Simulation Design of Cyclic Code Error Control System Based on Simulink

2018 ◽  
Author(s):  
Ma Xiao-Qing
Keyword(s):  
Control System ◽  
Error Control ◽  
Cyclic Code ◽  
Simulation Design

Design and Integrated Simulation of the Electro-Hydraulic Servo System Based on AMESim and Matlab

2010 ◽  
Vol 44-47 ◽  
pp. 1355-1359 ◽  
Author(s):  
Xiang Xu ◽  
Zhi Xiong Li ◽  
Hong Ling Qin
Keyword(s):  
Control System ◽  
Design Method ◽  
Design Procedure ◽  
Servo System ◽  
Hydraulic Cylinder ◽  
Fast Response ◽  
Simulation Design ◽  
Integrated Simulation ◽  
Hydraulic Servo ◽  
Hydraulic Servo System

Since electro-hydraulic servo system has fast response and highest control accuracy, it has been widely used in industrial application, including aircraft, mining, manufacturing, and agriculture, etc. With the fast development of computer science, it is feasible and available to evaluate the performance of the designed control system via virtual simulation before the practical usage of the system. In order to optimize the design procedure of the electro-hydraulic proportional controller, the co-simulation design method based on AMESim-Matlab is presented for the electro-hydraulic servo system in this paper. High accuracy of the mathematical model of electro-hydraulic servo system was full-fitted by the use of AMESim, and the advantage of high solving precision for large amount of calculation was full played using Matlab. The PID controller was employed to realize the efficient control of the motion of the hydraulic cylinder. The united simulation technique was adopted to verify the good performance of the designed control system. The simulation results suggest that the proposed method is effective for the design of electro-hydraulic servo systems and thus has application importance.

Linear Quadratic Regulator Method in Vision-Based Laser Beam Tracking for a Mobile Target Robot

Robotica ◽  
2020 ◽  
pp. 1-11
Author(s):  
Yun Ling ◽  
Jian Wu ◽  
Weiping Zhou ◽  
Yubiao Wang ◽  
Changcheng Wu
Keyword(s):  
Control System ◽  
Laser Beam ◽  
Tracking Control ◽  
Error Control ◽  
Linear Quadratic Regulator ◽  
Lyapunov Theory ◽  
State Function ◽  
Linear Quadratic ◽  
Mobile Target ◽  
Beam Tracking

SUMMARY This paper proposes a novel laser beam tracking mechanism for a mobile target robot that is used in shooting ranges. Compared with other traditional tracking mechanisms and modules, the proposed laser beam tracking mechanism is more flexible and low cost in use. The mechanical design and the working principle of the tracking module are illustrated, and the complete control system of the mobile target robot is introduced in detail. The tracking control includes two main steps: localizing the mobile target robot with regards to the position of the laser beam and tracking the laser beam by the linear quadratic regulator (LQR). First of all, the state function of the control system is built for this tracking system; second, the control law is deduced according to the discretized state function; lastly, the stability of the control method is proved by the Lyapunov theory. The experimental results demonstrate that the Hue, Saturation, Value feature-extracting method is robust and is qualified to be used for localization in the laser beam tracking control. It is verified through experiments that the LQR method is of better performance than the conventional Proportional Derivative control in the aspect of converge time, lateral error control, and distance error control.

An error control system with multiple-stage forward error corrections

1990 ◽  
Vol 38 (10) ◽  
pp. 1799-1809 ◽  
Author(s):  
T. Takata ◽  
T. Fujiwara ◽  
T. Kasami ◽  
S. Lin
Keyword(s):  
Control System ◽  
Error Control ◽  
Error Corrections ◽  
Forward Error ◽  
Forward Error Corrections

scholarly journals Simulation design of trajectory planning robot manipulator

2019 ◽  
Vol 8 (1) ◽  
pp. 196-205 ◽  
Author(s):  
Wahyu S. Pambudi ◽  
Enggar Alfianto ◽  
Andy Rachman ◽  
Dian Puspita Hapsari
Keyword(s):  
Neural Network ◽  
Control System ◽  
Robot Manipulator ◽  
Optimal Path ◽  
Average Error ◽  
Target Point ◽  
Simulation Design ◽  
Self Organizing Maps ◽  
Network Process ◽  
Fuzzy Pd

Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.

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