Design and Realization of Two-Wheeled Auto-Balancing Vehicle

Li, Shuangquan; Kong, Lingyong; Nie, Xinxin; Li, Jian

doi:10.1109/aits.2015.16

Cited by 4 publications

(3 citation statements)

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“…The main body of PID regulates the system through three links: proportion, integral, differential [7]. The main design idea of this method is to compare the system set value with the system output value through proportional, integral and differential calculation to form a deviation value, and control the system by calculating the difference [8]. The deviation value is obtained by comparing the feedback value with the target value, and then the system is adjusted through the proportional coefficient corresponding to the p-ring.…”

Section: Pid Control Algorithmmentioning

confidence: 99%

Research on Algorithm Based on Improved PID Controller

2022

J. Phys.: Conf. Ser.

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In order to solve the problem of noise and lag in the control system, which can not make the balance vehicle reach a fast and stable state, an improved PID closed-loop controller is proposed. The piecewise function is added to the closed-loop controller to weaken the integral, and the integral link is weakened in different states to make the system reach a stable state. The data collected by the sensor is processed, and the balance system reaches the steady state through Kalman filtering algorithm. The simulation results show that the improved PID control algorithm can effectively reduce the lag effect. At the same time, the environmental noise can be removed after Kalman filter processing, so that the balance car can reduce the jitter time and achieve stability quickly.

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Section: Pid Control Algorithmmentioning

confidence: 99%

Research on Algorithm Based on Improved PID Controller

2022

J. Phys.: Conf. Ser.

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“…The kinetic energy of the IPS is the sum of linear and rotational kinetic energy of each part. According to (7) - (12), it can be obtained by…”

Section: B Dynamic Modlementioning

confidence: 99%

“…The authors in [11] proposed an adaptive inversion control algorithm and the anti-interference performance of the TWSB vehicle was verified by simulation. In [12], an incremental PID algorithm was used to form a closed-loop control system for TWSB vehicles, and a Kalman filter was used to compensate for the disadvantage of the instability of the accelerometer output and the drift of the gyroscope during the motion. Literature [13] proposed a common Actor-Critic algorithm, composed of an adaptive search network and an adaptive review network, to control TWSB vehicles in continuous domain.…”

Section: Introductionmentioning

confidence: 99%

Control of Different-Axis Two-Wheeled Self-Balancing Vehicles

et al. 2020

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This paper investigates the controls of straight running and turning of a different-axis twowheeled self-balancing (DATWSB) vehicle. The inverted pendulum system (IPS) with gyroscopic effect is used to describe the uncertainty caused by the working conditions. Based on the generalized coordinate systems, the nonlinear mathematical model of the IPS is established according to Lagrange equation. The sliding mode controller (SMC) and adaptive sliding mode controller (ASMC) are respectively designed to control the system, in which the roll angle feedback is used. The simulation results of three models with/without the controllers are presented, which indicate that the ASMC can make the IPS recover upright faster in straight running, and better achieve the desired roll angle in turning compared with the SMC. Bikesim, a commercial software, is used to build a two-wheeled vehicle model with self-balancing function in combination with Matlab/Simulink. The results show that the ASMC can guarantee the anti-interference and turning abilities of the DATWSB vehicle. INDEX TERMS Different-axis two-wheeled self-balancing vehicle, gyroscopic effect, inverted pendulum, sliding mode control, adaptive sliding mode control.

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