Auto-Tuning Tub-Level Control of Blender in Hydraulic Fracturing

2016 ◽  
Author(s):  
Zheng Chen ◽  
Leslie Cargill ◽  
Brent Naizer
Keyword(s):  
Control System ◽  
Hydraulic Fracturing ◽  
Oil And Gas ◽  
Pi Control ◽  
Automation System ◽  
Control Performance ◽  
Level Control ◽  
Relay Feedback ◽  
System Parameters ◽  
Auto Tuning

Hydraulic fracturing is one of the key technologies for producing shale oil and gas. During hydraulic fracturing, a blender is used to mix sand with water and chemicals to obtain a fluidic mixture that will be pumped down a well to frack rocks. In order to achieve high-quality fracturing during a job, the blender needs to maintain its tub level as well as the density of the fluidic mixture. In this paper, an auto-tuning proportional-integral (PI) control is developed for the blender automation system to maintain the tub level of its fluidic mixture. The control system adopts a single-loop PI with gains that can be auto-tuned during a job. A relay feedback test is conducted for auto-tuning the PI gains online. The auto-tuning PI control has been successfully tested in a blender simulator. Experimental results have shown that the control performance was improved after auto-tuning and that the control system was adaptive to variation in system parameters.

scholarly journals Dynamic Performance Assessment of Primary Frequency Modulation for a Power Control System Based on MATLAB

Processes ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 11 ◽  
Author(s):  
Shizhe Li ◽  
Yinsong Wang
Keyword(s):  
Control System ◽  
Performance Assessment ◽  
Internal Model ◽  
Control Method ◽  
Dynamic Performance ◽  
Dynamic Control ◽  
Pi Control ◽  
Control Performance ◽  
Assessment Index ◽  
Primary Frequency

The primary frequency modulation (PFM) performance of a power control system (PCS) is an important factor affecting the security and stability of a power grid. The traditional control method is proportional integral (PI) control. In order to improve its dynamic control performance, a control method based on the combination of internal model control (IMC) and PI is proposed. Using the method of theoretical assessment and system identification, a simple simulated model of the typical PCS is established. According to the principle of system identification and the least square estimation (LSE) algorithm, the mathematical models of a generator and a built-in model are established. According to the four dynamic performance indexes, the main and auxiliary assessment index of the PCS are defined, and the benchmark and the result of the performance assessment are given. According to three different structures, the PFM dynamic performance of the PCS is analyzed separately. According to the dynamic performance assessment index of PFM, the structure of the control system and the influence of different parameters on the performance of the PCS are analyzed under ideal conditions. The appropriate control structure and controller parameters are determined. Secondly, under the non-ideal condition, the influence of the actual valve flow coefficient on the performance of the control system is studied under two different valve control modes. The simulation results show that the internal model combined with PI has better dynamic control performance and stronger robustness than the traditional PI control, and it also has better application prospects for thermal power plants.

Relay Based PID Auto-tuning Applied to a Multivariable Level Control System

2014 ◽  
Author(s):  
Diogo C. Nunes ◽  
Jan E. M. G. Pinto ◽  
Daniel G. V. Fonseca ◽  
André L. Maitelli ◽  
Fábio M. U. Araújo
Keyword(s):  
Control System ◽  
Level Control ◽  
Level Control System ◽  
Auto Tuning

scholarly journals Interactive Water Level Control System Simulator Based on OMRON CX-Programmer and CX-Designer

2021 ◽  
Vol 11 (9) ◽  
pp. 91-99
Author(s):  
Rijalul Fahmi Mustapa ◽  
◽  
Rozi Rifin ◽  
Mohd Ezwan Mahadan ◽  
Aznilinda Zainuddin
Keyword(s):  
Control System ◽  
Embedded System ◽  
Water Level ◽  
Teaching And Learning ◽  
Programmable Logic Controller ◽  
Automation System ◽  
Programmable Logic ◽  
Level Control ◽  
Level Control System ◽  
Automation Systems

Abstract— Programmable Logic Controller (PLC) is an essential component in industrial automation where it acts as the backbone of the system. In line with Industrial Revolution (IR) 4.0, most industrial and manufacturing sectors move towards automation systems. Preparing university students about automation and PLC fundamental knowledge and skill is crucial before graduation, where the preoccupied knowledge will enhance graduate employability. Fulfilling this task, universities have to prepare the necessary equipment in the laboratory for teaching and learning purposes. The problem arises when certain universities with budget constraints cannot purchase the equipment for the PLC embedded system as huge costs have to be borne by universities. Thus, an alternative approach has to be taken where the main objective of this paper is to develop an interactive water level control system simulator as a substitution of the expensive automation PLC embedded system for teaching and learning purposes. OMRON software, namely CX-Programmer and CX-Designer used to design and develop an interactive water level control system simulator. In addition, the interactive water level control will be embedded with a PLC component that replicates the actual automation system laboratory equipment. Moreover, universities with a limited budget can utilize the tool for teaching and learning purposes of the PLC and automation system, which is the main contribution of this paper. Keywords—Water Level Control System, Programmable Logic Controller, Simulator, CX-Programmer, CX-Designer.

Parameter Optimization for AP1000 Steam Generator Feedwater Control System Using Particle Swarm Optimization Algorithm

2016 ◽  
Author(s):  
Shifa Wu ◽  
Pengfei Wang ◽  
Jiashuang Wan ◽  
Xinyu Wei ◽  
Fuyu Zhao
Keyword(s):  
Particle Swarm Optimization ◽  
Control System ◽  
Water Level ◽  
Steam Generator ◽  
Parameter Optimization ◽  
Particle Swarm ◽  
Operating Conditions ◽  
Control Performance ◽  
Level Control ◽  
Swarm Optimization

The U-tube Steam Generator (UTSG) of AP1000 Nuclear Power Plant (NPP) is the crucial component transferring heat from the primary loop to the secondary loop to make steam. The UTSG of AP1000 NPP is a highly complex, nonlinear and time-varying system and its parameters vary with operating conditions. Therefore, it is difficult and challenging to well control the water level of AP1000 UTSG by tuning the PID controller parameter in a traditional way, especially when the system is undergoing a sharp transient. To achieve better control performance, the Particle Swarm Optimization (PSO) algorithm was applied for the parameter optimization of the AP1000 UTSG feedwater control system in this study. First, the mathematical model of AP1000 UTSG was established and the objective function was developed with the system constraints considered. Second, the simulation platform was built and then the simulation was conducted in MATLAB/Simulink environment. Finally, the optimized parameters were obtained and the feedwater control system with optimized parameters was simulated against that without optimized. The simulation results demonstrate that optimized parameters of AP1000 UTSG feedwater control system can significantly improve the water level control performance with smaller overshoot and faster response. Therefore, the PSO based optimization method can be applied to optimizing AP1000 UTSG feedwater control system parameters to provide much better control capabilities.

scholarly journals PID Controller Design Based on Radial Basis Function Neural Networks for the Steam Generator Level Control

2016 ◽  
Vol 16 (5) ◽  
pp. 15-26 ◽  
Author(s):  
Kong Xiangsong ◽  
Chen Xurui ◽  
Guan Jiansheng
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Radial Basis Function ◽  
Steam Generator ◽  
Pid Control ◽  
Basis Function ◽  
Pid Controller ◽  
Rbf Neural Networks ◽  
Control Performance ◽  
Level Control

Abstract Steam generator level control system is a vital control system for the Pressurized Water Reactor (PWR). However, the steam generator level process is a highly nonlinear and non-minimum phase system, the conventional Proportional- Integral-Derivative (PID) control scheme with fixed parameters was difficult to obtain satisfactory control performance. The Radial Basis Function (RBF) Neural Networks based PID control strategy (RBFNN-PID) is proposed for the steam generator level control. This method can identify the mathematical model of the steam generator via the RBF neural networks, and then the PID parameters can be optimized automatically to accommodate the characteristic variation of the process. The optimal number of the hidden layer neurons is also discussed in this paper. The simulation results shows that the PID controller designed based on the RBF neural networks has good control performance on the steam generator level control.

scholarly journals An Auto-Tuning PI Control System for an Open-Circuit Low-Speed Wind Tunnel Designed for Greenhouse Technology

Sensors ◽  
2015 ◽  
Vol 15 (8) ◽  
pp. 19723-19749 ◽  
Author(s):  
Karlos Espinoza ◽  
Diego Valera ◽  
José Torres ◽  
Alejandro López ◽  
Francisco Molina-Aiz
Keyword(s):  
Control System ◽  
Wind Tunnel ◽  
Open Circuit ◽  
Pi Control ◽  
Low Speed ◽  
Auto Tuning ◽  
Low Speed Wind Tunnel
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