Flexible payload transportation using cooperative space manipulators with statics compensation

Area of Science:

• Robotics
• Control Systems Engineering
• Aerospace Engineering

Background:

• Space exploration missions often involve complex robotic systems for payload manipulation.
• Controlling flexible payloads with multiple manipulators presents significant dynamic challenges.
• Accurate modeling and robust control are crucial for successful space operations.

Purpose of the Study:

• To develop a cooperative control strategy for two space manipulators transporting a flexible payload.
• To address the dynamic complexities and uncertainties inherent in space manipulation tasks.
• To enhance the stability and precision of space robotic systems during payload handling.

Main Methods:

• Discretization of the flexible payload using the assumed mode method.
• Development of a system dynamics model based on Lagrange's equations and the Lagrange multiplier method.
• Estimation of payload boundary forces and torques using statics analysis.
• Implementation of a radial basis function neural network (RBF NN) for approximating unknown system terms.
• Design of a NN-based cooperative controller incorporating statics compensation.
• Stability analysis using Lyapunov theory.

Main Results:

• A dynamics model for the two-manipulator, flexible-payload system was successfully established.
• A novel NN-based cooperative controller with statics compensation was designed and validated.
• The controller demonstrated effectiveness in driving both manipulators and the payload to desired states.
• Numerical simulations and experimental results confirmed the controller's efficiency and stability.

Conclusions:

• The proposed NN-based cooperative control strategy is effective for space manipulators handling flexible payloads.
• The integration of statics compensation and RBF NNs enhances control performance and system stability.
• The study provides a viable solution for precise and stable payload transportation in space robotics.