Ball Balancing Table: Innovative Ball Plate System

OVERVIEW

Ball Balancing Table, with its easily accessible and user-friendly components, is a hands-on experiment, closing the gap between real industrial systems and DIY-approach. Students can understand the effects of different controller types on the system and easily cover controller design concepts with control system experiments. The ready-to-use courseware and a wide range of software options give the maximum flexibility to learn the essential aspects of control theory by experimenting. The system is also suitable for graduate studies for designing advanced controller types such as robust control, adaptive control, and so on. Open-source software makes it possible that students and researchers can modify and test their own developed algorithms.

SOFTWARE OPTIONS

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LabVIEW, Real-Time (optional), FPGA (optional)

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Altair Activate

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Executable & GUI

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Python

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LabVIEW, Real-Time, FPGA (optional)



Python and OpenCV



API for External Control (Examples for LV, Matlab, Python)

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MatLab/Simulink

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C with STM32 software

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API for External Control (Examples for LV, Matlab, Python)

* Different controllers may require

CONTROLLER OPTIONS

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USB (PC based)

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Raspberry Pi + Shield

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NI myRIO

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Arduino Mega + Shield

SPECIFICATIONS

Payload

12 kgs (26,5 lbs)

Up to 150 kgs (331 lbs)

Workspace Options

X and Y Axis +/-60 mm
Z Axis +/-50 mm
Roll, Pitch, Yaw +/- 20°

Up to +/-300 mm
Up to +/-150 mm
Up to +/- 45°

Position Repeatability

+/- 100 µm

Down to +/- 25 µm

Angular Sensitivity

0.2°

Down to 0.1°

Max. Linear Speed

40 mm/sec.

Up to 80 mm/sec.

Height (min-max)

406-506 mm

330-920 mm

Platform Diameter

350 mm (hexagonal)

250-1000+ mm

Base Diameter

450 mm (hexagonal)

450-1000+ mm

Weight

14 kgs (31 lbs)

Based on custom options

SPECIFICATIONS

Payload

260 gr.

Workspace

± 7° in Pitch & Roll

Position Repeatability

± 1mm.

Angular Sensitivity

0.36°

Max. Speed

90 °/second

Height (min-max)

130mm. - 150mm. (± 2mm.)

Height

Rod Height

Platform Dimensions (Length * Width)

375mm. * 310mm. (± 2mm.)

Base Dimensions (Length * Width)

410mm. x 350mm. (± 2mm.)

Weight

4,400 gr.

Propeller Wingspan

Ball Diameter

40mm. (± 1mm.)

Magnet Diameter

Rod's Diameter

Motor Type

RC Servomotors with Built-In Encoder

Feedback Sensors

Resistive Touch Sensor (1200px * 800px)

Power Requirement

12 V - 5 A

FEATURES

Assembled and ready to control plant with the integrated power unit

Getting Started Program with rich Graphical User Interface for out-of-the-box user experience

Implementation of advanced digital control techniques

Fully compatible with MATLAB®/Simulink®, LabVIEW™ and Altair Activate®

Fully documented system models and parameters provided for MATLAB®/Simulink®, LabVIEW™, Altair Activate®

Ball position feedback using a high precision touch surface (camera-based feedback optional) Actuating the table by RC servo motors, which are familiar to students

Rectangular and circular path options are integrated into the software

Enables students to create their own real-time algorithms. Open architecture with extensive courseware, suitable for undergraduate courses for engineering disciplines related to control systems

Digital twin available in Altair software.

FAQs

What is Ball Balancing Table?



The Ball Balancing Table system is an automatic control system, used for teaching control systems and various control algorithms.

What is a Ball Balancing Table used for?



The Ball Balancing Table is used for trying different algorithms to control the ball's position in 2 different horizontal directions, in a safe and repeatable manner.

What is the feedback sensor type?



An analogue touch sensor is used to determine the position of the ball. The servo motor has also an optional potentiometer to measure the position of the servo motor's arm. Product can also optionally provided with an Inertial Measurement (IMU) sensor to measure the tilt angles of the moving plate.

Is there a non-academic version for other usage purposes?



Yes there is a maker version based on Python software. Custom software options also exists for different test scenarios.

Does the product comes with a controller and software/courseware?



Product comes with the controller, software and a companion courseware with example source codes.

Is there any after-sales support or training for the product?



A complimentary online support session is available after the delivery of the products. Standard support is provided via the phone, e-mail or remote desktop connection.

CURRICULUM

Components of Ball Balancing Table

RC Servo Motors
Touch Sensor Controller
Acrome Power Distribution BoxMechanics of the System

FUNDAMENTALS OF PWM

PWM Signaling Theory
Generating PWM Signals Driving
RC Servos with PWM Signals

SYSTEM MODELING

Lagrangian Method
Newton’s Law of Motion
Modeling of Actuator
Obtaining Transfer Function

FEEDBACK IN CONTROL SYSTEMS

Reading Ball Position from Touch Sensor
Derivative Filtering

PERFORMANCE MEASURES

Time Domain Characteristics
Steady State Response and Steady State Error

CONTROL SYSTEM DESIGN

Design of Linear Controllers
PID controller and Fuzzy Logic Controller
Comparing the Simulation and Real System Responses for Different Controllers

CONTROL SYSTEM VERIFICATION

Frequency response analysis
Experimental Bode Diagram
Cut-Off Frequency Determination

Ball Balancing Table Maze Solver - Reinforcement Learning

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Min

In this project, we investigate the application of PID control and Q-learning algorithms to the Ball Balancing Table (BBT) in order to solve a maze. An open-source tool called the BBT makes it possible to experiment with control systems directly. The device can guide a ball through a maze by adjusting the tilt of the table, imparting important knowledge about reinforcement learning, control theory, and feedback systems. The table's orientation is adjusted by using a PID controller in response to real-time feedback from the ball's position. A matrix of 0s and 1s with open paths and walls, respectively, is used to depict the maze. The system associates movements with the Q-learning reinforcement learning algorithm to learn how to move the ball through the maze.

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Ball Balancing Table

REFERENCE CUSTOMERS

OVERVIEW

SMD PRODUCTS

SMD - RED

SMD - Starter Kit

SMD - Education Kit

SOFTWARE OPTIONS

CONTROLLER OPTIONS

APPLICATION AREAS

PRODUCT PHOTOS

SPECIFICATIONS

SPECIFICATIONS

FEATURES

FAQs

CURRICULUM

Ball Balancing Table Maze Solver - Reinforcement Learning

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