Implementation of SISO robust predictive control to a three tanks system

This work presents an application of linear and nonlinear robust predictive control onto a three tanks system. The design of the linear solution is based on Single-Input Single-Output Controlled Auto Regressive Integrated Moving Average (CARIMA) model and the nonlinear controller considers Nonlinear Auto Regressive with eXogenous output (NARX) model. Parametric uncertainties and polytopic uncertainties are adopted in order to take into account the uncertain behavior of the system. Based on worst case strategy, the control law is obtained by the resolution of a min-max optimization problem. However, the performance criterion to be optimized is non-convex. To overcome this problem, non-determinist and determinist global optimization algorithms are proposed namely Genetic Algorithms (GA) and Generalized Geometric Programming (GGP). Experiment results onto a three tanks system are given to illustrate the effectiveness of the developed strategies.