Two-Wheeled Inverted-Pendulum Self-Balancing Robot with LQR or PID Control

Petcu, Razvan; Andreescu, Gheorghe-Daniel

doi:10.1109/iccc202255925.2022.9922862

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…From the perspective of automatic control, TWSBRs are unstable, underactuated, and highly coupled. Over time, linear timeinvariant (LTI) controls have been published, the pole placement controller [9], the optimal linear quadratic regulation (LQR) [10], [11], and the proportional integral derivative (PID) [12], [13], [14], [15]. In [16], an optimal PID controller VOLUME 11, 2023 and LQR controller were designed.…”

Section: Introductionmentioning

confidence: 99%

ADRC Attitude Controller Based on ROS for a Two-Wheeled Self-Balancing Mobile Robot

Muñoz-Hernandez,

Díaz-Téllez,

Estevez-Carreon

et al. 2023

IEEE Access

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In this investigation, ROS-based robust attitude control is designed for a two-wheeled selfbalancing mobile robot (TWSBR) using the active disturbance rejection control (ADRC) technique. The designed ROS framework contemplates communication between topics for the desired robot commands and distributed framework design. This open architecture allows the integration of sensors, actuators, and processors. The architecture includes User-Friendly Interface, storage, navigation, control, and drivers. The low-cost robot was designed for educational purposes. It uses an Arduino Mega as a low-level processing unit, a Raspberry Pi 4 as a companion computer where high-level commands are processed, an MPU6050 Inertial Measurement Unit sensor, DC motors GW4058-555 with quadrature type encoder with two phases, the VNH2SP30 controller module used as the power stage and a Lithium Polymer (Li-Po) battery (11.1 V, 2200 mah) is used as the power source. The robust control algorithm is designed through the ADRC methodology based on the extended state observer (ESO). The ESO simultaneously estimates external disturbances, model uncertainties, and unmodeled dynamics such as friction, engine wear, and tire slippage. The stability of the developed controller is analyzed via the Lyapunov stability theory. Real-time experimental results are carried out under the regulation and rejection of external disturbances. The control algorithm is light and easy to implement and adjust in integrated systems with low computer resources. INDEX TERMS ADRC, ESO, Mobile Robot, ROS, Two-wheeled self-balancing, Segway.

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