Nonlinear systems are prevalent in real-world applications, posing significant challenges in control due to their complex dynamics and inherent uncertainties. This chapter presents a novel multi-model control scheme that facilitates the application of linear control technique to nonlinear systems. The proposed approach comprises four steps: (i) obtaining ‘ \(N_m\) ’ number of local linear models, representing the nonlinear system dynamics across various operating regions, (ii) selecting a subset of ‘ \(N_{mg}\) ’ local linear models out of ‘ \(N_m\) ’ linear models using gap metric, (iii) designing a local controller for each of the ‘ \(N_{mg}\) ’ local linear models using the model matching controller design algorithm, and (iv) utilizing a weight scheduling algorithm to determine the degree of influence of each local controller on the overall control action. The developed algorithm is implemented by designing multimodel PI controller for the real-time conical tank process by considering multiple operating points. The experimental result shows a smooth response for a wide range of operating conditions with improved performance.