Draft:Ball and Plate System
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Comment: In preparing this draft, I disclose that AI assistance was used as follows: I used google gemini to know how to add refrence Maheshsuthar18 (talk) 18:44, 30 October 2026 (UTC)
== Introduction ==
The Ball and Plate System is a known closed-loop feedback control system and robotics platform. It is widely used to study dynamic system stabilization real-time computer vision and multi-axis kinematic trajectory tracking. The system has a plate that can tilt. This plate is mounted above a fixed base. A small ball moves freely on the plate. An optical sensor tracks the ball’s position. Mechanical actuators adjust the tilt of the plate in time. By measuring how far the ball is from the center of the plate the control system computes the needed tilt angle. This helps stabilize the ball at a target point (X, Y) or guide it along a planned path in space.
Hardware Architecture
[edit]A modern high-speed implementation relies on three main subsystems: vision tracking, processing and actuation, and physical linkage designed via Computer-Aided Design(CAD).
Computing and Sensing
[edit]The hardware setup consists of three parts: vision tracking, processing and actuation and physical linkages built using Computer-Aided Design. The system runs on a Raspberry Pi 5 single-board computer with 8GB of RAM. This processor powers the control loops and real-time vision algorithms. It uses a quad-core CPU. Connects directly to the camera through a MIPI CSI-2 interface. That connection gives bandwidth and fast data transfer.
For tracking a Raspberry Pi Camera Module 3 Wide is mounted above the plate on an arm. [1]This camera captures video at frame rates. The wide-angle lens allows for a compact frame design. Phase Detection Autofocus or PDAF reduces the delay in capturing the ball’s position. This makes tracking more responsive. The system uses the camera to detect the ball’s location in time.
Computing and Sensing
[edit]The physical part of the system includes three torque MG996R metal-gear servo motors. These motors are arranged in a 3-DOF linkage setup around a central pivot. This allows the plate to tilt in pitch, roll and height. The servo motors are controlled by pulse width modulation signals. These signals are sent through a PCA9685 16-channel PWM driver. The driver communicates with the Raspberry Pi using the I²C bus. This setup keeps the processor free from handling pulse generation tasks.
The control strategy involves a vision processing pipeline. First the camera sends video frames through the libcamera or Picamera2 drivers. OpenCV then processes these frames to find the ball. It uses color segmentation in the HSV color space or contour detection to locate the ball. The ball’s pixel coordinates are converted into world displacement values. These values show how far the ball is from the center of the plate in the x and y directions.
Actuation and Power
[edit]Power is supplied by a dedicated regulated DC power source. It provides voltage and current directly to the PCA9685 driver board. This prevents voltage drops during motor adjustments. The mechanical structure is designed in CAD. The base, motor mounts, linkage arms, camera frame and the upper plate are all modeled together. The three-point linkage gives control over the plate’s orientation.
Structural Mechanics
[edit]CAD Design: The base structure, motor mounts, linkage arms, overhead camera frame, and upper platform are designed as a CAD assembly. The three-point mechanical linkage allows dynamic control over pitch,roll and height.
Control Loop
[edit]A control loop uses axis Proportional-Integral-Derivative (PID) control[2]. The PID controller calculates the required tilt angle using the error signal. The formula is:
Inverse Kinematics Mapping
[edit]This equation adjusts the tilt based on how the ball is from the target how long it has been off and how fast it is moving. The target tilt angles (α,β) are then converted into individual servo horn angles (θ₁, θ₂, θ₃) using inverse kinematics. These equations are derived from the model of the 3-DOF parallel linkage
Applications
[edit]The Ball and Plate System has applications. In education it helps teach control theory concepts. It demonstrates control systems (MIMO) state estimation and sensor filtering like Kalman filters. In industry it serves as a testbed for balance algorithms. These algorithms are used in marine stabilization systems, rocket engine thrust vectoring and active suspension systems.
References
[edit]1. ^Spong, M. W., Hutchinson, S., & Vidyasagar, M. (2005). *Robot. Control*. Wiley.
2. ^Åström K. J.,. Murray, R. M. (2021). *Feedback Systems: An Introduction, for Scientists and Engineers*. Princeton University Press.
3. ^Raspberry Pi Foundation. (2023). *Raspberry Pi Camera Module 3 Documentation*.
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