Adaptive Tuning Of Servo Parameters In BLDC System

The current loop parameter setting of the motor driver directly affects the smoothness and response performance of the servo motor.Therefore,it is of great significance to conduct current loop self-tuning research.Traditional tuning methods have disadvantages such as low tuning efficiency and poor nonlinear adaptability.The first research goal of this paper is to propose a current loop self-tuning method that is easy to use,strong in parameter robustness,and strong in nonlinear adaptability.Another research goal of this article is to design a high-performance brushless motor driver using TMCC160 motor driver chip which can address the situation that the high price of ELMO drives for laboratory badminton robots which limited its application scenarios.Aiming at the above research goals,this paper proposed a current loop tuning strategy based on the combination of the maximum sensitivity method and the NN-IMC-PID controller and designed a BLDC driver based on TMCC160.This article first established the general model of the brushless DC motor in the natural coordinate system and the rotating coordinate system.Then,the various links in the current loop of the servo system is modeled,and the influence of non-linear factors such as the dead time and the conduction voltage drop of the switch tube has been analyzed which helped in reviseing the current loop model.Next,the general form of the RLS algorithm is derived,and an improved method of forgetting factor is introduced for the phenomenon of data saturation.Combining the current loop model with the improved RLS algorithm,a current loop parameter identification method for brushless DC motors is proposed.Aiming at the influence of non-linear links such as inverters on the identification results,the noise figure and correlation index are used to construct the identification validity judgment standard.Based on this,an identification incentive method is designed,and the effectiveness of the algorithm is verified by simulation and experiment.Aiming at the characteristics of strong cross-coupling and complex model in controling of BLDC motors,this paper proposed a current loop tuning strategy based on internal model decoupling control.Using the first-order Pade expansion,the time-delay links such as the inverter are equivalently processed.And on this basis,the relationship between the filter parameters and the current loop PI parameters is derived.In order to improve the model robustness and anti-interference ability of the tuning method,this paper used the maximum sensitivity method to tune the current loop IMCPID controller.And used Simulink model to verify the robustness and anti-interference ability of the algorithm.Finally,this article designd a brushless DC motor driver based on the TMCC160 chip.And carried out the motor parameter identification and current loop PI parameter tuning experiment on the drive.The experimental results prove the effectiveness of the proposed IMC-PID tuning strategy and NN-IMC-PID tuning strategy.Finally,a set of parameter debugging and tuning software based on the tuning method was established.