Research On Sensorless Control In Underwater Propulsion System Based On Luenberger Observer

The underwater robot has the advantages of strong environmental adaptability,convenient control and strong endurance.The superior underwater robot propulsion system can realize the multi-posture control of the underwater robot.In order to reduce costs,its thrusters are mostly controlled by sensorless control algorithms.Limited by the current sensorless control that cannot well solve the problem of the forward and reverse position errors of the underwater propeller,the control system becomes unstable or even unable to operate normally.In addition,the sensorless control of the underwater thruster relies on the motor model,so the complicated ocean environment will change the parameters of the underwater thruster,which will affect the position identification and speed identification accuracy of the position sensorless.In order to improve the stability performance and position-speed identification accuracy of the sensorless control,this thesis focuses on the problems encountered by the underwater propeller in the actual environment,and carries out the corresponding problem modeling and solving method research.The specific research contents are as follows:First of all,this thesis conducts mathematical modeling of the permanent magnet synchronous motor(PMSM),the core element of the underwater propeller.On this basis,a Luenberger observer for vector control is constructed and its stability is analyzed.The simulation experiment proves the effectiveness of the Luenberger observer and can estimate a good back-EMF waveform.Then,this thesis proposes a new phase-locked loop(PLL)structure.This article mainly discusses the structure and working principle of the traditional PLL.The Jacobian matrix is established through dynamic equations to verify that when the rotation direction of the PMSM changes,the position error identified in the original direction cannot be converged.Therefore,a PLL structure with convergent position errors in both directions is designed.Use the same theory to verify the effectiveness of the new PLL.The simulation experiment results verify that the traditional PLL cannot guarantee the position error convergence problem and the new PLL can realize the function of the PMSM that the position error can converge in both directions.Secondly,this thesis proposes a new method of parameter identification of recursive least squares(RLS)algorithm with forgetting factor combined with extended Luenberger observer.By establishing the vector diagram of the equation,the sensitivity formula of speed identification to various parameters is obtained.The maximum variation range of each parameter is obtained from the actual working conditions and the parameter variation formula,and the variation range is used as the parameter variation range of the simulation experiment.The RLS algorithm with forgetting factor is used to estimate the selected parameters online to achieve the purpose of optimizing the extended Luenberger observer model.The simulation experiment verifies the sensitivity of each parameter and the effectiveness of the optimized observer,and can reduce the sensitivity of the Luenberger observer to the parameters and improve the speed identification accuracy.Finally,develop an underwater robot propulsion system,and complete the underwater thruster thrust experiment.A high-performance motor drive board was developed to complete the design and debugging of the power supply cabin and the control cabin.On this basis,the validity of the algorithm based on the new PLL was verified,and underwater experiments were completed to obtain the relationship curve between the rotational speed and thrust of the underwater propeller.The experimental results verify the stability and practicability of the underwater propulsion system developed in this thesis.