Multivariable model-based control strategies for level control in a quadruple tank process

This paper presents three model-based control strategies applied to a multivariable process. First, a simple and rather naive approach is employed, i.e. treating the process as two SISO (Single Input Single Output) loops and design PID controllers. Obviously, this approach is effective, but does not take into account the interaction between the loops. Next, interaction is compensated by using dynamic decouplers and control performance is improved. Finally, a multivariable IMC (Internal Model Control) method is applied. All the results were validated on the laboratory setup with coupled quadruple tanks from Quanser. This is an interesting and challenging testbed for control, i.e. it poses non-minimum phase transmission zeros. Our experimental results show that the IMC outperforms the PID control at the cost of additional design complexity. All controllers were successfully tested for setpoint trajectory and disturbance rejection and tackled well the noise in the system.