Title :
Optimal robust decoupled sliding mode control based on a Multi-objective Genetic Algorithm
Author :
Sahnehsaraei, Morteza Andalib ; Mahmoodabadi, Mohammad Javad ; Taherkhorsandi, Milad
Author_Institution :
Iranian Gas Transm. Co., Nat. Iranian Gas Co., Ramsar, Iran
Abstract :
Optimal design of the decoupled sliding mode control (SMC) is a great and worthwhile challenge by regarding appropriate design parameters and objective function. In the present study, Genetic Algorithm (GA) is employed as an effectual smart evolutionary algorithm to design optimally the control coefficients of an Inverted Pendulum (IP) and to eliminate tedious and repetitive trial-and-error process. When decoupled SMC is used to address the problem, there has to be a trade-off between the error of the position and the error of the angle. Hence, a Multi-objective Genetic algorithm is used to design optimally the Pareto front of the problem by regarding the errors as objective functions. Moreover, simulation has been done by considering the case with external disturbance and without external disturbance. Then, the results implemented in the MATLAB software environment are contrasted with the experimental results. Numerical results and comparison analysis elucidates the superiority of the optimal robust proposed controller over the traditional decoupled sliding mode controller in terms of attenuating the chattering and actuator variations.
Keywords :
Pareto optimisation; control system synthesis; genetic algorithms; nonlinear control systems; optimal control; pendulums; robust control; variable structure systems; MATLAB software environment; Pareto front; SMC; actuator variations; angle error; chattering attenuation; comparison analysis; control coefficients; design parameters; effectual smart evolutionary algorithm; external disturbance; inverted pendulum; multiobjective genetic algorithm; objective function; optimal design; optimal robust decoupled sliding mode control; position error; Genetic algorithms; Linear programming; Mathematical model; Optimization; Robustness; Sliding mode control; Vectors; Genetic Algorithm; Inverted Pendulum System; Multi-objective Optimization; Sliding Mode Control;
Conference_Titel :
Innovations in Intelligent Systems and Applications (INISTA), 2013 IEEE International Symposium on
Conference_Location :
Albena
Print_ISBN :
978-1-4799-0659-8
DOI :
10.1109/INISTA.2013.6577641