← ALL PROJECTSCONTROL SYSTEMS

Maglev PID Controller

YEAR2024
STATUSCOMPLETE
ROLEControls Engineer — Team of 3
COURSEME 344: Control Systems

// ABSTRACT

For ME 344: Control Systems, my team of three modeled a magnetic levitation system in MATLAB and designed a PID controller implemented in LabVIEW. The controller tracks step, sine, square, and random inputs at frequencies up to 60 Hz and amplitudes of 0.25 cm — the most dynamic performance achieved in the class. The project combined analytical system modeling with iterative experimental tuning.

SKILLS

PID TuningElectromechanical ModelingLabVIEWStability AnalysisExperimental Calibration

TOOLS

MATLABLabVIEWPID ControlSISOtoolSystem ModelingControl Theory
// TECHNICAL WRITEUP

System Description

The Maglev system levitates a ferromagnetic ball beneath an electromagnet. The electromagnet current is modulated to keep the ball at a target height — a classic unstable control problem, since the magnetic force increases as the ball moves closer to the magnet, creating a positive feedback loop that the controller must overcome.

The system responds to user-defined setpoints and perturbations via a LabVIEW front panel.

System Modeling (MATLAB)

Before designing the controller, we modeled the electromechanical dynamics in MATLAB to establish the plant transfer function. Key steps:

  1. Linearization: The magnetic force is nonlinear (proportional to 1/distance²). We linearized around the nominal operating point to obtain a linear time-invariant model
  2. Parameter identification: System constants (electromagnet inductance, ball mass, nominal air gap) were estimated from the hardware specifications and measured experimentally
  3. Stability analysis: Used SISOtool to evaluate open-loop poles and determine the range of gains that provide stable closed-loop behavior

The linearized plant has a right-half-plane pole — confirming the system is inherently unstable and requires active control at all times.

PID Controller Design (LabVIEW)

The controller was implemented in LabVIEW with a user-accessible front panel for real-time gain adjustment and input signal selection.

Design process:

  • Started with proportional control only to establish a baseline
  • Added derivative action to damp oscillations (critical for the unstable plant)
  • Added integral action to eliminate steady-state error for step inputs
  • Iteratively tuned all three gains experimentally against live hardware

The final controller achieves:

  • Step inputs: Settling time < 200 ms, no steady-state error
  • Sine inputs: Tracks accurately up to 60 Hz
  • Square inputs: Sharp response with minimal overshoot
  • Random inputs: Stable tracking across the tested amplitude range

Front Panel Design

The LabVIEW front panel was designed for easy operation during testing and demonstration:

  • Input signal selection (step, sine, square, random)
  • Live amplitude and frequency controls
  • Real-time position and error plots
  • PID gain sliders with live feedback

Results

The controller achieved the widest dynamic range in the class — tracking inputs at frequencies up to 60 Hz and amplitudes up to 0.25 cm. This performance reflected both a well-tuned controller and a front panel that made tuning fast and visible.

The project reinforced a core lesson in control engineering: the model guides your starting point, but experimental tuning on real hardware is where controllers are actually built.