scholarly journals Fault Identification for a Closed-Loop Control System Based on an Improved Deep Neural Network

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2131 ◽  
Author(s):  
Bowen Sun ◽  
Jiongqi Wang ◽  
Zhangming He ◽  
Haiyin Zhou ◽  
Fengshou Gu
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Systems ◽  
Deep Neural Network ◽  
Closed Loop ◽  
Fault Identification ◽  
Closed Loop Control ◽  
Loop Control ◽  
Identification Methods ◽  
Loop Control System

Fault identification for closed-loop control systems is a future trend in the field of fault diagnosis. Due to the inherent feedback adjustment mechanism, a closed-loop control system is generally very robust to external disturbances and internal noises. Closed-loop control systems often encourage faults to propagate inside the systems, which may lead to the consequence that faults amplitude becomes smaller and fault characteristics difference becomes more inapparent. Hence, it has been challenging to achieve fault identification for such systems. Traditional fault identification methods are not particularly designed for closed-loop control systems and thus cannot be applied directly. In this work, a new fault identification method is proposed, which is based on the deep neural network for closed-loop control systems. Firstly, the fault propagation mechanism in closed-loop control systems is theoretically derived, and the influence of fault propagation on system variables is analyzed. Then deep neural network is applied to find fault characteristics difference between different data modes, and a sliding window is used to amplify the fault-to-noise ratio and characteristics difference, with an aim to increase the identification performance. To verify this method, the simulations that are based on a numerical simulation model, the Tennessee industrial system and the satellite attitude control system are conducted. The results show that the proposed method is more feasible and more effective in fault identification for closed-loop control systems compared with traditional data-driven identification methods, including distance-based and angle-based identification methods.

scholarly journals Robust Control System Design for Small UAV Using H2-Optimization

2018 ◽  
Vol 23 (2) ◽  
pp. 151-159
Author(s):  
Róbert Szabolcsi
Keyword(s):  
Control System ◽  
Control Systems ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Worst Case ◽  
Loop Control ◽  
Closed Loop Control System ◽  
Wide Range ◽  
Loop Control System ◽  
Dynamic Performances

Abstract Unmanned aerial vehicles are famous for their wide range of applications. In D3 (Dirty-Dull-Dangerous) UAV applications flight conditions may vary on large scale. External disturbances like atmospheric turbulences and gusts may be subjected to UAV, and as a result, UAV flight mission might be conducted with high level of the degradation of the accuracy. Sensor noises are also present, and theirs negligence might lead to improper dynamic performances of the closed loop control systems. Uncertainties of the control systems being structured or unstructured may tend the closed loop control system to stability bounds. In worst case, uncertainties may destabilize closed loop control systems. The purpose of the author is to present a robust controller design method called H2-optimal design ensuring stability of the closed loop control systems with simultaneous dynamic performances predefined for the closed loop control system.

scholarly journals Closed-loop control system for well-defined oxygen supply in micro-physiological systems

2017 ◽  
Vol 3 (2) ◽  
pp. 363-366
Author(s):  
Tobias Steege ◽  
Mathias Busek ◽  
Stefan Grünzner ◽  
Andrés Fabían Lasagni ◽  
Frank Sonntag
Keyword(s):  
Control System ◽  
Oxygen Supply ◽  
Closed Loop ◽  
Microfluidic System ◽  
Closed Loop Control ◽  
Loop Control ◽  
Cell Vitality ◽  
Closed Loop Control System ◽  
Loop Control System

AbstractTo improve cell vitality, sufficient oxygen supply is an important factor. A deficiency in oxygen is called Hypoxia and can influence for example tumor growth or inflammatory processes. Hypoxia assays are usually performed with the help of animal or static human cell culture models. The main disadvantage of these methods is that the results are hardly transferable to the human physiology. Microfluidic 3D cell cultivation systems for perfused hypoxia assays may overcome this issue since they can mimic the in-vivo situation in the human body much better. Such a Hypoxia-on-a-Chip system was recently developed. The chip system consists of several individually laser-structured layers which are bonded using a hot press or chemical treatment. Oxygen sensing spots are integrated into the system which can be monitored continuously with an optical sensor by means of fluorescence lifetime detection.Hereby presented is the developed hard- and software requiered to control the oxygen content within this microfluidic system. This system forms a closed-loop control system which is parameterized and evaluated.

Adaptive synchronization of uncertain fractional-order chaotic systems using sliding mode control techniques

2019 ◽  
Vol 234 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Bahram Yaghooti ◽  
Ali Siahi Shadbad ◽  
Kaveh Safavi ◽  
Hassan Salarieh
Keyword(s):  
Control System ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Chaotic Systems ◽  
Closed Loop ◽  
Sliding Mode ◽  
Closed Loop Control ◽  
Loop Control ◽  
Closed Loop Control System ◽  
Loop Control System

In this article, an adaptive nonlinear controller is designed to synchronize two uncertain fractional-order chaotic systems using fractional-order sliding mode control. The controller structure and adaptation laws are chosen such that asymptotic stability of the closed-loop control system is guaranteed. The adaptation laws are being calculated from a proper sliding surface using the Lyapunov stability theory. This method guarantees the closed-loop control system robustness against the system uncertainties and external disturbances. Eventually, the presented method is used to synchronize two fractional-order gyro and Duffing systems, and the numerical simulation results demonstrate the effectiveness of this method.

Tangible Programming for Basic Control System New Frameworks to Engineering Education for Children

2014 ◽  
Vol 931-932 ◽  
pp. 1298-1302
Author(s):  
Thiang Meadthaisong ◽  
Siwaporn Meadthaisong ◽  
Sarawut Chaowaskoo
Keyword(s):  
Control System ◽  
Engineering Education ◽  
Control Systems ◽  
Primary Schools ◽  
Closed Loop ◽  
Open Loop ◽  
Closed Loop Control ◽  
College Level ◽  
Loop Control ◽  
Tangible Programming

Programming control in industrial design is by its nature expert upon an example being Programmable Logic Controller (PLC). Such programmes are unsuitable for children or novices as they cannot understand how to use the programme. This research seeks to present tangible programming for a basic control system in new frameworks in engineering education for children. Such programmes could be for use in kindergartens, primary schools or general teaching where knowledge about basic control is required. Normally open-loop and closed-loop control system programming is taught at university and college level. This may be late as far as acquiring knowledge of basic control systems is concerned. Using tangible programming without a computer but instructions and interface, relay and motor could result in children in kindergartens and primary schools being able to programme open-looped control systems which mix chemicals or closed-loop control systems which control conveyor belts. However, the children would not be able to undertake programming using programmable control in a similar scenario.

Sign in / Sign up

Export Citation Format

Share Document