Design of Optimal Ship Steering Active Disturbance Rejection Controller Based on Adaptive Particle Swarm Optimization

In this study, it has proposed to adjust the parameters of the Linear Effective Distortion Prevention Controller (LADRC) with the Symbiotic Organism Search (SOS) algorithm. The parameters of LADRC were determined by both traditional methods and Symbiotic Organism Search (SOS) algorithm, and comparative analyzes were performed on the speed control performances of permanent magnet direct current motor (PMDCM). Two different reference signals have applied to both systems and monitoring performances were presented graphically and also in the form of a table containing the mean of the squared errors. Simulation-based results have shown that LADRC, which already has a powerfull control performance, can create a faster system response, especially in steep transitions and deterioration points in the reference mark, by adjusting its parameters offline with the SOS algorithm. This situation has caused a decrease in total tracking error and revealed that SOS optimized LADRC has a better tracking performance.

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Design of Optimal Ship Steering Active Disturbance Rejection Controller Based on Adaptive Particle Swarm Optimization

Cited by 2 publications

References 6 publications

Improved Grey Wolf Optimizer Tuned Active Disturbance Rejection Control for Ship Heading

Improved Grey Wolf Optimizer Tuned Active Disturbance Rejection Control for Ship Heading

Doğrusal Etkin Bozucu Engellemeli Denetleyici Parametrelerinin SOS Algoritması ile Ayarlanması

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