Stable adaptive control of a multivariable nonlinear process

In this paper, we apply an adaptive control algorithm to a nonlinear multivariable process. Such controller is based on the multiple models approach. As the design of the control law requires the knowledge of the dynamical model of the system, we deal firstly with the identification of the system parameters using the recursive least squares and the retro propagation of the gradient algorithms. Then, we focus on the application of the multiple model approach. So, we decomposed the nonlinear model of the system in sub-systems and we adopted a proper criterion of commutation between the various models. The global control consists in the interpolation between the elementary control extracted from each model. The resulting controller is applied to a multivariable process to solve a tracking problem of the water levels into a twin tank process. The control strategy ensures the stability of the closed loop system and guarantees a good behavior when tracking a reference trajectory.