Self-Balancing Robot with a PID Controller: FYP Build Guide.

The two-wheeled self balancing robot using pid controller is a classic, universally respected capstone project for Mechatronics, Electrical, and Control Systems engineers looking for standout final year project ideas in Pakistan to build a demonstrable fyp prototype. Modeling an inverted pendulum tests a team's mastery of dynamic differential equations, digital sensor signal filtering, high-speed PWM motor control, and rigid mechanical chassis fabrication.

1. Inverted Pendulum System Architecture

The self-balancing robot maintains upright stability by driving its wheels in the direction that the upper chassis is falling. The hardware pipeline consists of four interconnected subsystems:

• IMU Angle Sensing: An MPU-6050 sensor mounted near the center of gravity measuring angular rate and gravitational acceleration vectors.
• Sensor Fusion Filter: Combining low-pass filtered accelerometer angles with integrated gyroscope angular rates using a complementary filter to obtain drift-free pitch angles.
• Microcontroller PID Processing: Executing a high-frequency (200Hz) timer interrupt loop calculating required motor compensation torque based on proportional, integral, and derivative terms.
• Motor Driver & Actuators: Dual H-bridge driver (TB6612FNG or L298N) modulating 12V geared motors equipped with quadrature encoders.

2. Practical PID Tuning Procedure

Tuning the PID controller requires a methodical, step-by-step approach:

1. Set Ki = 0 and Kd = 0. Gradually increase proportional gain Kp until the robot responds to tilt and begins oscillating slowly around the vertical setpoint.
2. Introduce derivative gain Kd to dampen the oscillations and eliminate overshoot. Continue increasing Kd until the robot resists sudden push disturbances without shuddering.
3. Introduce a small integral gain Ki to eliminate steady-state tilt error, enabling the robot to maintain a stationary balance point without drifting forward or backward.

Frequently Asked Questions