In order to maintain upright stability, two-wheel self-balancing robots belong to a type of underactuated, intrinsically unstable systems that need constant feedback control. The design, modelling, and practical implementation of a two-wheel self-balancing robot employing a proportional-derivative (PD) control approach are presented in this study. An inverted pendulum supported by two driven wheels serves as the model for the robot. An inertial measuring device made up of an accelerometer and gyroscope provides real-time orientation feedback. To fuse sensor data and reduce noise and drift, a complementary filter is used. LabVIEW is used to build the control algorithm on an NI myRIO platform, where the PD controller produces pulse-width-modulated motor commands. According to experimental data, the PD controller can achieve stable balancing with low oscillations and a quick transient response when the gain is tuned appropriately. The paper demonstrates that classical PD control provides a dependable and computationally effective solution for self-balancing robotic platforms, making it appropriate for real-time embedded control, prototype-level, and instructional applications.
S et al. (Thu,) studied this question.