MPC700: Model Predictive Control Design, Implementation and Maintenance

The MPC700 course provides in-depth training on Model Predictive Control (MPC), covering its design, implementation, troubleshooting, and maintenance. It teaches how to use MPC software to optimize control systems in industrial settings.

This course is ideal for process control engineers, DCS technicians, and supervisors with prior knowledge of primary process control systems and some experience in plant operations.

The MPC700 course can be completed in 2 days through classroom training or 18 hours of online learning, providing flexibility for your learning schedule.

Participants should have a basic understanding of process control, including PID control, and ideally, a few months of plant experience, especially with DCS systems.

You will learn how to design, implement, tune, and troubleshoot MPC controllers, conduct step tests, optimize dynamic models, and maintain and modify MPC systems after years of operation.

MPC is an advanced control strategy that uses mathematical models to predict future plant behavior and make real-time adjustments to optimize system performance. It is ideal for complex processes with constraints.

The course equips you with hands-on experience in designing MPC systems, fine-tuning controllers, troubleshooting, and using modern technology like the 3G closed-loop dynamics identification to improve control systems.

Key topics include MPC vs APC, dynamic models, MPC control matrix, PID optimization, step response coefficients, MPC tuning parameters, troubleshooting, and commissioning of MPC systems.

The course helps you determine which control strategy is most suitable for a particular process by understanding the strengths and weaknesses of both MPC and APC.

MPC allows for superior control of complex systems, optimizes performance, and adapts to changing conditions. It is especially effective in managing constraints and improving system efficiency.

Yes, the course includes a focus on troubleshooting MPC controllers, helping you understand common issues and solutions so you can maintain smooth operations in your plant.

You will use MPC software and receive hands-on training with real-world tools, helping you develop practical skills for designing, commissioning, and maintaining MPC systems.

The course teaches you how to build and optimize MPC systems, enabling you to improve control over process dynamics, reduce energy consumption, and enhance overall plant performance.

The course highlights potential challenges such as tuning, model identification, and troubleshooting, and provides you with effective strategies to overcome these hurdles and implement MPC successfully.

MPC systems require regular maintenance to remain effective, especially after process changes. The course teaches how to modify and improve MPC models over time, ensuring long-term performance and adaptability.

Yes. MPC is a cornerstone of modern digital plant infrastructure. MPC700 helps control engineers build smarter control systems that support predictive analytics, digital twins, and AI-driven optimization.

Absolutely. MPC helps reduce variability and ensures systems stay within tight constraints, critical for meeting GMP, FDA, and environmental compliance standards.

MPC700 provides a framework for rebuilding and optimizing control logic when migrating DCS platforms, modernizing legacy MPCs, or integrating with modern model-based or AI-driven layers.

Yes. The course walks you through how to quantify the business impact of MPC—such as improved yields, reduced energy, and downtime—making it easier to present a business case to management.

Yes. PiControl offers custom training sessions that incorporate your plant’s data, models, and DCS platform for an applied learning experience.

Yes. Attendees receive documentation templates, commissioning checklists, and model validation sheets to streamline the implementation and maintenance of MPC systems.