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Application of Fuzzy Logic Sliding Mode Control Approach with PID Structure for Electro-Hydraulic Actuator Tracking System
Author(s) -
Muhamad Fadli Ghani,
Ahmad Athif Mohd Faudzi,
Rozaimi Ghazali,
Shahrol Mohamaddan
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3575908
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The electro-hydraulic actuator (EHA) system generates a trajectory by transferring high force densities in the form of pressurized fluid flows to a hydraulic actuator. Moreover, the sliding mode control (SMC) approach has been discovered as a potential method for the EHA trajectory tracking control system. However, high-frequency proportional valve activity has occurred during the practical application of the conventional SMC approach, resulting in tracking performance degradation. Furthermore, a preferable SMC sliding surface design is necessary to improve the precision of trajectory tracking performance, and the SMC designs involve complicated procedure and mathematical formulations. Therefore, this paper proposes a hybrid optimized fuzzy logic (FL) SMC with a proportional-integral-derivative (PID) structure (FLSMCPID) for precise trajectory tracking control in an EHA system. The proposed control strategy was designed with the switching function modification based on an FL approach in the conventional SMC algorithm. Due to the difficulty of concurrent hybrid design, a particle swarm optimization (PSO) algorithm was employed to determine the optimal control variables value. Simulations utilizing a linear EHA system model obtained using the grey-box identification approach and experimentation on an EHA system workbench for various trajectories and under the consequences of variation in supply pressure were conducted to evaluate the performance of the proposed control strategy. The simulation and experimental results demonstrate that higher effectiveness, precision, and robustness were achieved by the EHA system with the proposed control strategy.

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