scholarly journals Dual-valve parallel prediction control for an electro-hydraulic servo system

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041987566
Author(s):  
Shi-jie Su ◽  
Yuan-yuan Zhu ◽  
Cun-jun Li ◽  
Wen-xian Tang ◽  
Hai-rong Wang
Keyword(s):  
Dynamic Response ◽  
Predictive Control ◽  
Servo System ◽  
High Flow ◽  
Control Performance ◽  
Proportional Integral Derivative ◽  
Hydraulic Servo ◽  
Response Performance ◽  
Hydraulic Servo System ◽  
Control Accuracy

To improve the dynamic response performance of a high-flow electro-hydraulic servo system, scholars have conducted considerable research on the synchronous and time-sharing controls of multiple valves. However, most scholars have used offline optimization to improve control performance. Thus, control performance cannot be dynamically adjusted or optimized. To repeatedly optimize the performance of multiple valves online, this study proposes a method for connecting a high-flow proportional valve in parallel with a low-flow servo valve. Moreover, this study proposes an algorithm in which a proportional–integral–derivative system and multivariable predictive control system are used as an inner loop and outer loop, respectively. The simulation and experimental results revealed that dual-valve parallel control could effectively improve the control accuracy and dynamic response performance of an electro-hydraulic servo system and that the proportional-integral-derivative–multivariable predictive control controller could further dynamically improve the control accuracy.

System identification and robust position control for electro-hydraulic servo system using hybrid model predictive control

2017 ◽  
Vol 24 (18) ◽  
pp. 4145-4159 ◽  
Author(s):  
Hai-Bo Yuan ◽  
Hong-Cheol Na ◽  
Young-Bae Kim
Keyword(s):  
System Identification ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Position Control ◽  
Servo System ◽  
Model Parameters ◽  
Integral Control ◽  
Hybrid Controller ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

This paper examined system identification using grey-box model estimation and position-tracking control for an electro-hydraulic servo system (EHSS) using hybrid controller composed of proportional-integral control (PIC) and model predictive control (MPC). The nonlinear EHSS model is represented by differential equations. We identify model parameters and verify their accuracy against experimental data in MATLAB to evaluate the validity of this mathematical model. To guarantee improved performance of EHSS and precision of cylinder position, we propose a hybrid controller composed of PIC and MPC. The controller is designed using the Control Design and Simulation module in the Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW). A LabVIEW-based experimental rig is developed to apply the proposed controller in real time. Then, the validity and performance superiority of the hybrid controller were confirmed by comparing them with the MPC and PIC results. Results of real-life experiments show improved robustness and dynamic and static properties of EHSS.

Optimization of the Dynamic Performance of the Direct Drive Volume Control System Based on Orthogonal Experiment

2014 ◽  
Vol 945-949 ◽  
pp. 2680-2684
Author(s):  
Ai Qin Huang ◽  
Yong Wang
Keyword(s):  
Control System ◽  
Dynamic Response ◽  
Orthogonal Experiment ◽  
Dynamic Performance ◽  
Servo System ◽  
Volume Control ◽  
Structure Parameters ◽  
Direct Drive ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

Direct drive volume control (DDVC) electro-hydraulic servo system has many advantages compared to the valve control system. However, its application scopes were restricted by its poor dynamic performance. To study the reason for the low dynamic response, mechanical model of DDVC electro-hydraulic servo system is established. Structure parameters influencing the dynamic performance are analyzed. To optimize the structure parameters, the methodology of orthogonal experiment is presented. The selection of factors and levels of the experiment and the choice of the evaluation index are also revealed. The proposed methodology is carried out by simulation software and an optimal configuration is obtained. The dynamic response of the DDVC system with the optimal parameters is simulated. The results show that the dynamic performances are improved. The cross-over frequencyincreases from 0.0046 rad/s to 0.0442 rad/s, and the rise time Tr decreases from 488.6s to 47.90s.

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

2019 ◽  
Vol 234 (6) ◽  
pp. 701-714 ◽  
Author(s):  
Mohamed El-Sayed M Essa ◽  
Magdy AS Aboelela ◽  
MA Moustafa Hassan ◽  
SM Abdrabbo
Keyword(s):  
Genetic Algorithm ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Search Algorithm ◽  
Servo System ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Switching Model ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

This article discusses a system identification based on a black-box state-space model for an experimental electro-hydraulic servo system. Furthermore, it presents force-tracking control for the electro-hydraulic servo system based on model predictive control. The parameters of model predictive controls have been tuned by cuckoo search algorithm as well as genetic algorithm. The realization of model predictive controls depends on using a data acquisition card (NI-6014) and Simulink/MATLAB as the core of the electro-hydraulic servo system control system. In this research, the combination of model predictive control tuned by cuckoo search algorithm and genetic algorithm has been introduced in the form of switching model predictive controls. This combination collects the advantages of two model predictive controls in one model predictive control by switching model predictive controls. The simulation and experimental results display that the suggested switching of model predictive controls introduces a good tracking performance in terms of settling time, rise time, and system overshoots as compared to the two separated model predictive controls. In addition, the experimental evaluation has shown that the proposed switching model predictive controls achieved a stable and robust control system even facing to a different reference command signals (step, multistep, and sinusoidal signals). Moreover, its behavior is more robust for system parameters perturbation and small or large perturbation of disturbances in the working environment. It also achieves the necessitated physical limits of the actuator. As a general conclusion and a deep study of electro-hydraulic servo system, one can conclude that the switching strategy between model predictive control tuned by cuckoo search algorithm and by genetic algorithm has the priority of applying it on the field of electro-hydraulic servo system. The proposed new strategy (switching of model predictive control) is promising in experimental applications.

scholarly journals Experimental evaluation of the parameter-based closed-loop transfer function identification for electro-hydraulic servo systems

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668442 ◽  
Author(s):  
Guang-Da Liu ◽  
Ge Li ◽  
Gang Shen
Keyword(s):  
Closed Loop ◽  
Transfer Functions ◽  
Servo System ◽  
Proportional Integral Derivative ◽  
Servo Systems ◽  
Closed Loop Systems ◽  
Loop Transfer Function ◽  
Tracking Controllers ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

Closed-loop systems of an electro-hydraulic servo system including position, acceleration, and force closed-loop systems and their closed-loop transfer functions based on parameter model are adaptive identified using a recursive extended least-squares algorithm. The position and force closed-loop tracking controllers are designed by a proportional–integral–derivative controller and are tuned by the position and force step signals. The acceleration closed-loop tracking controller is designed by a three-variable controller and the three states include position, velocity, and acceleration. Experimental results of the estimated position, acceleration, and force closed-loop transfer functions are performed on an actual electro-hydraulic servo system using xPC rapid prototyping technology, which clearly demonstrate the benefit of the adaptive identification method.

A Suboptimal Controller Design Method for the Energy Efficiency of a Load-Sensing Hydraulic Servo System

1991 ◽  
Vol 113 (3) ◽  
pp. 487-493 ◽  
Author(s):  
S. D. Kim ◽  
H. S. Cho
Keyword(s):  
Energy Efficiency ◽  
Controller Design ◽  
Design Method ◽  
Servo System ◽  
Control Performance ◽  
Response Characteristics ◽  
Load Sensing ◽  
Highly Nonlinear ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

The dynamic characteristics of a load-sensing hydraulic servo system are complex and highly nonlinear and, furthermore, the stability is critically deteriorated compared with that of the conventional hydraulic servo systems. Another property of the systems is that the setting value of the pump pressure-compensator considerably affects energy efficiency as well as control performance of the system. These features significantly add complexity to the controller design of the load-sensing systems. To guarantee satisfactory control performance and energy efficiency of the system an effective controller design method, therefore, needs to be developed. This paper considers a suboptimal PID control for the velocity control problem of a loadsensing hydraulic servo system. To show the effectiveness of the controller a series of simulations and experiments were performed. Both results show that the proposed suboptimal controller can produce satisfactory response characteristics and yield an effective trade-off between control performance and energy efficiency of the system.

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