Balancing and Driving Control of a Bicycle Robot

Abstract

This paper proposes a balancing and driving control system for a bicycle robot. A reaction wheel pendulum control method is adopted to maintain the balance while the bicycle robot is driving. For the driving control, PID control algorithm with a variable gain adjustment has been developed in this paper, where the gains are heuristically adjusted during the experiments. To measure the angles of the wheels the encoders are used. For the balancing control, a roll controller is designed with a non-model based algorithm to make the shortest cycle. The tilt angle is measured by the fusion of the acceleration and gyroscope sensors, which is used to generate the control input of the roll controller to make the tilt angle zero. The performance of the designed control system has been verified through the real experiments with the developed bicycle robot.

Design Low-Order Robust Controller for Self-Balancing Two-Wheel Vehicle

“…e stabilizer using flywheel according to the principle of an inverted pendulum is proposed in [18][19][20][21][22][23]. In this method, the rotation direction of the flywheel will be changed to create a force that balances the gravity of the vehicle to maintain the equilibrium state.…”

“…To control the self-balancing two-wheel vehicle according to the inverted pendulum principle, there are various methods such as PD [20], PID [17][18][19], LQG and MPC [21], SMC [25][26][27], and robust control [11,[28][29][30][31][32][33][34][35][36][37][38]. However, when a two-wheel vehicle works in reality, it will suffer many uncertain effects such as load, noise, and external force.…”

Balancing Control of Two-Wheel Bicycle Problems

“…(i) Controlling balance by controlling the steering angle or using centrifugal force as in the research of Tanaka and Murakami [1], Chen and Dao [2][3][4], Huang et al [5], Vatanashevanopakorn Parnichkun [6], and Wang et al [7] (ii) Controlling balance by changing the center of mass such as Lee and Ham [8], Keo et al [9], and Yamakita et al [10] (iii) Controlling balance by flywheel as in the studies of Suebsomran [11], Sikander and Prasad [12], Beznos et al [13], Hwang et al [14], Karnopp [15], Gallaspy [16], Xu et al [17], Lam [18,19], Lot and Fleming [20], Park and Yi [21], Stephen and Girard [22], Lee et al [23], Suprapto [24], and Kim et al [25] e control method using centrifugal force has the disadvantage of not being able to control bicycle balance when the bicycle is stationary. e control method by changing the center of mass requires more weight, increasing the bicycle weight, while the response time of the system is slow.…”

“…In contrast, two-wheel bicycle models use flywheels based on the principle of inverted pendulum [17,23,25]; to create a balanced torque for the bicycle, the flywheel usually rotates only with low speed, so the flywheel will dissipate a small amount of energy. is group's typical work is research [25]; the author has built a self-balancing two-wheeled model based on the bike's chassis.…”

“…ere are many proposed balance control algorithms for two-wheel bicycle, such as nonlinear control of Lee and Ham [8], Beznos [13], compensator design using root locus approach of Gallaspy [16], PD control of Surpato [19,24], PID control of Lee et al [23], and fuzzy control of Chen and Dao [2][3][4]. However, these control algorithms are not robust; the two-wheel bicycle model cannot carry loads with varied weights and cannot work in disturbance environments.…”