Abstract
With the goal of creating a flexible spatial parallel robot system in which the elastic deformation of the flexible link causes a rigid moving platform to produce small vibrations, we proposed an adaptive sliding mode control algorithm based on a neural network. To improve the calculation efficiency, the finite element method was used to discretize the flexible spatial link, and then the displacement field of the flexible spatial link was described based on floating frame of reference coordinates, and the dynamic differential equation of the flexible spatial link considering high-frequency vibrations was established through the Lagrange equation. This was combined with the dynamic equation of the rigid link and the dynamic equation considering small displacements of the rigid movable platform due to elastic deformation, and a highly nonlinear and accurate dynamic model with a rigid–flexible coupling effect was obtained. Based on the established accurate multi-body dynamics model, the driving torque with coupling effects was calculated in advance for feedforward compensation, and the adaptive sliding mode controller was used to improve the tracking performance of the system. The nonlinear error was examined to determine the performance of the neural network’s approximation of the nonlinear system. The trajectory errors of the moving platform in the X-, Y-, and Z-directions were reduced by 12.1%, 38.8%, and 50.34%, respectively. The results showed that the designed adaptive sliding mode neural network control met the control accuracy requirements, and suppressed the vibrations generated by the deformation of the flexible spatial link.
Highlights
Parallel robots exhibit good dynamic performance, small cumulative errors, and fast response speeds
To achieve high control accuracy, suppress flexible vibrations, and achieve dynamic control of the system, a combination of a neural network controller and an adaptive sliding mode controller was used in this work to study the control of flexible spatial parallel robots
To verify the correctness of the dynamic simulation model, the dynamic simulation model of the flexible spatial parallel robot was first compared with the results of a
Summary
Parallel robots exhibit good dynamic performance, small cumulative errors, and fast response speeds. To improve the calculation efficiency of the control system, the deformation of the flexible link and the establishment of an accurate dynamic model that considers the rigid–flexible coupling effects are essential. To achieve high control accuracy, suppress flexible vibrations, and achieve dynamic control of the system, a combination of a neural network controller and an adaptive sliding mode controller was used in this work to study the control of flexible spatial parallel robots. Based on the established precise dynamics model of the system, the pre-calculated driving torque with coupling effects is subjected to feedforward compensation, and the adaptive sliding mode controller is used to ensure the tracking performance and improve the response speed of the system.
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