Mechatronic Hydraulic Drive with Regulator, Based on Artificial Neural Network

Burennikov, Yuri; Kozlov, Leonid; Pyliavets, Volodymyr; Piontkevych, Oleh

doi:10.1088/1757-899x/209/1/012071

Cited by 13 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Simulation modeling [9][10][11][12]18,19,[24][25][26] of hydraulic drive control system of mobile machines by means of program products MAPLE, MATLAB Simulink, ANSYS, Solidworks Flow Simulation, Autodesk Simulation CFD enables to solve complex engineering problems of hydraulic equipment design. Such method of the design is economically efficient and accurate.…”

Section: Analysis Of the Studies Of The Hydraulic Drives Control Systmentioning

confidence: 99%

Experimental research characteristics of counterbalance valve for hydraulic drive control system of mobile machine

Kozlov¹

2019

ELECTROTECHNICAL REVIEW

View full text Add to dashboard Cite

Experimental studies of counterbalance valve for the hydraulic drive control systems of mobile machines are presented. According to the results of theoretical research experimental prototype of the counterbalance valve is developed. Experimental stands are elaborated, where leak tightness degree was studied and static characteristics were obtained. Dependences of operating fluids supply on the parameters of the pressure difference at its basic spool and load pressure are plotted. Transient processes in the hydraulic drive control system are analyzed, adequacy of the theoretical calculations to the elaborated mathematical models for the control system of mobile machine hydraulic drive is proved.Streszczenie. Przedstawiono badania eksperymentalne zaworu równoważącego w układach sterowania napędem hydraulicznym maszyn mobilnych. Zgodnie z wynikami badań teoretycznych opracowano eksperymentalny prototyp zaworu równoważącego. Opracowano stanowiska eksperymentalne, na których badano stopień szczelności oraz uzyskano charakterystyki statyczne. Narysowano wpływ zasilania płynów eksploatacyjnych na różnicę ciśnień na szpuli podstawowej i ciśnienie obciążenia. Przeanalizowano procesy przejściowe w układzie sterowania napędem hydraulicznym, udowodniono zgodność obliczeń teoretycznych z opracowanymi modelami matematycznymi dla układu sterowania napędem hydraulicznym maszyny mobilnej. (Charakterystyki eksperymentalne zaworu równoważącego układu sterowania napędem hydraulicznym maszyny mobilnej).

show abstract

Section: Analysis Of the Studies Of The Hydraulic Drives Control Systmentioning

confidence: 99%

Experimental research characteristics of counterbalance valve for hydraulic drive control system of mobile machine

Kozlov¹

2019

ELECTROTECHNICAL REVIEW

View full text Add to dashboard Cite

show abstract

“…Mobile machines with hydraulic drive and replaceable actuating elements are widely used in industry, construction, agriculture and transport [1][2][3][4]. Such machines are efficiently operated during all seasons of the year and perform various operations due to the use of loading buckets, hydraulic hammers, excavator, drilling and crane equipment.…”

Section: Introductionmentioning

confidence: 99%

Algorithm of Controlling an Adaptive Hydraulic Circuit for Mobile Machines

Kozlov¹,

Buriennikov²,

Rusu³

et al. 2021

IJMMT

View full text Add to dashboard Cite

Hydraulic systems based on adjustable pumps, proportional electrohydraulic equipment and controllers are used in mobile machines. The authors propose a new scheme of the hydraulic system for mobile machines, which provides the auger drilling operation. A number of studies have shown that a certain ratio should be maintained between the frequency of auger rotation and its feed during operation, where the productivity of soil disruption should not exceed the productivity of transporting loose soil from the drilling zone. Ensuring the required ratio between the speed of the auger rotation and its feed is implemented by a controller that works according to a certain algorithm. A nonlinear mathematical model of the hydraulic system was developed to create the algorithm for controller operation and setting. The equations of the mathematical model are solved in the MATLAB-Simulink environment by the Rosenbrock method. As a result of solving the equations for the mathematical model, the dependences of variables describing the state of the hydraulic system on time are obtained. The values of the controller settings are determined at which the hydraulic system works steadily, the error of flow rate stabilization, the time for pressure adjustment and readjustment does not exceed the allowable values. The algorithm for controlling the auger feed value is formed. This algorithm provides the necessary ratio between the auger feed and speed, as well as reducing the feed rate in the case of soil hardness increases. This creates the conditions for uninterrupted pit drilling at full depth and protection of the hydraulic system from overload.

show abstract

“…The usage of artificial neural network (hereinafter referred to as ANN) is a reasonable solution for power flow regulators (Ma et al, 2018). Also, ANN can be used as a tool for detecting stable equivalent series resistance (ESR) in voltage regulator characterization (Zaman et al, 2018), in mechatronic hydraulic drive regulation (Burennikov et al, 2017) or autopilot (Zhao et al, 2018). However, researchers are particularly curious about the possibility of using artificial neural networks in the automatic tuning of PID regulators (Ayomoh and Ajala, 2012; Hernández-Alvarado et al, 2016; Pirabakaran and Becerra, 2002;Zhang et al, 2016;Du et al 2018;Han et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Predictive Neural Network in Multipurpose Self-Tuning Controller

Bondar

2020

Acta Mechanica Et Automatica

View full text Add to dashboard Cite

A very important problem in designing of controlling systems is to choose the right type of architecture of controller. And it is always a compromise between accuracy, difficulty in setting up, technical complexity and cost, expandability, flexibility and so on. In this paper, multipurpose adaptive controller with implementation of artificial neural network is offered as an answer to a wide range of tasks related to regulation. The effectiveness of the approach is demonstrated by the example of an adaptive thermostat. It also compares its capabilities with those of classic PID controller. The core of this approach is the use of an artificial neural network capable of predicting the behaviour of controlled object within its known range of parameters. Since such a network, being trained, is a model of a regulated system with arbitrary precision, it can be analysed to make optimal management decisions at the moment or in a number of steps. Network learning algorithm is backpropagation and its modified version is used to analyse an already trained network in order to find the optimal solution for the regulator. Software implementation, such as graphical user interface, routines related to neural network and many other, is done using Java programming language and Processing open-source integrated development environment.

show abstract

Mechatronic Hydraulic Drive with Regulator, Based on Artificial Neural Network

Cited by 13 publications

References 0 publications

Experimental research characteristics of counterbalance valve for hydraulic drive control system of mobile machine

Experimental research characteristics of counterbalance valve for hydraulic drive control system of mobile machine

Algorithm of Controlling an Adaptive Hydraulic Circuit for Mobile Machines

Predictive Neural Network in Multipurpose Self-Tuning Controller

Contact Info

Product

Resources

About