Applications of MPC and PI controls for liquid level control in coupled-tank systems

The coupled-Tank (CT) system remains an important tool for research by process control engineers. However, effective control of the system depends largely on the accuracy of the mathematical model that predicts its dynamic behavior. In this work, the nonlinear model for the CT system based on analytical technique has been investigated. Linear models for the CT system were obtained based on analytical and empirical techniques. Accuracy of the linear models were investigated based on integral absolute error (IAE), were empirical model was found to be more accurate. Proportional integral (PI) control systems based on Ziegler Nichols (ZN), Ciancone correlation (CCR), Cohen Coon (CC), IMC and pole placement (PP) tuning methods were designed for liquid level control in the CT system tank 2. IAE results showed that PI controller did not meet all the specified control objectives. To improve the response, a neural network feedforward controller was incorporated to the PI controller and the response was compared to that of a model predictive controller (MPC). Simulations results showed that both PI-plus-feedforward and MPC satisfied all control specifications. However, MPC response was more satisfactory in terms of disturbance handling and time response criteria.