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Algorithms 2017, 10(1), 19; doi:10.3390/a10010019

Pressure Control for a Hydraulic Cylinder Based on a Self-Tuning PID Controller Optimized by a Hybrid Optimization Algorithm

1
School of Mechatronic Engineering, China University of Mining & Technology, No. 1 Daxue Road, Xuzhou 221116, China
2
CRRC Tangshan Corporation Limited, No. 3 Changqian Road, Fengrun District, Tangshan 063000, China
*
Authors to whom correspondence should be addressed.
Academic Editor: George Karakostas
Received: 24 November 2016 / Revised: 9 January 2017 / Accepted: 18 January 2017 / Published: 23 January 2017
(This article belongs to the Special Issue Metaheuristic Algorithms in Optimization and Applications)
View Full-Text   |   Download PDF [2032 KB, uploaded 23 January 2017]   |  

Abstract

In order to improve the performance of the hydraulic support electro-hydraulic control system test platform, a self-tuning proportion integration differentiation (PID) controller is proposed to imitate the actual pressure of the hydraulic support. To avoid the premature convergence and to improve the convergence velocity for tuning PID parameters, the PID controller is optimized with a hybrid optimization algorithm integrated with the particle swarm algorithm (PSO) and genetic algorithm (GA). A selection probability and an adaptive cross probability are introduced into the PSO to enhance the diversity of particles. The proportional overflow valve is installed to control the pressure of the pillar cylinder. The data of the control voltage of the proportional relief valve amplifier and pillar pressure are collected to acquire the system transfer function. Several simulations with different methods are performed on the hydraulic cylinder pressure system. The results demonstrate that the hybrid algorithm for a PID controller has comparatively better global search ability and faster convergence velocity on the pressure control of the hydraulic cylinder. Finally, an experiment is conducted to verify the validity of the proposed method. View Full-Text
Keywords: self-tuning PID controller; genetic algorithm; particle swarm optimization algorithm; pressure control self-tuning PID controller; genetic algorithm; particle swarm optimization algorithm; pressure control
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MDPI and ACS Style

Wang, R.; Tan, C.; Xu, J.; Wang, Z.; Jin, J.; Man, Y. Pressure Control for a Hydraulic Cylinder Based on a Self-Tuning PID Controller Optimized by a Hybrid Optimization Algorithm. Algorithms 2017, 10, 19.

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