Model predictive force control of hardware implementation for electro-hydraulic servo system

Abstract

This manuscript introduces the application of Model Predictive Control (MPC) for high force control precision in a real industrial electro-hydraulic servo system (EHSS). Moreover, it presents a fractional order control (FOC) and conventional controllers (CC) based on genetic algorithm (GA). The GA technique has been used to tune the parameters of FOC and CC approach. In order to verify the ability of the proposed controller applied to the hydraulic press machines emulator using EHSS, a hardware implementation of a test press system is also suggested and setup to be used in this research. As a result, the study has been investigated using a simulation model then verified via the experimental implementation. In fact, the EHSS plays an important role in many industrial applications, especially in flight simulators, aircraft landing gear system, material testing machine and hydraulic press machines for which the high accuracy and fast response of the force or pressure control are exceedingly necessary. Real-time experiments on the EHSS are carried out to evaluate the proposed control approach in a large system parameters variation of working environments. Considerable improvement in the performance generated by the designed MPC controller is compared with the traditional and fractional order controllers. Moreover, the results show that the performance criteria in terms of settling, rise times, system overshoots, system parameters variation and applying different test signals are good values in case of applying MPC over using FOC and CC in this study. As a general conclusion, one can conclude that the MPC has the priority of applying it in the field of the industrial EHSS. The obtained results are promising in the field of mechatronic.

Design of model predictive force control for hydraulic servo system based on cuckoo search and genetic algorithms

“…The used optimization methods were divided into two techniques such as CSA and GA. The description and explanation of GA are given in detail by Essa et al 25 while the CSA and GA are described in the following subsections.…”

“…The value of M must be chosen between 1 ≤ M ≤ P. In addition, the variable of manipulate (u) is utilized to forecast the output of the system to reduce cost function J (k). 25,36,37 More details about the MPC are given in previous works. 25,36,37…”

The Effects of Weightage Values with Two Objective Functions in iPSO for Electro-Hydraulic Actuator System

“…Several types of control approaches had been proposed by researchers to control the nonlinear EHA system, such as linear quadratic regulator [6][7][8], PID controller [9][10][11], model predictive controller [12][13][14], backstepping controller [15][16][17], sliding mode controller [18][19][20][21], and other hybrid controllers [22][23][24]. However, the PID controller is still the main choice for industrial applications due to its fast design process, simple structure, and robust control performance [25].…”

Model Predictive Control of a Shipborne Hydraulic Parallel Stabilized Platform Based on Ship Motion Prediction

“…Yuan et al [19,20] designed a MPC and PIC controller for accurate force tracking of an electro-hydraulic servo system (EHSS) and experimental result showed that the MPC-PIC controller has better robustness and dynamic and static properties than MPC and PIC controllers. Mohamed et al [21] studied the application of MPC for high force control precision in a real industrial EHSS, and the results showed that the performance of MPC controller is considerably improved compared with the traditional and fractional order controllers. Tao et al [22] presented a third order state-space model with input and output constraints to depict the dynamic behavior of the unidirectional proportional pump-controlled asymmetric cylinder systems, and designed model predictive controller and realized the high precision position control under multiple constraints effectively.…”