Active Vibration Control of a Cantilever Beam with Piezoelectric Materials

This project contains the entire source code for my Master Thesis for the a Masters in Mechanical Engineering, with specialization in Mechatronics in ITBA.

The objective of the project is to stop induced vibrations on a cantilever beam by acting on it with piezoelectric actuators. The system has the following components:

• The physical beam to be controlled.
• The piezoelectric actuators attached to the beam.
• An accelerometer attached to the beam to measure its vibrations.
• An Arduino interfacing between the actuators, the accelerometer, and a Desktop computer implementing the control strategy.
• A software FEM model of the beam, the piezoelectric actuators, and the accelerometer.
• A software implementation of Kalman filters to correct the accelerometer's input.
• A software Control module that implements the PID control strategy.

Contents

Arduino Drivers

• Accelerometer.cpp: driver to read from accelerometer. API:
  • int take_sample(int average_points, Coord coord) samples the accelerometer's output.
  • double read_g(int average_points, int coord_num) samples the accelerometer's output and transforms it into physical units (m/s^2)
• Piezo.cpp: a C++ driver to manage piezoelectric actuator. API:
  • void apply_voltage(float V) starts applying a voltage to the actuator. Apply 0 to stop it.
  • void actuate_square(float amp, float f) applies a voltage of amplitude amp with a frequency of f (measured in Hz)
  • void actuate_sin(float amp, float f) applies a sine way with maximum amplitude of amp with a frequency of f (measured in Hz). It approximates the sine function with the build it sin.

Simulation & Control

• Run.m: MATALAB class that serves as the main entry point of the application, initializing the FEM model, the Arduino interface, and the Controller
• Controller.m: MATLAB class to control the beam based on the accelerometer's readings and the piezoelectric's possible outputs. It uses a Kalman filter to improve the readings, a PID controller as its main control strategy, and a FEM model as a representation of the system to control
• DSP.m: MATLAB class to implement the Kalman filter and other Digital Signal Processing techniques (FFT for the prior analysis)
• Arduino.m: MATALAB class to interface with the Arduino controller