TY - JOUR
T1 - Adaptive Controller Tuning Method Based on Online Multiobjective Optimization
T2 - A Case Study of the Four-Bar Mechanism
AU - Rodriguez-Molina, Alejandro
AU - Villarreal-Cervantes, Miguel G.
AU - Mezura-Montes, Efren
AU - Aldape-Perez, Mario
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2021/3
Y1 - 2021/3
N2 - The efficient speed regulation of four-bar mechanisms is required for many industrial processes. These mechanisms are hard to control due to the highly nonlinear behavior and the presence of uncertainties or disturbances. In this paper, different Pareto-front approximation search approaches in the adaptive controller tuning based on online multiobjective metaheuristic optimization are studied through their application in the four-bar mechanism speed regulation problem. Dominance-based, decomposition-based, metric-driven, and hybrid search approaches included in the algorithms, such as nondominated sorting genetic algorithm II, multiobjective evolutionary algorithm based on decomposition and differential evolution, S-metric selection evolutionary multiobjective algorithm, and nondominated sorting genetic algorithm III, respectively, are considered in this paper. Also, a proposed metric-driven algorithm based on the differential evolution and the hypervolume indicator (HV-MODE) is incorporated into the analysis. The comparative descriptive and nonparametric statistical evidence presented in this paper shows the effectiveness of the adaptive controller tuning based on online multiobjective metaheuristic optimization and reveals the advantages of the metric-driven search approach.
AB - The efficient speed regulation of four-bar mechanisms is required for many industrial processes. These mechanisms are hard to control due to the highly nonlinear behavior and the presence of uncertainties or disturbances. In this paper, different Pareto-front approximation search approaches in the adaptive controller tuning based on online multiobjective metaheuristic optimization are studied through their application in the four-bar mechanism speed regulation problem. Dominance-based, decomposition-based, metric-driven, and hybrid search approaches included in the algorithms, such as nondominated sorting genetic algorithm II, multiobjective evolutionary algorithm based on decomposition and differential evolution, S-metric selection evolutionary multiobjective algorithm, and nondominated sorting genetic algorithm III, respectively, are considered in this paper. Also, a proposed metric-driven algorithm based on the differential evolution and the hypervolume indicator (HV-MODE) is incorporated into the analysis. The comparative descriptive and nonparametric statistical evidence presented in this paper shows the effectiveness of the adaptive controller tuning based on online multiobjective metaheuristic optimization and reveals the advantages of the metric-driven search approach.
KW - Adaptive tuning
KW - four-bar mechanism
KW - intelligent control
KW - metaheuristics
KW - multiobjective optimization
UR - http://www.scopus.com/inward/record.url?scp=85101176215&partnerID=8YFLogxK
U2 - 10.1109/TCYB.2019.2903491
DO - 10.1109/TCYB.2019.2903491
M3 - Artículo
C2 - 30908253
AN - SCOPUS:85101176215
SN - 2168-2267
VL - 51
SP - 1272
EP - 1285
JO - IEEE Transactions on Cybernetics
JF - IEEE Transactions on Cybernetics
IS - 3
M1 - 8673799
ER -