The nonlinear dynamics of a bird-like flapping wing robot under randomly uncertain disturbances was studied in this study. The bird-like flapping wing robot was first simplified into a two-rod model with a spring connection. Then, the dynamic model of the robot under randomly uncertain disturbances was established according to the principle of moment equilibrium, and the disturbances were modeled in the form of bounded noise. Next, the energy model of the robot was established. Finally, numerical simulations and experiments were carried out based on the above models. The results show that the robot is more likely to deviate from its normal trajectory when the randomly uncertain disturbances are applied in a chaotic state than in a periodic state. With the increase of the spring stiffness under the randomly uncertain disturbances, the robot has a stronger ability to reject the disturbances. The mass center of the robot is vital to realize stable flights. The greater the amplitude of randomly uncertain disturbances, the more likely it is for the robot to be in a divergent state.
In this article, flexible joints are applied to the structure design of large range six-component force platform, and the structure scheme of the large range six-component force platform with flexible joints is proposed. Through the structural parameters optimization design, statics analysis and modal analysis of six-component force platform, the new model large range 6-UPUR six-component force platform with flexible joints is manufactured. The static calibration hardware system based on large-tonnage hydraulic loading principle and the static calibration software system including data acquisition, processing, calibration and performance analysis are developed. Meanwhile, the six-dimensional force-torque loading project is given, the static nonlinear calibration and performance analysis of the six-component force platform is achieved by using method of RBF neural network, and the experimental results show that the developed six-component force platform in this paper has higher precision. Keywords -large range, flexible joints, six-component force platform, static nonlinear calibration, RBF neural network.
AUTHORBIOGRAPHY Shi Zhongpan was born in Qin huangdao, China, in 1969. He received BS and MS from Yanshan University, China, in 1992 and 2001, respectively. Now he is a vice professor and PhD candidate in Yanshan University, China. His research interests include computer application technology and six-dimensional force/torque sensor technology.
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