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Mixing and Blending Controllers

About Mixing and Blending Controllers

Mixing controllers and blending controllers govern the ratio, mixing or blending parameters of two or more ingredients in a process automation system (PAS). They are used to control the addition of gas or air, liquids, and/or solids. Mixing controllers and blending controllers receive inputs from sensors and systems such as weigh feeders, belt conveyors that control the flow of bulk solids by continuously weighing material and adjusting the belt speed accordingly. Choices for mixing and blending controllers with regard to functionality include: rate indication, data logging, and totalizing. The user interface for a mix controller or blend controller may consist of a digital front panel or analog components such as knobs and switches. Computer-programmable, web-enabled, and network-ready mixing controllers and blending controllers are also available. A mix controller or blend controller with digital controls may include human machine interface (HMI) software or provide supervisory data acquisition and control (SCADA) functionality. Mixing and blending controllers that incorporate a programmable logic controller (PLC) or interface with a personal computer (PC) are also available.

Mixing controllers and blending controllers can use limit control, linear control, PID control, feedforward control, fuzzy logic, or advanced (non-linear) controls. Limit control is a type of on-off or bang-bang control that establishes set points or limits that, when reached, send a signal to stop or start a process variable. Linear control matches a variable input signal with a correspondingly variable control signal. Proportional, integral, and derivative (PID) control requires real-time system feedback. Feedforward control provides direct-control compensation from the reference signal. Fuzzy logic is a mix / blend control technique in which process variables can have imprecise values (as in partial truth) rather than a binary status (completely true or completely false). Advanced or nonlinear controls for mixing and blending controllers use algorithms such as neural networking and adaptive gain.

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