An LMI Robust Predictive Control Approach Applied in a Chemical Reactor

The paper addresses a case study of robust stabilization of a continuous stirred tank reactor using robust model-based predictive control with constrained input variables. The control approach is based on solution of a set of linear matrix inequalities. This formulation enables to use convex optimization methods to design a gain matrix of a state feedback controller in each control step. The task of stabilization is solved in assumed control conditions with respect to symmetric constraints on control inputs. The control performance achieved by robust constrained model-based predictive control is studied via simulations. Obtained results confirm that the robust constrained model-based predictive control ensures the stability demands and the quality requirements represented by chosen quadratic cost function.