Trajectory tracking method within fixed time of underwater robot-manipulator system

Abstract

The invention discloses a trajectory tracking method within fixed time of an underwater robot-manipulator system, which belongs to the field of robot control. The method comprises the following steps: designing a fixed time disturbance observer, and adopting the fixed time disturbance observer to realize observation on unmodeled dynamics and exterior disturbance of the underwater robot-manipulator system within fixed time, thereby obtaining influence torque, on the underwater robot-manipulator system, of the unmodeled dynamics and exterior disturbance; designing a fixed time integral sliding mode controller which balances influences, on the underwater robot-manipulator system, of the unmodeled dynamics and exterior disturbance by generating a compensation torque according to the influences; and finally, realizing precise tracking on the operation trajectory of the underwater robot-manipulator system by the fixed time integral sliding mode controller. The fixed time integral sliding mode controller designed by the method can track an expected trajectory within the fixed time, and realizes fixed-time stabilizing of the system.

Description

technical field [0001] The invention relates to the field of robot control, in particular to an underwater robot-manipulator system fixed-time trajectory tracking method. Background technique [0002] Sliding mode variable structure control is not sensitive to the unmodeled part of the system, and has the characteristics of fast response and strong robustness, so it is widely used in the control of nonlinear systems, so it is more suitable for underwater robot-manipulator systems in complex working environments (Underwater Vehicle-Manipulator Systems, UVMS). Wang et al. proposed a non-singular terminal sliding mode control method based on time delay estimation. Combining the characteristics of time delay estimation without dynamic model and the strong robustness of non-singular terminal sliding mode control, the algorithm has good control performance and anti-interference Ability to realize the trajectory tracking control of UVMS under complex disturbances; Tang Qirong and ...

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Problems solved by technology

The PID control method is relatively mature and widely used in practical engineering. Its control parameters need to adapt to the changes of model parameters; neural network control does not rely on precise mathematical models, and has strong learning ability and adaptability, but neural network control needs to pass through a large number of Sample training to improve control accuracy; adaptive control is suitable for occasions with strong model parameter uncertainty, slow parameter change and less degrees of freedom, but the control stability is poor

However, the UVMS model has great uncertainty, high degrees of freedom, and rapid parameter changes, so PID control methods, neural network control, and adaptive control methods are not completely suitable for UVMS control.

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