Adjust and understand oscillation tuning parameters
- Set up online OPC servers to simulate real-plant environment Use of Apromon-OPC
- Run example cases on Apromon-OPC
- Implement Apromon-OPC using OPC simulation server
- More explanation of process control quality performance monitoring criteria Procedure and tips on implementing Apromon-OPC in a plant environment
- Need for detection of online oscillation in an industrial process Need for detection of sluggish control in an industrial process. Precise determination of oscillation
- Practical challenges of detecting oscillations reliably Understanding of true amplitude detection) algorithm
- Setting up Apromon-OPC and configuring it in online/real-time mode
- Implementing online adaptive control using DCS, Apromon and a OPC server-based computer
- Identification of SISO Closed-Loop Process Transfer Functions Multi-Input Closed-Loop Transfer Function Identification
- Identifying Process Dynamics based on analyzing actual Time-Sampled Data
- Lab Session using Pitops to identify first and second order transfer functions using real plant data Use Pitops to identify multivariable transfer functions using real plant data in closed-loop mode Model-Predictive Control
- When to use PID, Cascade PID, Advanced Regulatory, DMC, RMPCT, Rule-Based Control Identifying, Debugging and Troubleshooting PID Tuning and Process Control Problems Online PID/APC Control Quality Monitoring and Reporting
- Online Oscillation Detection and Online Control Sluggishness Detection
- PID Control Quality Alerting to Smartphones for Improved Proactive Maintenance