On l1-Predictive Control of Mixed-Logical Dynamical Systems

Abstract

Constant technological innovations and environmental and economical requirements have created new challenges in industrial process control. The hybrid system predictive control is a representative example of great interest in this modern scenario. Hybrid behavior is found by continuous operation dynamics inserted with discrete event changes that might occur by internal and external actions of the system. Internal actions that generate hybrid behavior can be faults, changes between operation modes and perturbations. External actions can be represented by logical and decisory aspects and safety constraints. The chemical process operation often deals with controlled transitions among operation modes due to changes in the raw materials, energy sources, product specification and market demand. In this paper, a hybrid systems representation of linear systems known as mixed logical dynamical models (MLD) is investigated. The paper addresses the MLD /1-Model Predictive Control (MPC) problem. Structurally, the MLD model control problem is described through a linear mixed integer optimization problem (MILP), which is computationally demanding, but they can be satisfactorily applied to systems of certain speed and dimension. The paper presents a study on the characteristics of the controller. A system of interest is used to illustrate the study. The results show that the application of MLD in the MPC control framework can have a positive impact specially when there is the inclusion of logical decisions aspects and operational knowledge in the MPC problem.