Nonsquare Multivariable Chemical Processes: A Hybrid Centralized Control Proposal
2020
Revelo, Jefferson | Herrera, Marco | Camacho, Oscar | Alvarez, Hernan
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 δ and 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.
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