Development of Tracking and Control System Based on Computer Vision for RoboMaster Competition Robot

The main purpose of this paper is to construct an autopilot system for unmanned railcars based on computer vision technology in a fixed luminous environment. Four graphic predefined signs of different colors and shapes serve as motion commands of acceleration, deceleration, reverse and stop for the motion control system of railcars based on image recognition. The predefined signs’ strong classifiers were trained based on Haar-like feature training and AdaBoosting from Open Source Computer Vision Library (OpenCV). Comprehensive system integrations such as hardware, device drives, protocols, an application program in Python and man machine interface have been properly done. The objectives of this research include: (1) Verifying the feasibility of graphic predefined signs serving as commands of a motion control system of railcars with computer vision through experiments; (2) Providing reliable solutions for motion control of unmanned railcars, based on image recognition at affordable cost. The experiment results successfully verify the proposed methodology and integrated system. In the main program, every predefined sign must be detected at least three times in consecutive images within 0.2 s before the system confirms the detection. This digital filter like feature can filter out false detections and make the correct rate of detections close to 100%. After detecting a predefined sign, it was observed that the system could generate new motion commands to drive the railcars within 0.3 s. Therefore, both real time performance and the precision of the system are good. Since the sensing and control devices of the proposed system consist of computer, camera and predefined signs only, both the implementation and maintenance costs are very low. In addition, the proposed system is immune to electromagnetic interference, so it is ideal to merge into popular radio Communication Based Train Control (CBTC) systems in railways to improve the safety of operations.

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Application of Computer Vision and Python Scripts as Educational Mechatronic Platforms for Engineering Development in STEM Technologies

10.20944/preprints202112.0352.v1 ◽

2021 ◽

Author(s):

Vladimir Tudić ◽

Damir Kralj ◽

Josip Hoster ◽

Tomislav Tropčić

Keyword(s):

Applied Sciences ◽

Computer Vision ◽

Control System ◽

Block Diagram ◽

Low Cost ◽

Source Control ◽

Position Resolution ◽

University Of Applied Sciences ◽

Engineer Education ◽

And Control

This paper presents the process of designing, fabrication, assembling, programming and optimizing a prototype of a nonlinear mechatronic Ball-Plate System (BPS) as a laboratory platform for STEM engineer education. Due to the nonlinearity and complexity of BPS, task presents challenging issues, such as: 1) difficulties in controlling the stabilization of a given position point known as steady state error, 2) position resolution known as specific distance error and 3) adverse environmental effects - light shadow error, also discussed in this paper. The laboratory BPS prototype for education was designed, manufactured and installed at the Karlovac University of Applied Sciences at the Department of Mechanical Engineering, Study of mechatronics. The low-cost two degrees BPS system uses a USB HD camera for computer vision as feedback and two DC servomotors as actuators. Due to controlling problems, an advanced block diagram of control system is proposed and discussed. An open-source control system based on Python scripts that allows the use of ready-made functions from the library allows changing the color of the ball and the parameters of the PID controller, thus indirectly simplifying control system and directly the mathematical calculation. The authors will continue their research on this BPS mechatronic platform and control algorithms.

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Development of a Jacobian Module for Advanced Pulp and Paper Simulation and Control

TAPPI Journal ◽

10.32964/tj8.1.4 ◽

2009 ◽

Vol 8 (1) ◽

pp. 4-11

Author(s):

MOHAMED CHBEL ◽

LUC LAPERRIÈRE

Keyword(s):

Control System ◽

Nonlinear Behavior ◽

Simulation Software ◽

Pulp And Paper ◽

Pid Controllers ◽

Tuning Parameters ◽

Pid Tuning ◽

Fixed Set ◽

And Control ◽

Operating Points

Pulp and paper processes frequently present nonlinear behavior, which means that process dynam-ics change with the operating points. These nonlinearities can challenge process control. PID controllers are the most popular controllers because they are simple and robust. However, a fixed set of PID tuning parameters is gen-erally not sufficient to optimize control of the process. Problems related to nonlinearities such as sluggish or oscilla-tory response can arise in different operating regions. Gain scheduling is a potential solution. In processes with mul-tiple control objectives, the control strategy must further evaluate loop interactions to decide on the pairing of manipulated and controlled variables that minimize the effect of such interactions and hence, optimize controller’s performance and stability. Using the CADSIM Plus™ commercial simulation software, we developed a Jacobian sim-ulation module that enables automatic bumps on the manipulated variables to calculate process gains at different operating points. These gains can be used in controller tuning. The module also enables the control system designer to evaluate loop interactions in a multivariable control system by calculating the Relative Gain Array (RGA) matrix, of which the Jacobian is an essential part.

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