Performance Comparison of Advanced Control Strategies Based on Optimization for Active Suspension Under Real Vertical Speed Reducers Excitation | Zendy

Tugrulhan Akgul | Zendy; Ali Unluturk | Zendy

Open Access

Performance Comparison of Advanced Control Strategies Based on Optimization for Active Suspension Under Real Vertical Speed Reducers Excitation

Author(s) -

Tugrulhan Akgul,

Ali Unluturk

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.2025.3613460

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

In this study, real vertical speed reducers (VSRs) were modeled according to ITE standards and applied as road inputs to an active suspension system (ASS). Proportional-Integral-Derivative (PID), Fractional-Order-PID (FO-PID), Sigmoid-PID (S-PID), Sigmoid-Based Fractional-PID (SFO-PID), Exponential-PID (E-PID) and Linear Quadratic Regulator (LQR) controllers are designed for the ASS. The parameters of the controllers are optimized using methods such as Artificial Bee Colony (ABC), Golden Jackal Optimization (GJO), Mayfly Optimization (MFO), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA). The root mean square (RMS) values of vertical body acceleration (VBA), vertical tire acceleration (VTA), suspension travel (SM), and dynamic load coefficients (DLC), which are the key performance indices of ASS, as well as error-performance indices such as integral of absolute value of error (IAE), integral of squared error (ISE), time integral of absolute value of error (ITAE), and time integral of squared error (ITSE), are compared with the advanced control methods and Passive Suspension (PS). The proposed MFO-E-PID provides 56.07% improvement in RMS values for VBA, 26.71% for VTA, 10.17% for SM, and 29.37% for DLC compared to PS; and 7.97% improvement in VBA, 3.99% for VTA, 2.37% for SM, and 2.77% for DLC compared to the second best, MFO-LQR. The MFO-E-PID method provided 30.45%, 49.99%, 23.58%, and 46.27% improvement in error-performance indices for IAE, ISE, ITAE, and ITSE, respectively, compared to PS; and 6.03%, 16.14%, 4.71%, and 17.20% improvement compared to MFO-LQR. Real-time tests have shown that MFO-E-PID improves ASS performance, safety, and comfort, and holds promise for future vehicles.

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