International Journal of Modelling and Simulation
ISSN: 0228-6203 (Print) 1925-7082 (Online) Journal homepage: http://www.tandfonline.com/loi/tjms20
Modeling and identification of hydraulic servo systems Magdy A. S. Aboelela, Mohamed El-Sayed M. Essa & M. A. Mustafa Hassan To cite this article: Magdy A. S. Aboelela, Mohamed El-Sayed M. Essa & M. A. Mustafa Hassan (2017): Modeling and identification of hydraulic servo systems, International Journal of Modelling and Simulation, DOI: 10.1080/02286203.2017.1405713 To link to this article: https://doi.org/10.1080/02286203.2017.1405713
Published online: 12 Dec 2017.
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Date: 12 December 2017, At: 20:11
International Journal of Modelling and Simulation, 2017 https://doi.org/10.1080/02286203.2017.1405713
Modeling and identification of hydraulic servo systems Magdy A. S. Aboelelaa , Mohamed El-Sayed M. Essab
and M. A. Mustafa Hassana
a
Faculty of Engineering, Electric Power and Machines Department, Cairo University, Giza, Egypt; bIAET, Imbaba Airport, Giza, Egypt
ARTICLE HISTORY
Downloaded by [156.196.213.110] at 20:11 12 December 2017
ABSTRACT
The goal of this research is to implement a nonlinear simulation model of hydraulic servo system (HSS).The model is based on physical laws as well as experimental identification of piston position. It also presents the tuning of PID/PI controller’s parameters using particle swarm optimization technique. The mathematical model includes the most nonlinear effects that are involved in the hydraulic system under study. The dynamics of hydraulic systems are highly nonlinear due to directional change of valve opening, friction forces, and oil compressibility. The model describes the behavior of a servo system BOSCH REXROTH servo valve (4WRSE). It has been developed using MATLAB/SIMULINK. The main objective of the simulation modeling and system identification for electro-hydraulic servo valve is to obtain good performance of its dynamic and nonlinear behavior. The identified model has been found to be a third-order continuous time model. The identification of HSS is performed by using System Identification Toolbox of MATLAB. The obtained results are promising and satisfactory. In addition, the simulation and experimental results have shown the superiority of using PID controller type for requirement of minimum settling time and the PI controller type for minimum value of percentage overshoot.
1. Introduction The hydraulic servo systems (HSS) are considered as a magic tool in many industrial and non-industrial applications [1,2]. This is not only due to its powerful supply for large force but also for its accurate control of the response. Examples of the applications of HSS are mobile lifting, digging, material handling equipment, machine tool drives, flight simulators, rolling mills, and control surfaces of aircraft. The HSS is a system consisting of motor, servo, controller, power supply, sensors (position, velocity, force, or pressure), and actuating cylinders as mentioned in [3,4]. The HSS consists of axial pump (A10VSO), BOSCH REXROTH servo valve, two hydraulic actuating cylinders with face-to-face connection, and linear displacement transducer. The mathematical modeling, which captures most of nonlinear dynamics of HSS and system identification, can be developed using MATLAB/SIMULINK software package. Nonlinear models of HSS are based on differential equations which govern the system dynamics. In addition, the continuous time hydraulic system model can be identified by manipulating the experimental hardware system as it will be explained later in this paper. This research also aims to introduce the design of proportional integral derivative controller that can be tuned by particle swarm optimization (PSO) techniques taking into consideration two types of objective functions. The main difficulties facing the researchers while designing and implementing the control strategies for a certain application are the process of how to build a model to simulate the desired control system as well as the investigation of experimental hardware for this
CONTACT Magdy A. S. Aboelela
[email protected]
© 2017 Informa UK Limited, trading as Taylor & Francis Group
Received 22 January 2017 Accepted 13 November 2017 KEYWORDS
Hydraulic servo system (HSS); system identification; particle swarm optimization (PSO); proportional- integralderivative (PID)
system. Therefore, the simulation model is the starting point of any control strategy design. For these reasons, this research has focused on the implementation of a simulation model for an industrial application as electro hydraulic servo system and verified the output results of the model. A new method for friction identification of electro-hydraulic servo system (EHSS) is given in [5]. This approach is based on evolutionary algorithm and statistical logics. The obtained simulation results have been verified with experimental hardware system. This work focuses only on a certain part of the hydraulic system not the whole system. A numerical simulation and experimental validation of L-Shaped check valve ball-type behavior has been presented in [6]. In this endeavor, a full-scale model of a check ball, made from acrylic resin, is investigated. In addition, the relationship between the initial position of the ball and the position and diameter of the inflow port is determined. In Ref. [7], the authors investigated the effect of the design parameters on cavitations of a solenoid valve of an electric vehicle braking system. In addition, they provided an optimal design to minimize the cavitations using an optimization technique. However, they didn’t implement a model for all the components of hydraulic system. Moreover, in [8], the researchers studied the increase of the efficiency of electro-hydraulic system by controlling the variable supply in the system and the pressure during the task of position tracking. For this purpose, an EHSS structure with controllable supply pressure was proposed and its dynamic model was derived from the basic laws of physics. In addition, an extended state observer (ESO) of the hydraulic systems with back stepping was discussed in [9]. In this work, the researchers
