Design of the LQR controller and observer with fuzzy logic GA and GA-PSO algorithm for triple an inverted pendulum and cart system. Molazadeh, V. R., Banazadeh, A., & Shafieenejad, I. In Proceedings of the 2014 International Conference on Advanced Mechatronic Systems, pages 295–300, August, 2014. doi abstract bibtex In this paper, designing of the LQR controller and observer with intelligent tools for the triple inverted pendulum is investigated. Intelligent tools are considered as GA and GA-PSO optimization algorithms and fuzzy logic to qualify achieving LQR gains. The pendulum is swung up from the vertical position to the unstable position. The rules for the controlled swing up are heuristically achieved such that each swing results are controlled. The inverted pendulum and cart system are modeled and constructed their equation based on energy method. Also, the performances of the proposed fuzzy logic controller, GA and GA-PSO tuning LQR gains are investigated and compared. Simulation results show that the fuzzy Logic Controllers are far more superior in terms of overshoot, settling time and response to parameter changes.
@inproceedings{molazadeh_design_2014,
title = {Design of the {LQR} controller and observer with fuzzy logic {GA} and {GA}-{PSO} algorithm for triple an inverted pendulum and cart system},
doi = {10.1109/ICAMechS.2014.6911560},
abstract = {In this paper, designing of the LQR controller and observer with intelligent tools for the triple inverted pendulum is investigated. Intelligent tools are considered as GA and GA-PSO optimization algorithms and fuzzy logic to qualify achieving LQR gains. The pendulum is swung up from the vertical position to the unstable position. The rules for the controlled swing up are heuristically achieved such that each swing results are controlled. The inverted pendulum and cart system are modeled and constructed their equation based on energy method. Also, the performances of the proposed fuzzy logic controller, GA and GA-PSO tuning LQR gains are investigated and compared. Simulation results show that the fuzzy Logic Controllers are far more superior in terms of overshoot, settling time and response to parameter changes.},
booktitle = {Proceedings of the 2014 {International} {Conference} on {Advanced} {Mechatronic} {Systems}},
author = {Molazadeh, V. R. and Banazadeh, A. and Shafieenejad, I.},
month = aug,
year = {2014},
keywords = {Controller, Couplings, Equations, Evolutionary optimization, Fuzzy logic, GA-PSO optimization algorithms, LQR, LQR controller design, LQR gains, Mathematical model, Observer, Observers, Optimization, Triple vertical pendulum, Tuning, cart system, control system synthesis, fuzzy logic, fuzzy logic GA, fuzzy logic controller, genetic algorithms, intelligent tools, linear quadratic control, nonlinear systems, observer, observers, particle swarm optimisation, pendulums, triple inverted pendulum, triple pendulum},
pages = {295--300},
}
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The inverted pendulum and cart system are modeled and constructed their equation based on energy method. Also, the performances of the proposed fuzzy logic controller, GA and GA-PSO tuning LQR gains are investigated and compared. 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