Spatial robot prediction control method based on quantum particle swarm optimization algorithm

Abstract

The invention provides a spatial robot prediction control method based on a quantum particle swarm optimization algorithm. Firstly, a lagrangian dynamic model of a spatial robot system is establishedon the basis of an extended mechanical arm method, and a discrete state space model is established by combining the dynamic model with a kinematic model; secondly, a corresponding discrete model prediction controller is designed on the basis of a system extended state space model and a Laguerre polynomial; finally, rolling optimization is conducted on performance indexes under the constraint condition through the quantum particle swarm optimization algorithm, and prediction errors are subjected to feedback correction, so that effective tracking of tail end desired trajectory is achieved. According to the control method, effective tracking of the tail end desired trajectory can be achieved under the given constraint condition, and task space trajectory planning does not need to be carried out in advance; the situation that a global optimum solution cannot be found through a conventional quadratic programming algorithm under multi-constraint conditions can be avoided; energy consumptioncan be optimized while the requirement of tracking precision is met.

Description

technical field [0001] The invention relates to a predictive control method for a space robot, which belongs to the technical field of space operation and control. Background technique [0002] In recent years, with the development of space technology, human space activities have become increasingly frequent. Considering the harshness of the space environment and the complexity of space missions, it has become an inevitable trend to replace astronauts with space robots to complete space missions. However, unlike the fixed-base robot on the ground, the dynamic coupling between the base and the manipulator of the space robot brings great difficulties to its dynamic modeling and control. In order to solve the dynamics and control problems of highly nonlinear systems such as space robots, scholars have proposed many methods. [0003] Based on the principle of conservation of momentum, Umetani and Yoshida proposed a generalized Jacobian matrix that reflects the velocity-level m...

AI Technical Summary

Problems solved by technology

Zong Lijun proposed a mixed integer predictive control method for space robots on the basis of Wang. This method established the priority of each constraint in the control process based on propositional logic, which effectively compensated for the lack of Multiple constraints may lead to insufficient control failure

Images