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Optimal controller design for a railway vehicle suspension system using particle swarm optimization
Arfah Syahida Mohd Nor1, Hazlina Selamat2, Ahmad Jais Alimin3.
This paper presents the design of an active suspension control of a two-axle railway vehicle using an optimized linear quadratic regulator (LQR). The control objective is to minimize the lateral displacement and yaw angle of the wheelsets when the vehicle travels on straight and curved tracks with lateral irregularities. In choosing the optimum weighting matrices for the LQR, the Particle
Swarm Optimization (PSO) method has been applied and the results of the controller performance
with weighting matrices chosen using this method is compared with the commonly used, trial and
error method. The performance of the passive and active suspension has also been compared. The
results show that the active suspension system performs better than the passive suspension system. For the active suspension, the LQR employing the PSO method in choosing the weighting matrices provides a better control performance and a more systematic approach compared to the trial and error method.
Affiliation:
- Universiti Teknologi Malaysia, Malaysia
- Universiti Teknologi Malaysia, Malaysia
- Universiti Tun Hussein Onn Malaysia, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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