A swarm intelligence-based tuning method for the Sliding Mode Generalized Predictive Control
J B Oliveira1, J Boaventura-Cunha1, P B Moura Oliveira1
1INESC TEC - INESC Technology and Science (formerly INESC Porto, UTAD pole) Department of Engineering, School of Sciences and Technology 5001-811 Vila Real, Portugal.
Abstract:
This work presents an automatic tuning method for the discontinuous component of the Sliding Mode Generalized Predictive Controller (SMGPC) subject to constraints. The strategy employs Particle Swarm Optimization (PSO) to minimize a second aggregated cost function. The continuous component is obtained by the standard procedure, by Quadratic Programming (QP), thus yielding an online dual optimization scheme. Simulations and performance indexes for common process models in industry, such as nonminimum phase and time delayed systems, result in a better performance, improving robustness and tracking accuracy.
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