An approach of dynamic sliding mode control for chemical processes. (January 2020)

• Record Type: Journal Article
• Authors: Herrera, Marco; Camacho, Oscar; Leiva, Hugo; Smith, Carlos
• Is Part Of: Journal of process control. Volume 85(2020)
• Page Start: 112
• Page End: 120
• Publication Date: 2020-01
• Subjects: SMC -- Chemical processes -- Dynamic sliding mode control; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2019.11.008
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: An alternative to improve the performance of the SMC while avoiding chattering is proposed. The approach is called dynamic sliding mode control. The approach strategy result in substantially smoothed control input signals and the possibility of chattering free controller responses. An efficient alternative and adequate for process control analysis and design based on empirical models is used. This approach gives a better control performance to processes with dead-time or inverse responses. This proposal is robust when facing modelling mismatches, and it reduces or eliminates the chattering problem. Abstract: The purpose of this paper is to develop a Dynamic Sliding Mode Controller (DSMC) based on the Iinoya and Altpeter approach and the Sliding Mode Control (SMC) design procedure. The proposed approach is applied to chemical processes of high order with long dead time, and with inverse response. A simulation of a nonlinear mixing tank with variable delay, and an implementation on an Arduino Temperature Control Lab are used to test the controller. A comparison of the proposed approach (DSMC), and the SMC based on Internal Model Control (IMC) is presented to evaluate advantages and disadvantages of the proposal. The results show that the approach of the DSMC presented in this work reduces the chattering, compensates the effect of external disturbances, and of the parametric uncertainties. To measure the controller's performance, the Integral Square Error index (ISE) and Total Variation index (TV) are used.