Stability analysis of nonlinear processes using empirical state affine models and LMIs

A novel methodology is proposed for the analysis of robust stability of a nonlinear process under PI (Proportional-Integral) control. The analysis is based on state-affine empirical models regressed from input-output data. The state model is represented by a set of polynomial matrices nonlinear with respect to the manipulated variables. This model in combination with a linear PI controller results in a closed loop model that can be shown to lie in a polytope of matrices. This allows for the formulation of a Lyapunov stability test in terms of a simple set of LMIs (linear matrix inequalities). This set of inequalities can be also expanded to account for input saturation. The stability analysis produces regions of stability, in terms of the PI controller parameters, that are significantly larger than the regions previously calculated by a singular value test. The issues of saturation and modeling error are also incorporated into the analysis. The technique permits also to test the stability of the closed loop system with a gain scheduling PI controller. The conservativeness of the analysis is assessed by comparison to closed loop simulations of a highly nonlinear CSTR (continuous stirred tank reactor) under PI control.