TAILIEUCHUNG - Hybrid PD and adaptive backstepping control for self balancing two wheel electric scooter

The proposed adaptive controller allows the design of a feedback control that stabilizes self-balancing control of eScooter in the presence of uncertainty and perturbation. Additionally, the sensor signals are treated by Kalman filters and the CAN networks are applied to communication among modules of eScooter. Simulation and experiment results are shown to analyze and validate the performance of proposed controller. | Journal of Computer Science and Cybernetics, , (2014), 347–360 DOI: HYBRID PD AND ADAPTIVE BACKSTEPPING CONTROL FOR SELF-BALANCING TWO-WHEEL ELECTRIC SCOOTER NGUYEN NGOC SON1 , HO PHAM HUY ANH2 1 Faculty of Electronic Engineering, Industrial University of Ho Chi Minh City, Vietnam; nguyenngocson@ 2 Faculty of Electrical and Electronic Engineering, Ho Chi Minh City University of Technology, Vietnam; hphanh@ Abstract. This paper proposes a combination of adaptive self-balancing controller and the left and right turning PD controller for self-balancing two-wheel electric scooter (eScooter). An adaptive selfbalancing controller is synthesized by the backstepping approach and the Lyapunov stability theory. The proposed adaptive controller allows the design of a feedback control that stabilizes self-balancing control of eScooter in the presence of uncertainty and perturbation. Additionally, the sensor signals are treated by Kalman filters and the CAN networks are applied to communication among modules of eScooter. Simulation and experiment results are shown to analyze and validate the performance of proposed controller. Keywords. Adaptive backstepping control, Kalman filter, self-balancing two-wheel robot, CAN networks, embedded system. 1. INTRODUCTION In control theory, the backstepping control is a technique developed in 1990 by Petar and others [5,6,9] for designing stable control applied to a special class of nonlinear dynamic systems. Backstepping control method, based on the Lyapunov design approach, is efficiently applied when higher derivative appearance in presence of uncertainty and perturbation. The key idea of adaptive backstepping technique is to drive the error equation to zero by designing Lyapunov stability approach, by using the recursive structure to seek the controlled function. Hence the adaptive backstepping method induces a feedback control rule that ensures to efficiently control

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