Robust Control of a Multivariable Experimental Four-Tank System

Abstract

A multivariable laboratory process of four interconnected water tanks is considered for modeling and robust control. The objective of the current study is to design and implement a variety of control algorithms and present corresponding robust control analysis for a multivariable laboratory four-tank process. The control methodologies considered are (i) decentralized PI control, (ii) “inner−outer” factorization-based multivariable internal model control (IMC), and (iii) μ-analysis-based H ∞ control. The three control algorithms are comparatively analyzed using standard robustness measures for stability and peformance. The algorithms are implemented on the four-tank system, and the performance is compared in reference tracking and disturbance rejection cases. Using experimental data, the process dynamics and disturbance effects are modeled. Input−output controllability analysis is performed to characterize achievable performance. A lumped unstructured uncertainty description is used to represent the variations in the system. The three controllers designed are implemented on the four-tank experimental apparatus using a Bailey control system with a MATLAB and Freelance software interface. The controllers are shown to provide stable and acceptable performance for reference tracking and disturbance rejection experiments. The multivariable IMC and H ∞ controllers performed similarly and provided better performance than the decentralized PI control.