Abstract
Advanced control approaches are essential for industrial processes to enhance system performance and increase the production rate. Model Predictive Control (MPC) is considered as one of the promising advanced control algorithms. It is suitable for several industrial applications for its ability to handle system constraints. However, it is not widely implemented in the industrial field as most field engineers are not familiar with the advanced techniques conceptual structure, the relation between the parameter settings and control system actions. Conversely, the Proportional Integral Derivative (PID) controller is a common industrial controller known for its simplicity and robustness. Adapting the parameters of the PID considering system constraints is a challenging task. Both controllers, MPC and PID, merged in a hierarchical structure in this work to improve the industrial processes performance considering the operational constraints. The proposed control system is simulated and implemented on a three-tank benchmark system as a Multi-Input Multi-Output (MIMO) system. Since the main industrial goal of the proposed configuration is to be easily implemented using the available automation technology, PID controller is implemented in a PLC (Programable Logic Controller) controller as a lower controller level, while MPC controller and the adaptation mechanism are implemented within a SCADA (Supervisory Control And Data Acquisition) system as a higher controller level.
Highlights
Industrial processes have become more complex and contain several control loops.The Proportional Integral Derivative (PID) controller is considered the most popular control loop for field engineers and plant operators due to its simple structure
A combination of PID and Model Predictive Control (MPC) is recommended to be implemented in industrial applications
The proposed algorithm is executed in a hierarchical structure of two levels, one to implement PID controllers and the other to identify the PID controller gains using Recursive Least Square (RLS) to obtain the same performance of MPC
Summary
Industrial processes have become more complex and contain several control loops. The Proportional Integral Derivative (PID) controller is considered the most popular control loop for field engineers and plant operators due to its simple structure. The proposed technique adapts PID gains for MIMO with constraints based on MPC. The MPC control loop and the adaptation algorithm will be executed at the upper controller level such as SCADA system This configuration allows the proposed technique to be suitable for different industrial processes. The main contributions of this paper are summarized as (1) Design an adaptation technique of PID for MIMO considering process constraints, human and existing technology constraints as well; (2) Integrate MPC, as one of the effective APC techniques, with PID to adapt its loop instead of adjusting the setpoint only; (3) Implement the control algorithm in a hierarchical structure considering the human background and industrial technology constraints, functionality and computational burden; (4) Validate the proposed technique on an experimental benchmark using industrial automation technology.
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