1. A method for tuning an adaptive Multivariable Proportional-Integral-Derivative (PID) controller within an operating range of the Multivariable PID controller, in a plant using a Model Predictive Control (MPC), the operating range comprising a plurality of critical regions, the method comprising: formulating the MPC for a process model of the plant, wherein a solution of the MPC accounts for constraints on the plant; obtaining an optimal control solution of the MPC in one or more critical regions from the plurality of critical regions using a look-up table comprising a plurality of rows, wherein each row of the look-up table is associated with a critical region from the plurality of critical regions, wherein each critical region from the plurality of critical regions is associated with a corresponding affine control law in the look-up table, the corresponding affine control law having the form U=M·θ+m, where U is an output, θis an input, and M and m are constant matrices, and wherein the optimal control solution accounts for the constraints on the plant and the optimal control solution is for providing the affine control law corresponding to each of the one or more critical regions; determining one or more equivalent PID tuning parameters for the one or more critical regions corresponding to the optimal control solution of the MPC in the one or more critical regions based on the one or more corresponding affine control laws from the plurality of affine control laws, wherein determining the one or more equivalent PID tuning parameters comprises one of (i) merging the one or more critical regions and (ii) clustering the one or more critical regions by merging the one or more equivalent PID tuning parameters corresponding to the one or more critical regions; and tuning the adaptive Multivariable PID controller with the one or more equivalent PID tuning parameters to control the plant in the one or more critical regions.