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Rockwell Automation will release PlantPAx model predictive control (MPC) software, which for the first time embeds fully functional MPC technology into Logix controllers to help maximize equipment performance. When used in process applications ranging from consumer to heavy industries, PlantPAx MPC reportedly can help improve overall control in a single machine or an entire line to help to maximize throughput, increase yield, reduce quality variability and improve energy usage.
PlantPAx MPC is included in the latest release of the PlantPAx modern distributed control system.
Multivariable Coordination: PlantPAx MPC delivers better coordination of multivariable actions in complex process applications to help maximize controller performance and maintain quality. A single control-system-based MPC module supports up to five separate MPC applications, and each of those applications can support up to 10 controllable variables and 10 manipulated variables.
Predictably Handle Outside Disturbances: The software provides the ability to measure disturbance variables that cannot be controlled, such as ambient humidity. Once detected, the system can predictably respond to these disturbances as needed to help keep the process optimized.
Manage Long and Complex Processes: Both operators and control systems can struggle when managing long and complex processes for applications, such as dryers and kilns. PlantPAx MPC uses dynamic explicit modeling to identify and program the specific responses and requirements for these processes.
Predictive Response to Constraints: PlantPAx MPC dynamically predicts process behavior against identified constraints and makes proactive adjustments to help maintain process performance within identified limits.
Maximize Equipment Performance: Dynamic and steady-state constraints can be enforced in the software to better maximize equipment performance up to its limits. For example, enforcing a flooding constraint in a distillation process can help feed levels at their highest without the risk of flooding.
Keywords: Energy Efficiency, Controller-Embedded MPC, Multivariable Actions, Complex Process Applications, Dynamic Explicit Modeling, ARC Advisory Group.