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) mu -analysis-based H-infinity control. The three control algorithms are comparatively analyzed using standard robustness measures for stability and performance. 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 is with a MATLAB and Freelance software interface. The controllers are shown to preside stable and acceptable performance for reference tracking and, disturbance rejection experiments. The multivariable IMC and H-infinity controllers performed similarly and provided better performance than the decentralized PI control.