Flexible payload transportation using cooperative space manipulators with statics compensation

This study focuses on the dynamics and cooperative control for two space manipulators transporting the flexible payload. The assumed mode method is used to discretize the flexible component. Based on the Lagrange's equations of second kind and Lagrange multiplier method, the dynamics model of system is built. To compensate for the disturbances from the payload acting on the manipulators, the boundary forces and torques of the payload are estimated based on the statics analysis. A radial basis function neural network (RBF NN) is adopted to approximate some unknown terms. A NN-based cooperative controller with statics compensation is proposed for such a space manipulation system to drive the manipulators and beam to the desired states. The stability of the controller is proven through Lyapunov theory. Numerical simulations via the constant-step generalized-α integrator and some experiments based on QArm platforms are performed to show the efficiency of the designed controller.