Backstepping Sliding Mode Adaptive Control Of Ball&Plate System

The theory basis of the paper is the idea of backstepping control and sliding mode control. The Ball&Plate System experiment platform is selected as the control objective in order to achieve cricket’s desired trajectory tracking, which is a two-dimensional extension of Stem&Ball System. The experiment platform is a good tool to test the feasibility and effectiveness of the control algorithms. Effective control algorithms play an important role in many practical control areas. Therefore, this paper has both theoretical significance and practical application value.First, Lagrange dynamics equation of the nonlinear mathematical model is established for the Ball&Plate System. The model is simplified based on two different control variables. In order to improve the real-time performance of control and prevent shock phenomenon, the angle is selected as the control variable, and the simplified model is modified and qualitatively analyzed; Combining the advantages of the backstepping method and sliding mode control method, the backstepping sliding mode control algorithm is proposed; Due to the fixed upper bounds of uncertainties in the method,"chattering" phenomenon may happen in this system. In order to minimize the negative impact of the "chattering" phenomenon, the adaptive thought is introduced and the backstepping sliding mode adaptive control algorithm is proposed; In order to compare the pros and cons of control effect, the backstepping control algorithm based on sliding mode observer is designed. The simulation results show that the backstepping sliding mode adaptive control algorithm has smaller control error, more accurate trajectory tracking and a good control effect for the Ball&Plate System.In addition, the hardware structure of the experimental platform is introduced, and trajectory tracking effect diagrams and the corresponding conclusions of the Ball&Plate System under the effect of two controllers are given in this paper. Physical control results show that the backstepping sliding mode adaptive control algorithm has more superiority.