A two-wheeled self-balancing robot (TWSBR) is non-linear and unstable system. This study compares the performance of model-based and data-based control strategies for TWSBRs, with an explicit practical educational approach. Model-based control (MBC) algorithms such as Lead-Lag and PID control require a proficient dynamic modeling and mathematical manipulation to drive the linearized equations of motions and develop the appropriate controller. On the other side, data-based control (DBC) methods, like fuzzy control, provide a simpler and quicker approach to designing effective controllers without needing in-depth understanding of the system model. In this paper, the advantages and disadvantages of both MBC and DBC using a TWSBR are illustrated. All controllers were implemented and tested on the OSOYOO self-balancing kit, including an Arduino microcontroller, MPU-6050 sensor, and DC motors. The control law and the user interface are constructed using the LabVIEW-LINX toolkit. A real-time hardware-in-loop experiment validates the results, highlighting controllers that can be implemented on a cost-effective platform.

Cyber-physical systems, also known as CPS, is an emerging field of technology that combines the physical and digital worlds by allowing for seamless interaction and communication between the two. One of the key characteristics of a CPS is its ability to take input from its environment and use that information to produce an output through actuators in the physical world. A balancing robot is a prime example of a CPS, as it uses input from its sensors to continually monitor its orientation and take action to prevent falling over by generating thrust through its wheels or manipulating its inertia. In this specific project, a two-wheel self-balancing robot was developed, utilizing the concept of a reverse pendulum. A reverse pendulum by default is inherently unstable and requires an external force to maintain its balance. In this case, the balancing robot produces this external force through the use of wheels and motors. To achieve precise balancing, stepper motors were utilized in the design of the robot. Additionally, the robot has the capability to move in four basic directions and the movement is controlled through an app connected to the robot via Bluetooth. This allows for remote control and monitoring of the robot's movements and actions. Overall, the development of this two-wheel self-balancing robot serves as a demonstration of the potential and capabilities of cyber-physical systems technology.