Research On Trajectory Optimization Of Space Manipulator For On-orbit Tasks When Carrying A Heavy Payload

In recent years, with the continuous development of China's space industry, the manned space flight project has been fully transferred to the stage of space station, and the space operation requirements have become increasingly complex. During construction and maintenance process of space station, it is very necessary to complete some on-orbit tasks such as cabin assembly, auxiliary docking of hovering aircraft, large equipment installation and so on. Since most of these operation objects are floating target with large mass and large inertia, which makes the on-orbit operation much more difficult. The use of space manipulator to help astronauts or even replace them to complete the mentioned tasks can not only guarantee the operation accuracy, but also significantly improve the economic benefits and safety of on-orbit application. This suggests that space manipulator has wide application prospects in on-orbit operations.In order to complete the on-orbit tasks smoothly by using space manipulator when carrying a heavy payload, reasonable evaluation of load-carrying capacity and trajectory optimization study for this kind of task are necessary to carry out. The research in this field is of great scientific significance and theoretical value for promoting on-orbit service ability of space manipulator.This research comes from the National Natural Science Foundation of China named "Research on trajectory optimization of space manipulator for on-orbit tasks when carrying a heavy payload". In this study, we focus on load-carrying capacity analysis and trajectory optimization method of free-floating space manipulator. The main content of this paper includes the following aspects:1. Load-carrying capacity analysis of space manipulator. The dynamics model of space manipulator is established by using spatial operator algebra theory, then the key influencing factors are analyzed. On this basis, for two kinds of typical heavy load-carrying operation including point-to-point task in joint space and trajectory tracking task in Cartesian space, dynamic load-carrying capacity evaluation algorithms are proposed respectively. For trajectory tracking task, a kind of payload maximization initial configuration planning method based on Newton-Raphson iteration and particle swarm optimization is proposed,which demonstrate that maximum load-carrying capacity of space manipulator can be significantly improved by selecting a appropriate initial configuration.2. Research on trajectory optimization method of space manipulator for point-to-point task when carrying a heavy payload. To meet the requirements of load-carrrying operation and point-to-point task, the trajectory optimization problem is transformed into the multi-constrained multi-objective trajectory planning problem which simultaneously satisfies minimization of joint torque, base disturbances and system energy. The joint trajectories are specified using sinusoidal polynomial functions, and the polynomial coefficients are taken as decision vectors.For point-to-point task in joint space, a trajectory optimization algorithm based on MOPSO (multi-objective particle swarm optimization) is proposed, and non-dominated solutions are selected according to the constraint equations. The simulation results show that this method is able to make the maximum load-carrying capacity of space manipulator increased, by compared with the traditional trapezoidal planning method.On this basis, a two-stage method is proposed to solve the optimal trajectory for point-to-point task in Cartesian space. Simulation results show that this method can makes the joint torque, base disturbance and system energy decreased, by compared with the traditional rectilinear planning method.3. Research on trajectory optimization method of space manipulator for trajectory tracking when carrying a heavy payload. Firstly, the dynamics equation of space manipulator is described in state space.Considering load-carrying capacity optimization and trajectory tracking task, the composite performance index including the penalty of end-effector tracking error, optimization of joint torque/system energy and base angular velocity suppression is designed. Based on the mathematical model of the optimal control problem, the state-dependent Riccati equation (SDRE) is established, and the optimal control law is solved by using Taylor series approximation method. Then the trajectory optimization algorithm is proposed based on SDRE control method. The simulation results demonstrate that the proposed approach can meet the requirements of trajectory tracking and improvement of load-carrying capacity.4. Research on trajectory optimization method of space manipulator when carrying a heavy payload with uncertain parameters. Firstly, the dynamics characteristics of the space manipulator are evaluated by using the polynomial chaos method. Then the reliability and efficiency of the proposed method are verified by comparing with the traditional Monte Carlo method. In order to obtain the optimal reference trajectory when the payload contains uncertain parameters, the trajectory planning method combined with polynomial chaos evaluation and multi-objective trajectory optimization is proposed. Considering that the obtained optimal trajectory may not satisfy the requirements of load-carrying task, the trajectory adjustment strategy which introducing the time amplification factor is designed, and the problem caused by evaluation error is avoided by setting a security coefficient. Finally, the effectiveness of the proposed algorithm is verified by simulation examples.5. Experimental research for trajectory optimization algorithms of space manipulator when carrying a heavy payload. The ground experiment platform consisting of the base subsystem, the manipulator subsystem, the payload subsystems and related measuring equipments is present, while the design scheme and working principle of the system are also introduced. Experimental schemes of point-to-point and trajectory tracking tasks are designed, and then experimental studies on the physical platform are carried out. The results verify feasibility and effectiveness of the proposed trajectory optimization algorithms.