Strategy of Collaborative Control Including the Effects of Controllable Parameters (2018)
A chemical process plant is composed of several process units that work together in order to transform raw material into the desired final product. Additionally, the objective is to increase efficiency and decrease the effects that disturbances cause on the product quality. Disturbances motivate the implementation of control systems on chemical processes [1], which should be multivariable because processes have multiple input variables and multiple output variables (MIMO). In addition, control systems should consider the interactions of process dynamics. There exist many multivariable control strategies. Each strategy has applicability in accordance to a particular process, because it can consider their relevant aspects. In this sense, the multivariable control strategies can consider: strong nonlinearities, the necessity of a short settling time, low overshoot, the importance of the error between the controlled variable and the set point. Despite of the large amount of control strategies, the effect of controllable parameters is not considered by any of them, except for direct manipulation of these parameters proposed by some authors. This is particularly important when additional degrees of freedom are required in the control system. In this thesis an approach to collaborative and cooperative control definitions, highlighting their differences, are proposed. Usually in the literature, collaborative control and cooperative control are studied like the same techniquey, but there exist differences between them. Here, a collaborative control strategy including the effects of controllable parameters is proposed and applied. That strategy includes into the optimization procedure a term for considering the influence of one or more parameters that can be controlled using available control actions. To do this a mass transfer model for the aerated section in Benchmark Simulation Model No.1 (BSM1) is developed separating the effects of parameters kL y a. The behavior of collaborative control using such a separation is compared with traditional control structures using the integrated kLa parameter, all implemented over this benchmark.