scholarly journals Design of high precision mechatronic-hydraulic leveling system for vehicle-mounted radar

2021 ◽  
Vol 2113 (1) ◽  
pp. 012041
Author(s):  
Jun Xiao ◽  
YanChao Wang ◽  
XiangYu Li ◽  
Jie Zheng
Keyword(s):  
Control System ◽  
High Precision ◽  
Control Method ◽  
Good Control ◽  
Vehicle Body ◽  
Control Performance ◽  
Fuzzy Pid Control ◽  
Short Time ◽  
Leveling Control ◽  
The Mathematical Model

Abstract In order to improve the control performance of vehicle-mounted radar, a high precision leveling control system is designed through mechatronic-hydraulic integration technology. A leveling method combining angle error leveling method and height error leveling method is designed, and inclinometers are set in the front and rear of the vehicle body platform to effectively eliminate the virtual outrigger phenomenon in the leveling process. The mathematical model of hydraulic system is developed, the fuzzy PID control method is introduced, and the four-point support hydraulic leveling control system is developed by using STM32 microcontroller as the control core. The field test proves that the control system has good control performance, high leveling accuracy, short time, and meets the control requirements of the radar vehicle.

scholarly journals PMSM Rotor Position Detection Based on Hybrid Optical Encoder and R-Signal Zero-Setting Scheme

2016 ◽  
Vol 2016 ◽  
pp. 1-6
Author(s):  
Yaoqiang Wang ◽  
Xiaoyong Ma ◽  
Mingdong Wang ◽  
Chong Cao
Keyword(s):  
Control System ◽  
High Precision ◽  
Good Control ◽  
Detection Methods ◽  
Control Performance ◽  
Optical Encoder ◽  
Rotor Position ◽  
Position Detection

Rotor position detection is a prerequisite for achieving good control performance of PMSM. For a PMSM control system based on an optical encoder, it is a difficulty to detect rotor position and achieve R-Signal zero-setting. To solve the problem, a hybrid optical encoder is used in the paper by which a scheme for rotor position detection and R-Signal zero-setting is proposed. This encoder can do absolute and incremental rotor position detection simultaneously; here, the former is used for acquiring imprecise rotor position and the latter is for precise rotor position. Firstly, two detection methods of the encoder are analyzed, and a scheme for rotor position detection is proposed: absolute rotor position is used for motor starting before achieving R-Signal zero-setting; once achieving R-Signal zero-setting, incremental rotor position detection that has high precision is adopted. Then a novel scheme for R-Signal zero-setting is emphatically proposed. Finally, the simulation is conducted. Results show that rotor position detection and R-Signal zero-setting can be achieved by the proposed scheme.

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.

Intelligent Information of TS Fuzzy PID Control System of BLDCM

2013 ◽  
Vol 846-847 ◽  
pp. 313-316 ◽  
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Precision ◽  
Simulation Results ◽  
Intelligent Information

This paper presented a new method based on the Fuzzy self - adaptive PID for BLDCM. This method overcomes some defects of the traditional PID control. Such as lower control precision and worse anti - jamming performance. It dynamic model of BLDCM was built, and then design method for TS fuzzy PID model is given, At last, it compared simulation results of PID control method with TS Fuzzy PID control method. The results show that the TS Fuzzy PID control method has more excellent dynamic antistatic performances, as well as anti-jamming performance. The experiment shows that TS fuzzy PID control has the stronger adaptability robustness and transplant.

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.

Robust Control Method Based on Machine Learning for Boiler Combustion System

2014 ◽  
Vol 685 ◽  
pp. 368-372 ◽  
Author(s):  
Hao Zhang ◽  
Ya Jie Zhang ◽  
Yan Gu Zhang
Keyword(s):  
Robust Control ◽  
Intelligent Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Control Method ◽  
Support Vector ◽  
Control Performance ◽  
Fuzzy Pid Control ◽  
On Line ◽  
Control Output

In this study, we presented a boiler combustion robust control method under load changes based on the least squares support vector machine, PID parameters are on-line adjusted and identified by LSSVM, optimum control output is obtained. The simulation result shows control performance of the intelligent control algorithm is superior to traditional control algorithm and fuzzy PID control algorithm, the study provides a new control method for strong non-linear boiler combustion control system.

Development of a Ring Permeability Test System

2010 ◽  
Vol 136 ◽  
pp. 153-157
Author(s):  
Yu Hong Du ◽  
Xiu Ming Jiang ◽  
Xiu Ren Li
Keyword(s):  
Control System ◽  
Control Method ◽  
Dynamic Performance ◽  
Experimental Tests ◽  
Measuring Method ◽  
Test System ◽  
Fluid Theory ◽  
And Control ◽  
Relationship Of ◽  
The Mathematical Model

To solve the problem of detecting the permeability of the textile machinery, a dedicated test system has been developed based on the pressure difference measuring method. The established system has a number of advantages including simple, fast and accurate. The mathematical model of influencing factors for permeability is derived based on fluid theory, and the relationship of these parameters is achieved. Further investigations are directed towards the inherent characteristics of the control system. Based on the established model and measuring features, an information fusion based clustering control system is proposed to implement the measurement. Using this mechanical structure, a PID control system and a cluster control system have been developed. Simulation and experimental tests are carried out to examine the performance of the established system. It is noted that the clustering method has a high dynamic performance and control accuracy. This cluster fusion control method has been successfully utilized in powder metallurgy collar permeability testing.

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.

scholarly journals Decoupling Adaptive Smith Prediction Model of Flatness Closed-Loop Control and Its Application

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 895
Author(s):  
Mingming Song ◽  
Hongmin Liu ◽  
Yanghuan Xu ◽  
Dongcheng Wang ◽  
Yangyang Huang
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Time Delay ◽  
Control Method ◽  
Delay System ◽  
Control Performance ◽  
Time Delay System ◽  
Single Loop ◽  
Flatness Control ◽  
Pure Time Delay

Flatness control system is characterized by multi-parameters, strong coupling, pure time delay, which complicate the establishment of an accurate mathematical model. Therefore, a control scheme that combines dynamic decoupling, PI (Proportion and Integral) control and adaptive Smith predictive compensation is proposed. To this end, a dynamic matrix is used to decouple the control system. A multivariable coupled pure time-delay system is transformed into several independent generalized single-loop pure time-delay systems. Then, a PI-adaptive Smith predictive controller is constructed for the decoupled generalized single-loop pure time-delay system. Simulations show that the scheme has a simple and feasible structure, and good control performance. When the mathematical model of the control system is inaccurate, the control performance of adaptive Smith control method is evidently better than that of the ordinary Smith control method. The model is successfully applied to the cold rolling production site through LabVIEW, and the control accuracy is within 5I. This study reveals a new solution to the problem of coupled pure time-delay in flatness control system.

Modeling and Simulation of Nonlinear Networked Control System Based on Fuzzy Control

2012 ◽  
Vol 426 ◽  
pp. 368-371
Author(s):  
Sheng Li Song ◽  
Y. Chen ◽  
S.J. Huang ◽  
L.H Yang ◽  
R. He
Keyword(s):  
Control System ◽  
Nonlinear Problem ◽  
Control Method ◽  
Fuzzy Controller ◽  
Good Control ◽  
Networked Control System ◽  
Networked Control ◽  
Packet Dropout ◽  
Data Packet Dropout ◽  
Nonlinear Networked Control System

In the nonlinear networked control system (NCS), the conventional control method is difficult to achieve good control performance, due to the nonlinear problem associated with the disturbance factors, such as network induced time delay and data packet dropout. Considering this situation, this paper is aimed to propose a nonlinear networked control system based on T-S fuzzy model, which does not rely on specific network parameters or mathematical model. The nonlinear problem and the uncertainties of network can be both processed by the designed fuzzy controller. Then this approach is applied to nonlinear motor servo system, simulation of the example model is implemented in Matlab/Simulink associated with True Time toolbox. The results show that the proposed method not only is convenient for modeling, but also upgrade the performance of control system.

Sign in / Sign up

Export Citation Format

Share Document