Adaptive Robust Control Strategy With Recursive Priority Based Fitness Particle Swarm Optimization For An Electro Hydraulic Actuator System

• Main Authors: Ghazali, Rozaimi, Rahmat, Mohd Fua’ad, Md. Sam, Yahaya, Yusof, Ahmad Anas, Jaafar, Hazriq Izzuan, Hanafi, Dirman
• Format: Technical Report
• Language: English
• Published: UTeM 2019
• Online Access: http://eprints.utem.edu.my/id/eprint/25474/1/Adaptive%20Robust%20Control%20Strategy%20With%20Recursive%20Priority%20Based%20Fitness%20Particle%20Swarm%20Optimization%20For%20An%20Electro%20Hydraulic%20Actuator%20System.pdf; http://eprints.utem.edu.my/id/eprint/25474/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=118047

Recently, electrohydraulic actuator (EHA) system has become progressively crucial in various types of engineering equipment particularly in transportation industries such as in earth moving transportation, flight applications, automotive, agricultural machinery and military equipment. However, it is challenging to obtain optimal controller parameters due to the time-varying in EHA system’s parameters and the existence of disturbances. These conditions might effects actuator system’s performance, robustness and its adaptability characteristics that generally will reduce energy efficiency in the engineering design. If the robust controller’s variables and adaptation parameters can be optimized recursively, optimum design controller can be obtained and improved simultaneously. Therefore, this study is conducted to characterize the adaptive mechanism of recursive optimization with robust control that will optimize the controller parameters recursively. This study also has been successfully formulated a recursive optimization scheme with sliding mode controller (SMC) by using priority-based fitness particle swarm optimization (PFPSO) technique which will enhances the actuator system’s performance, controller robustness and its adaptability characteristics. Then, this study the adaptability mechanism and robustness of the recursive adaptive robust controller under the presence of disturbances and uncertainties also has been evaluated. Finally, validation on the controller performances in the presence of disturbances and uncertainties through the simulation and experimental studies has been conducted so that the optimum value of the controller designs can be evaluated. The optimally designed controller is effective to be implemented and enhanced energy efficiency problems in other applications considering the trade-off between the system’s response, controller robustness and adaptability performance. This fundamental works has bring significant information, knowledge and understanding to the transportation and orbanization particularly for industries in optimizing the variables and parameters of the adaptive robust controller design. As conclusion, the implementation of the optimally designed controller has successfully enhanced the performance of the actuator and potential to be implemented in various industrial applications.