Abstract
The sliding mode control algorithm based on grey prediction theory is proposed in this study, aiming at the uncertainties in the servo system of fruit harvesting robot and the external disturbances that may affect the control quality of conventional sliding mode control algorithm. The proposed algorithm uses the grey theory ability to unknown information data to establish the grey model to the uncertainty and real-time compensate the unmodeled dynamics and the interference signal of system. Meanwhile, an improved reaching law direction is proposed to resist chattering and improve control accuracy. The simulation results show that the proposed sliding mode control algorithm effectively predicts and compensates the unmodeled dynamics and disturbances signal in the DC motor servo system of the fruit harvesting robot and improves the control precision of controller which provides the theoretical basis for the industrial application based on the grey prediction theory of sliding mode control algorithm.
Highlights
Fruit harvesting robot has been important research field of Agricultural Engineering in recent years, which is widely used for Picking tomatoes, cucumber, orange, apple, cherry, etc., (Zhang, 2010; Men et al, 2013; Qian et al, 2010; Yuan et al, 2009; Cai et al, 2009; Qinghua et al, 2009; Tanigaki et al, 2008; Liu et al, 2008)
Taking into account uncertainties of the fruit harvesting robot servo system and quality control of traditional sliding mode control algorithm which is affected by the external disturbance, it proposes sliding mode control algorithm based on a gray prediction theory
The thesis draws a variable structure control algorithm based on the gray prediction theory and the improved sliding mode reaching law
Summary
Fruit harvesting robot has been important research field of Agricultural Engineering in recent years, which is widely used for Picking tomatoes, cucumber, orange, apple, cherry, etc., (Zhang, 2010; Men et al, 2013; Qian et al, 2010; Yuan et al, 2009; Cai et al, 2009; Qinghua et al, 2009; Tanigaki et al, 2008; Liu et al, 2008). Tomato harvesting manipulator is seven degree of freedom manipulator consisting of 2 prismatic joints and 5 revolute joints (Liang et al, 2008, 2005; Liang and Wang, 2006) with a highly nonlinear system It is an effective method for the nonlinear systems of sliding mode variable structure control. Sliding mode variable structure control appeared in twentieth Century 50 year It has experienced 50 years of development and formed a relatively independent branch of study, becoming a general design method of automatic control system (Liu and Sun, 2007). The study Kim et al (1996) design a disturbance observer based on the theory of two element control in the sliding mode control to feed-forward compensation for observed interference. This study put forward an improved reaching law method to eliminate the chattering problem in sliding mode control. The algorithm builds up the uncertainty of gray model using the gray theory ability to unknown information data and real-time compensate system unmodeled dynamics and interference signal to improve control accuracy
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