PID controller design for an industrial hydraulic actuator with servo system

Rozali, Sahazati Md.; Rahmat, M. F.; Wahab, Norhaliza Abdul; Ghazali, Rozaimi; Zulfatman,

doi:10.1109/scored.2010.5704005

Cited by 26 publications

(18 citation statements)

References 12 publications

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“…PID tuning approach such as Ziegler-Nichols [43] and Nelder-Mead [44] requires information of ultimate gain and ultimate period of oscillation in order to calculate the controller parameters. By using Ziegler-Nichols , [43] shows the increment of the best fit of the model from 92% to 98%.…”

Section: A Pid Controllermentioning

confidence: 99%

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Review on Modeling and Controller Design of Hydraulic Actuator Systems

Salleh

Rahmat

Othman

et al. 2015

International Journal on Smart Sensing and Intelligent Systems

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Abstract-The purpose of this paper is to review the literature on modeling and previous control strategies of the hydraulic actuator system proposed by most of the researchers around the world.Before comes to the main discussion, some background information related to hydraulic actuator will be presented. This review includes a short summary and conclusion for hydraulic actuator system. The repercussion of this review is for future inventions of a better and robust hydraulic actuator system.

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Section: A Pid Controllermentioning

confidence: 99%

“…By using Ziegler-Nichols , [43] shows the increment of the best fit of the model from 92% to 98%. 2) Fuzzy rules, consists of linguistic control rules which are conditional linguistic statements of the relationship between input and output, so that the property of fuzzy controller emulate the behavior of a human operator [48].…”

Section: A Pid Controllermentioning

confidence: 99%

Review on Modeling and Controller Design of Hydraulic Actuator Systems

Salleh

Rahmat

Othman

et al. 2015

International Journal on Smart Sensing and Intelligent Systems

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“…In order to solve the inverse kinematics problem, two random functions are used to produce a set of 1 and 5 from their working ranges ([ 1 min , 1 max ] and [ 5 min , 5 max ]) as the inputs. Then, 24 can be solved using the third equation of (22) immediately. Then, 6 can be solved using (20).…”

Section: Inverse Kinematicsmentioning

confidence: 99%

“…When 24 and 4 are available, 2 can be obtained. Finally, 7 can be solved using (24). Every time an unknown is solved, a judgement is conducted to make sure that the obtained solution is inside its working range.…”

Section: Inverse Kinematicsmentioning

confidence: 99%

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The Automatic Drilling System of 6R-2P Mining Drill Jumbos

Wang

Fang

Jiang

et al. 2014

Advances in Mechanical Engineering

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In order to improve the efficiency of underground mining and tunneling operations and to realize automatic drilling, it is necessary to develop the automation system for large drill jumbos. This work focuses on one such mining drill jumbo which is actually a redundant robotic manipulator with eight degrees of freedom, because it has six revolute joints and two prismatic joints. To realize the autonomous drilling operation, algorithms are proposed to calculate the desired pose of the end-effector and to solve the inverse kinematics of the drill jumbo, which is one of the key issues for developing the automation system. After that, a control strategy is proposed to independently control the eight joint variables using PID feedback control approaches. The simulation model is developed in Simulink. As the closed-loop controllers corresponding to all joints are local and independent of each other, the whole system is not a closed-loop feedback control. In order to estimate the possible maximal pose error, the analysis of the pose error caused by the errors of the joint variables is conducted. The results are satisfactory for mining applications and the developed automation system is being applied in the drill jumbos built by Mining Technologies International Inc.

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