Open AccessLiquid slosh control by implementing model-free PID controller with derivative filter based on PSO
Author(s) -
Mohd Zaidi Mohd Tumari,
Amar Faiz Zainal Abidin,
A Shamsul Rahimi A Subki,
Ab Wafi Ab Aziz,
Muhammad Salihin Saealal,
Mohd Ashraf Ahmad
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v18.i2.pp750-758
Subject(s) - slosh dynamics , control theory (sociology) , particle swarm optimization , pid controller , controller (irrigation) , engineering , filter (signal processing) , computer science , control engineering , algorithm , control (management) , temperature control , agronomy , electrical engineering , artificial intelligence , biology , aerospace engineering
Conventionally, the control of liquid slosh system is done based on model-based techniques that challenging to implement practically because of the chaotic motion of fluid in the container. The aim of this article is to develop the tuning technique for model-free PID with derivative filter (PIDF) parameters for liquid slosh suppression system based on particle swarm optimization (PSO). PSO algorithm is responsible to find the optimal values for PIDF parameters based on fitness functions which are Sum Squared Error (SSE) and Sum Absolute Error (SAE) of the cart position and liquid slosh angle response. The modelling of liquid slosh in lateral movement is considered to justify the design of control scheme. The PSO tuning method is compared by heuristic tuning method in order to show the effectiveness of the proposed tuning approach. The performance evaluations of the proposed tuning method are based on the ability of the tank to follow the input in horizontal motion and liquid slosh level reduction in time domain. Based on the simulation results, the suggested tuning method is capable to reduce the liquid slosh level in the same time produces fast input tracking of the tank without precisely model the chaotic motion of the fluid.