Online duration: 18 hours (published online course duration).
Audience:Process Control Engineers, DCS Technicians and Supervisors.
Prerequisites: Knowledge of primary process control and PID controllers is required. Several months of plant experience, especially with a DCS, is preferred.
Course material: Training slides and MPC software examples.
$525.00
MPC700 provides online model predictive control training for industrial process-control applications. It covers the role of dynamic models, predictions and constraints in MPC design, commissioning, monitoring and maintenance.
The course examines step-response coefficients, the MPC control matrix, PID foundations, step testing, tuning parameters and linear-programming costs. It includes model-identification concepts and the use of PITOPS-TFI examples to examine process dynamics when an application or process changes.
Review PID100 for primary-control foundations and STA200 system identification for modeling. Compare APC200 for advanced regulatory structures and read the APC versus MPC guide.
Study model predictive control through engineer-developed, recorded video training grounded in decades of industrial process-control experience. AIAPC's course-development background connects engineering principles with practical plant-control work.
For course support, use the contact form or email [email protected]. Scheduled live classes and private team training can be arranged separately.
Relevant work contexts: Control and APC engineers, process engineers and model-maintenance teams with the background needed for multivariable control study. These examples describe applications of the subject, not a promise of industry-specific exercises, job placement or employment. Employers also assess experience, site procedures and role-specific qualifications. Explore the process-control skills and career guide for broader learning context.
Study how the components of an MPC system work together, how controller settings and costs influence decisions, and how plant trends can inform troubleshooting. Compare situations suited to advanced regulatory control with those suited to MPC. Model quality, constraints and commissioning procedures remain important application-specific considerations.
The course syllabus covers:
This is recorded video training. For software-based exercises, contact AIAPC to confirm installation, compatibility and licensing requirements before enrolling. Live classes and company team training are arranged separately by appointment.
Compare the course catalog and learning paths, or review course completion certificate requirements before choosing your training.
MPC700 addresses industrial process-control applications: dynamic models, step-response coefficients, PID foundations, step tests, the MPC control matrix, tuning parameters, LP costs, monitoring and commissioning. Its published prerequisites require knowledge of primary control and PID controllers; plant experience, particularly with a DCS, is preferred. Review the industrial MPC guide alongside the course syllabus.
Compare STA200 when your learning gap concerns identifying transfer functions and process dynamics. Compare APC200 for broader advanced control structures, including cascade, feedforward and constraint override. MPC700 is the dedicated predictive-control course; the APC versus MPC guide helps separate the learning objectives.
Check the modeling and control tasks in the syllabus. MPC700 addresses industrial model predictive control through step-response coefficients, the control matrix, tuning parameters, LP costs and commissioning topics. Academic or software-specific courses may pursue different mathematical or implementation goals. Use the MPC prediction, constraint and control-cycle guide to compare the scope.
Review process dynamics, controlled and manipulated variables, interactions, prediction models and operating constraints. Keep model-identification questions separate from decisions about controller objectives and tuning. If model interpretation is the missing foundation, compare STA200 transfer-function identification first.
Browse the recorded lesson outline. Lesson and quiz access follows your enrollment.
Continue with the practical learning article: MPC Prediction Horizon vs Control Horizon: Examples. Review its worked example alongside the course topics above.