Underwater robot path tracking control method based on model predictive control

Abstract

The invention provides an underwater robot path tracking control method based on model predictive control, which belongs to the technical field of underwater robot motion control. The method includesthe following steps: a discrete time prediction model is obtained according to the kinematics and dynamics models of an underwater robot and is transformed into a regression model, and the parametersare estimated online based on a recursive least square method; an optimized objective function and constraints are determined for a target path point tracking problem by using the model, and an optimal control input sequence is obtained by a projection gradient method; and the optimal control input at the current time is executed on the underwater robot, and the underwater robot is enabled to reach every target path point through continuous iteration. By using the method, path point tracking control can be implemented efficiently and online on an underwater robot, the constraints of control input can be handled, and certain robustness can be maintained in the presence of model uncertainty and external disturbances.

Description

technical field [0001] The invention belongs to the technical field of motion control of underwater robots, in particular to a path tracking control method for underwater robots based on model predictive control. Background technique [0002] The discovery of marine science is highly dependent on underwater detection technology and equipment. Due to the complex marine environment and extreme conditions, currently operating underwater robots are mainly used to replace or assist humans in detection, observation and sampling. For all kinds of underwater robots, ensuring their controllable motion is the most basic functional requirement and the prerequisite for realizing various complex tasks. The dynamics and kinematics models of underwater robots are complex, with the characteristics of multivariable, nonlinear, strong coupling, input or state constraints, and time-varying, and the model parameters are uncertain, and there are external disturbances such as ocean currents. The...

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Problems solved by technology

[0009] However, each decision-making moment in the model predictive control algorithm requires the optimal control input sequence. This is a solution process of a nonlinear optimization problem, which includes the iterative steps of the nonlinear programming algorithm. The calculation is complex and time-consuming. It is applied to The problem that the requirements of control performance and computational efficiency cannot be satisfied at the same time when the waypoint tracking control of underwater robots

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