PSO fine-tuned model-free PID controller with derivative filter for depth control of hovering autonomous underwater vehicle

Mohd Zaidi, Mohd Tumari and Amar Faiz, Zainal Abidin and Mohamed Saiful, Firdaus Hussin and Ahmad Muzaffar, Abd Kadir and Mohd Shahrieel, Mohd Aras and Mohd Ashraf, Ahmad (2019) PSO fine-tuned model-free PID controller with derivative filter for depth control of hovering autonomous underwater vehicle. In: Proceedings of the 10th National Technical Seminar on Underwater System Technology 2018, 27-28 September 2018 , Universiti Malaysia Pahang. pp. 3-13., 538. ISBN 978-981-13-3708-6

PSO Fine-Tuned Model-Free PID Controller with Derivative Filter for Depth.pdf

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The tuning of PID controller by classical technique is a monotonous job and may results in inaccurate system response. This paper proposes investigations into the development of a model-free PID controller with derivative filter (PIDF) parameter tuning method by using Particle Swarm Optimization (PSO) for depth control of Hovering Autonomous Underwater Vehicle (HAUV). PIDF controller is developed to control the speed of th1usters where 4 PIDF parameters are fine-tuned using PSO algorithms and Sum Absolute Error (SAE) and Sum Square En·or (SSE) are chosen as it fitness functions. In order to confirm the design of control scheme, one degree of freedom nonlinear equation of the HAUV system in heave direction is considered. Supremacy of the proposed approach is shown by comparing the results with PID Tuner in Simulink/MATLAB. The performances of the control schemes are accessed in terms of time response specifications of depth tracking capability with the absences of added mass, hydrodynamic drag force, buoyancy force, model nonlinearities, and external disturbances on the HAUV system. Finally, it is seen from the simulation results that the proposed control technique guarantees a fast depth tracking capability.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Lecture Notes in Electrical Engineering book series
Uncontrolled Keywords: Particle swarm optimization: PID controller Hovering autonomous underwater vehicle (HAUV)
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 03 Sep 2019 03:01
Last Modified: 03 Sep 2019 03:01
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