Research on Robot Attitude Control Strategy Based on Model Predictive Control

doi:10.3901/JME.2024.19.088

Abstract

Abstract: For the complex and flexible tasks of robots, robots are required to have the ability of smooth motion, large range positioning and high precision tracking.In order to solve the problem that low real-time performance of offline trajectory planning and low precision numerical solution of inverse kinematics lead to robot jitter, a robot attitude control strategy based on model predictive control is proposed.Firstly, the forward kinematics model of the robot is established and expressed as a state space model.Secondly, considering the two constraints of the ultimate joint position and motion smoothness of the robot, and it is constructed as a compact and convex set.Then, the inverse kinematics of the robot is transformed into the constrained optimal control problem, and the optimal control action is obtained.Finally, the stability of the controller is proved theoretically.Simulation results show that compared with the classical control strategy, the proposed control strategy has better positioning ability in a large range.Apart from this, large range positioning experiments and complex trajectory tracking experiments based on six degree of freedom robot are designed, which confirm the good tracking and positioning ability of the proposed control strategy.

Key words: robot attitude control, model predictive control, system limitations, trajectory tracking

CLC Number:

TG242

YAO Jianjun, ZHANG Yikun, KE Yun, QIAN Chen, WANG Chao. Research on Robot Attitude Control Strategy Based on Model Predictive Control[J]. Journal of Mechanical Engineering, 2024, 60(19): 88-100.

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