Eventos Anais de eventos
COBEM 2017
24th ABCM International Congress of Mechanical Engineering
Bio-inspired optimation applied to the tuning of model predictive control parameters
Submission Author:
Eduardo Mesquita , GO
Co-Authors:
CARLOS H Llanos, Renato Sampaio, Eduardo Mesquita
Presenter: Eduardo Mesquita
doi://10.26678/ABCM.COBEM2017.COB17-2851
Abstract
Model Predictive Control (MPC) is a control strategy that uses a system dynamic model to predict its behaviour over a time horizon and has become a widely used tool in the industry. Different systems require different control settings and the choice of parameters is not an easy task. This paper proposes a tuning application of MPC parameters using bio-inspired algorithms: Particle Swarm Optimization (PSO) and Salp Swarm Algorithm (SSA). PSO is an algorithm proposed in 1995 and has been applied in several optimization problems. SSA is one of the newest proposed bio-inspired algorithm. The plant is a Triple Integrator and performance metric is the quadratic error between system output and the reference. The convergence error is faster with PSO than SSA, but the latter converges to the target at the end of the iterations. The results show SSA as efficient as PSO in minimization problems.
Keywords
MPC, bioinspired algorithm, optimation, PSO, SSA
