Process control systems are created to track and manage industrial processes, assuring their secure and effective operation. Several process control system types, such as continuous, batch, and discrete control systems, are often employed in a variety of industry.
Continuous control systems
In operations where a product is generated continually, such in chemical plants and refineries, continuous control systems are employed. The process variables, such as temperature, pressure, and flow rate, are monitored by sensors in these systems, and the inputs are changed to maintain the appropriate setpoints. Typically, feedback control is used in continuous control systems, which compare the process’ output to the target setpoint continually and modify the input as necessary.
Batch control systems
In operations where a product is produced in batches, such in the manufacture of pharmaceuticals, batch control systems are employed. In order to generate a batch of product, these systems usually follow a series of processes, with the inputs being changed at each stage to maintain the ideal process conditions. By using feedback or feedforward control, batch control systems change the input depending on both the circumstances of the current process and the anticipated circumstances of the future.
Discrete control systems
Processes involving discrete occurrences, such conveyor systems and manufacturing lines, require discrete control systems. Logic controllers are often used in these systems to regulate the motions of the equipment while sensors are used to detect the positions of the goods or parts. Open-loop and closed-loop control, where the input is changed based on the present process circumstances or the anticipated future conditions, are both options for discrete control systems.
Moreover, other control techniques, such as proportional-integral-derivative (PID) control, model-based control, and adaptive control, can be applied in process control systems.
PID control system
Popular control methods like PID control employ feedback control to modify the inputs in order to maintain the desired setpoint. The process variable is continually measured, the error between the setpoint and the actual value is calculated, and the input is then adjusted based on a proportional, integral, and derivative term.
Model-based control system
Model-based control predicts the behaviour of the system and modifies the inputs in accordance using mathematical models of the process. It may be used to lower energy usage and improve process performance.
Adaptive control system
A control strategy known as adaptive control modifies the input in response to the changing process circumstances, such as adjustments to the equipment or the environment. It may be applied to lessen variability and increase process stability.
For the purpose of assuring the secure and effective functioning of industrial processes, process control systems are crucial. Many control systems and control techniques may be applied to enhance the efficiency of a process, depending on the kind of process being controlled. Designing and implementing efficient process control systems requires an understanding of the many types of process control systems and control techniques.