scholarly journals Active Microvibration Control System Using Both Air Springs and Magnetic Bearings. 1st Report. Control Performance with Absolute Velocity Feedback.

1994 ◽  
Vol 60 (575) ◽  
pp. 2227-2232
Author(s):  
Weimin Cui ◽  
Yoichi Kanemitsu ◽  
Kenzo Nonami ◽  
Katsuhide Watanabe
Keyword(s):  
Control System ◽  
Magnetic Bearings ◽  
Absolute Velocity ◽  
Control Performance ◽  
Velocity Feedback

scholarly journals Electromagnetic Actuator System Using Witty Control System

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 65
Author(s):  
Der-Fa Chen ◽  
Shen-Pao-Chi Chiu ◽  
An-Bang Cheng ◽  
Jung-Chu Ting
Keyword(s):  
Control System ◽  
Control Method ◽  
Search Algorithm ◽  
Electromagnetic Actuator ◽  
Control Performance ◽  
Learning Capability ◽  
Learning Rates ◽  
Agricultural Applications ◽  
Actuator System ◽  
Rice Milling

Electromagnetic actuator systems composed of an induction servo motor (ISM) drive system and a rice milling machine system have widely been used in agricultural applications. In order to achieve a finer control performance, a witty control system using a revised recurrent Jacobi polynomial neural network (RRJPNN) control and two remunerated controls with an altered bat search algorithm (ABSA) method is proposed to control electromagnetic actuator systems. The witty control system with finer learning capability can fulfill the RRJPNN control, which involves an attunement law, two remunerated controls, which have two evaluation laws, and a dominator control. Based on the Lyapunov stability principle, the attunement law in the RRJPNN control and two evaluation laws in the two remunerated controls are derived. Moreover, the ABSA method can acquire the adjustable learning rates to quicken convergence of weights. Finally, the proposed control method exhibits a finer control performance that is confirmed by experimental results.

Application of PID in Controllable Pitch Propeller of a Multipurpose Ocean Tug

2013 ◽  
Vol 464 ◽  
pp. 253-257
Author(s):  
Hui Fang Chen
Keyword(s):  
Control System ◽  
Automatic Control ◽  
Automatic Control System ◽  
High Reliability ◽  
Control Process ◽  
Good Control ◽  
Control Performance ◽  
Hardware Configuration ◽  
Design Idea ◽  
And Control

This paper takes the automatic control system of controllable pitch propeller in a multipurpose ocean tug as an example to describe the application of the S7-200 series PLC in the control system of 4500 horse power controllable pitch propeller in detail. The principle of control system is addressed, as well as the hardware configuration, the design idea of the main software and control process. The system shows high reliability, accuracy and good control performance in practical in practical running.

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.

Combination of Neural Networks and State Vector Feedback Adaptive Control (SVFAC) Technique to Control the Gas Turbine Combustor

2006 ◽  
Author(s):  
Mahmood Lahroodi ◽  
A. A. Mozafari
Keyword(s):  
Neural Networks ◽  
Adaptive Control ◽  
Control System ◽  
Gas Turbine ◽  
Control Method ◽  
Control Performance ◽  
Gas Turbine Combustor ◽  
Model Network ◽  
Neural Network Controller ◽  
Nonlinear Plants

Neural networks have been applied very successfully in the identification and control of dynamic systems. When designing a control system to ensure the safe and automatic operation of the gas turbine combustor, it is necessary to be able to predict temperature and pressure levels and outlet flow rate throughout the gas turbine combustor to use them for selection of control parameters. This paper describes a nonlinear SVFAC controller scheme for gas turbine combustor. In order to achieve the satisfied control performance, we have to consider the affection of nonlinear factors contained in controller. The neural network controller learns to produce the input selected by the optimization process. The controller is adaptively trained to force the plant output to track a reference output. Proposed Adaptive control system configuration uses two neural networks: a controller network and a model network. The model network is used to predict the effect of controller changes on plant output, which allows the updating of controller parameters. This paper presents the new adaptive SFVC controller using neural networks with compensation for nonlinear plants. The control performance of designed controller is compared with inverse control method and results have shown that the proposed method has good performance for nonlinear plants such as gas turbine combustor.

Scheduling Strategy of Multiple Semi-Active Controllers With Information on the Disturbance and the Structural Response

2016 ◽  
Author(s):  
Kazuhiko Hiramoto ◽  
Taichi Matsuoka ◽  
Katsuaki Sunakoda
Keyword(s):  
Optimal Control ◽  
Control System ◽  
Active Control ◽  
Structural Response ◽  
Design Parameters ◽  
Control Law ◽  
Control Performance ◽  
Multiple Control ◽  
Control Laws ◽  
Scheduling Strategy

A scheduling strategy of multiple semi-active control laws for various earthquake disturbances is proposed to maximize the control performance. Generally, the semi-active controller for a given structural system is designed as a single control law and the single control law is used for all the forthcoming earthquake disturbances. It means that the general semi-active control should be designed to achieve a certain degree of the control performance for all the assumed disturbances with various time and/or frequency characteristics. Such requirement on the performance robustness becomes a constraint to obtain the optimal control performance. We propose a scheduling strategy of multiple semi-active control laws. Each semi-active control law is designed to achieve the optimal performance for a single earthquake disturbance. Such optimal control laws are scheduled with the available data in the control system. As the scheduling mechanism of the multiple control laws, a command signal generator (CSG) is defined in the control system. An artificial neural network (ANN) is adopted as the CSG. The ANN-based CSG works as an interpolator of the multiple control laws. Design parameters in the CSG are optimized with the genetic algorithm (GA). Simulation study shows the effectiveness of the approach.

scholarly journals Output Feedback NCS of DoS Attacks Triggered by Double-Ended Events

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xinzhi Feng ◽  
Yang Yang ◽  
Xiaozhong Qi ◽  
Chunming Xu ◽  
Ze Ji
Keyword(s):  
Control System ◽  
Denial Of Service ◽  
Network Control ◽  
Control Performance ◽  
Network Control System ◽  
Dos Attack ◽  
Dos Attacks ◽  
Network Attacks ◽  
Elastic Event ◽  
Event Triggering

In recent years, the research of the network control system under the event triggering mechanism subjected to network attacks has attracted foreign and domestic scholars’ wide attention. Among all kinds of network attacks, denial-of-service (DoS) attack is considered the most likely to impact the performance of NCS significantly. The existing results on event triggering do not assess the occurrence of DoS attacks and controller changes, which will reduce the control performance of the addressed system. Aiming at the network control system attacked by DoS, this paper combines double-ended elastic event trigger control, DoS attack, and quantitative feedback control to study the stability of NCS with quantitative feedback of DoS attack triggered by a double-ended elastic event. Simulation examples show that this method can meet the requirements of control performance and counteract the known periodic DoS attacks, which save limited resources and improve the system’s antijamming ability.

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