Robustness Analysis Of An Optimized Controller Via Particle Swarm Algorithm

• Main Authors: Chong, Chee Soon, Ghazali, Rozaimi, Jaafar, Hazriq Izzuan, Syed Hussein, Syarifah Yuslinda, Md Rozali, Sahazati
• Format: Article
• Language: English
• Published: American Scientific Publishers 2017
• Online Access: http://eprints.utem.edu.my/id/eprint/21214/2/20171101_Advanced_Science_Letter_Chong.pdf; http://eprints.utem.edu.my/id/eprint/21214/; http://www.ingentaconnect.com/content/asp/asl/2017/00000023/00000011/art00165; https://doi.org/10.1166/asl.2017.10248

This paper deals with an evaluation on the effectiveness of the robust controller in terms of its robustness towards the changes in the electro-hydraulic actuator (EHA) system parameters. It is well known that the defects exposed in this system are the existence of disturbances, parameters variation, and uncertainties in nature that yielding great difficulties in the development of system controller and the modelling of EHA system. Such difficulties simultaneously vitiating system performance and imposed if inappropriate control strategy is employed. A nonlinear EHA system model is established and the proposed controller which is sliding mode controller (SMC) is implemented in the simulation studies. The proposed control strategy has been compared with the conventional proportional-integral-derivative (PID) controller concerning its robustness characteristic with the variation in the system supply pressure in which the controller variables are obtained through particle swarm optimization (PSO) algorithm. The finding shows that the SMC that utilized the PSO algorithm parameters are capable to produce smaller robustness index values, which demonstrated better robustness characteristic in confront with the variation of the system parameter.