Nonsquare Multivariable Chemical Processes: A Hybrid Centralized Control Proposal

This paper presents a hybrid centralized control scheme for a nonsquare multivariable process. The proposed approach combines the Smith predictor, gain-scheduling methodology, and Davison method with the Particle Swarm Optimization (PSO) algorithm, all of which are combined to solve a nonsquare control-system problem that compensates for the multiple and different time delays and process nonlinearities. We call this fusion a hybrid control scheme. The Davison method does not provide a fine-tuning methodology for the centralized controller; therefore, the PSO method is added. This optimization method yields the best values for δand ϵ, improving the process response with a smoother controller action, with a trade-off between the performance and robustness of the proposed controller. This method is applied to a reactor-separator-recycle (R-S-R) plant. These process types are characterized as being subjected to strong interactions among its variables and present strong nonlinearities. The R-S-R plant is modeled using the identification method based on the reaction curve, from which its equivalent transfer function (ETF) is determined. ETF represents a multivariable system with multiple time delays. In the current proposal, the nonlinearities that are present in the R-S-R system are compensated using the gain-scheduling strategy. The simulation tests verify the performance of the proposed controller, which is performed in MatLab. This controller is compared with a proportional integral (PI)-centralized controller and Smith delay compensator. All controllers are tuned using PSO.