Simulation Study Of Active Disturbance Rejection Control Technology To AUV Motion Control

Autonomous Underwater Vehicle is a system with nonlinear, strong coupled, time-variable and uncertain model exposed to unknown external disturbances. For these reasons, higher requirement is put forward about design of AUV motion controller. General control strategy is hard to obtain better control results. Active disturbances rejection controller can realize decoupling control without accurate mathematical model of objects. This paper introduces Active Disturbance Rejection Control technology into motion control of AUV system in order to solve the limitations of traditional control methods. Analytical research is made on Active Disturbance Rejection Controller (ADRC) and its application in AUV motion control and its further improvements.Firstly, this essay analysis AUV's dynamic model, build a 4-degrees of freedom mathematical model of AUV based on the characteristics of the disc typed AUV, and get equations of depth, heading and speed control, further, establish AUV's thruster model and interference model of current. Secondly, based on the advantages and disadvantages of traditional PID controller, this essay discusses the basic knowledge of tracking differentiator, extended state observer and non-linear state error feedback, describes the chart of active disturbance rejection controller and the implements of its algorithm. Build a simulation model of active disturbance rejection controller in Matlab/Simulink using S-function.Once again, according to the problem of setting ADRC parameters, determine the principles of the parameter setting. Design the underwater vehicle controller with ADRC technology, simulate with locating depth, orientation, and speed. Results show that the ADRC can implement AUV control with accuracy, robustness, and stability, and overcome the influence of such interference current. Comparing with traditional PID controller, ADRC performances better.Finally, analyze the performance of ADRC, and design a more robust ADRC based on neural network, using BP neural network to compensate the object's changes, according to ADRC and its ESO characteristics. The simulation confirms that ADRC based on neural network controls AUV well with large parameter changes.This essay supports for applications of ADRC in other similar marine engineering equipment control problem.