Estratégia de um sistema de controle em cascata relacionando a composição do efluente à entrada de topo em um modelo empírico de coluna de stripper

Abstract

The chlor-alkali industry, which relies on brine electrolysis, produces essential chemicals such as chlorine, sodium hydroxide, and hydrogen. The electrolysis of brine (an aqueous sodium chloride solution) yields gaseous chlorine, sodium hydroxide, and hydrogen gas. Chlorine, in particular, is crucial for manufacturing polyvinyl chloride (PVC), one of the most widely used plastics globally. After production, chlorine gas undergoes purification, beginning with cooling in heat exchangers. During this process, water condenses and is treated as an impurity, potentially containing residual chlorine traces. This water cannot be discarded without removing the dissolved chlorine, as it would lead to production losses and effluent contamination. To address this issue, a stripping column is employed, where volatile components are removed by introducing saturated steam at the column's base. Chlorine is volatilized and exits at the top, while the condensed water—now suitable for disposal or reuse—is collected at the bottom. Maintaining all variables within operational ranges is critical to ensure process safety and efficiency. This study proposes and evaluates a cascade control strategy for a stripping column used in chlorine purification. The strategy correlates the effluent concentration (process variable) with the feed flow rate (manipulated variable) to derive a transfer function. Process modeling was conducted using Aspen HYSYS, MATLAB System Identification, and Simulink, covering both steady-state and transient simulations. The methodology included operational data collection, analysis, and PID controller tuning via trial-and-error, Ziegler-Nichols, and Cohen-Coon methods. Results demonstrated that the trial-and-error method outperformed conventional techniques, achieving optimal PID parameters with IAE = 1 and ITAE = 1.5. After incorporating sensor and actuator gains, performance metrics were IAE = 3001 and ITAE = 14,800 for FIC-002 (flow control), and IAE = 144 with ITAE = 792 for AIC-001 (temperature control), reducing overshoot and settling time. These findings validate the superiority of empirical tuning over theoretical methods for nonlinear systems. In conclusion, the proposed cascade control strategy enhances operational efficiency and safety, highlighting the importance of integrating simulation and practical control in complex industrial processes.