Design and PID control of two wheeled autonomous balance robot

Ünlütürk, Ali; Aydoğdu, Ömer; Guner, Ufuk

doi:10.1109/icecco.2013.6718278

Cited by 18 publications

(5 citation statements)

References 7 publications

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“…The only drawback of this controller is large overshoot. Unluturk Ali et al [15] observed the effects of P, PI and PID controllers on selfbalancing robot with the help of visual computer interface based on Qt-creator [16]. They observed that P-controller, alone is not sufficient for robot's balance.…”

Section: Introductionmentioning

confidence: 99%

Robot development using single stepper driver

Maheshbhai¹,

Kumar²

2022

Robotics, Automation and Non-Destructive Evaluation

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One of the important parameters for the development of specific robots is the mechanical stability of robots. Due to increased applications of robots in various fields such as marines, aerospace, biomedical, and so on, it has now become an important area of research. In this paper, the inverted pendulum concept was used to create a two-wheeled robot (TWR). To balance its vertical position, a Proportional Integrate Derivative (PID) controller was used. The TWR is made up of one Inertial Mass Unit (IMU) sensor, two stepper motors, an Arduino Nano microcontroller, and a stepper motor driver. Both motors were actuated by a single stepper driver in the developed design. Both motors were driven in opposite directions by a single stepper motor driver to ensure forward and backward motion of the robot. The IMU sensor was used to measure angular velocity along the pitch axis and acceleration along the other two axes. The measured data are used to calculate the inclination of TWR () with respect to its vertical position. Accelerometer data was used to compensate for gyro drifts using a complementary filter. With finely tuned PID constants, acceleration to wheels was provided as per inclination angle (). The performance of the developed TWR is found to be almost identical to that of an Arduino UNO-based Self-Balancing Robot [20], despite the fact that it has fewer components, is lighter, and costs less.

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Section: Introductionmentioning

confidence: 99%

Robot development using single stepper driver

Maheshbhai¹,

Kumar²

2022

Robotics, Automation and Non-Destructive Evaluation

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show abstract

“…The only drawback of this controller is large overshoot. Unluturk Ali et al 15 observed the effects of P, PI and PID controllers on self-balancing robot with the help of visual computer interface based on Qt-creator 16 . They observed that P-controller, alone is not sufficient for robot's balance.…”

Section: Introductionmentioning

confidence: 99%

Development of Two Wheeled Robot (TWR) by Single Stepper Driver Using PID Controller

Maheshbhai¹,

Kumar²,

Sinha³

2020

Preprint

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The mechanical stability is an important parameter for the development of specific robots. Nowadays, it has turned into an essential region of research in the current development, due to increased applications of robots in various fields such as biomedical, aerospace, marines etc. In this paper, Two wheeled Robot (TWR) is designed and fabricated following the concept of an inverted pendulum. It balances itself up in the vertical position. The Proportional Integral Derivative (PID) controller was utilized to locate its stable transformed position. The developed two wheeled robot (TWR) was controlled using angle of pendulum (). It consists of two stepper motors, one arduino Nano microcontroller, Inertial Mass Unit (IMU) sensor and stepper motor driver. An IMU sensor comprises of 3-axis accelerometer and 3-axis gyroscope which measure acceleration and angular velocity. The angle of robot () with respect to the vertical position is computed from the mesaured data. It helps the wheel to prevent from fall by providing the acceleration according to its inclination () from the vertical position. Further, complementary filter was used to compensate gyro drifts with the help of accelerometer readings. PID constants were tuned until optimum values are achieved. Performances were compared with ardunio UNO based Self-Balancing Robot [20] & found that the performance of TWR is almost similar to ardunio UNO based Self-Balancing Robot.

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“…Over the past years, self-balancing systems have attracted increased attention, since engineers and researchers are now able to test control algorithms on the inherent non-linear behaviour of such systems. Previous studies deploying basic Proportional Integral Derivative (PID) controllers have been tested [1–3]. However, the addition of motion control of a supporting moving platform requires a more sophisticated control scheme, such as a cascade PID.…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies deploying basic Proportional Integral Derivative (PID) controllers have been tested [1][2][3]. However, the addition of motion control of a supporting moving platform requires a more sophisticated control scheme, such as a cascade PID.…”

Section: Introductionmentioning

confidence: 99%

Velocity and Motion Control of a Self-Balancing Vehicle Based on a Cascade Control Strategy

Velazquez

Cruz

García

et al. 2016

International Journal of Advanced Robotic Systems

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This paper presents balancing, velocity and motion control of a self-balancing vehicle. A cascade controller is implemented for both balancing control and angular velocity control. This controller is tested in simulations using a proposed mathematical model of the system. Motion control is achieved based on the kinematics of the robot. Control hardware is designed and integrated to implement the proposed controllers. Pitch is kept under 1° from the equilibrium position with no external disturbances. The linear cascade control is able to handle slight changes in the system dynamics, such as in the centre of mass and the slope on an inclined surface.

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Design and PID control of two wheeled autonomous balance robot

Cited by 18 publications

References 7 publications

Robot development using single stepper driver

Robot development using single stepper driver

Development of Two Wheeled Robot (TWR) by Single Stepper Driver Using PID Controller

Velocity and Motion Control of a Self-Balancing Vehicle Based on a Cascade Control Strategy

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