Research On Control Strategy Of Servo Systems Of Biaxial Pointing Mechanism For Spaceborne Antenna

The on-orbit attitude adjustment of biaxial pointing tracking antenna is usually achieved by the precise motion of spatial two-dimensional pointing mechanisms.Most two-dimensional pointing mechanisms are driven by servo systems,and the pulsation generated by the servo systems output greatly affects the stability and pointing accuracy of antennas and even spacecraft.In order to enhance the pointing accuracy of the antenna,research on control strategies for antenna servo systems is conducted,the driving performance of the servo systems is improved,and its output pulsation is reduced,which is particularly important for the design of high-precision spacecraft.This article takes the low-speed permanent magnet synchronous motor(PMSM)servo systems of a certain type of spaceborne antenna biaxial pointing mechanism as the research object.In response to the shortcomings of the traditional field oriented control(TFOC)strategy used in its control accuracy,control strategy research is carried out,and model predictive control strategy is proposed,which effectively improves the output characteristics of the servo systems,and suppresses output pulsation.The relevant research work provides a valuable technical approach for formulating control strategies for space antenna servo systems.The main research work of the paper is as follows:Firstly,for the servo systems composed of PMSM and harmonic reducer,the mathematical models of PMSM and harmonic reducer are established,and the mathematical models of the servo systems are integrated based on the physical motion relationship between the two.Based on the MATLAB/Simulink environment,a three closed-loop,such as the current loop,speed loop,and position loop,simulation analysis model of the servo systems using TFOC is established.Through theoretical calculation and simulation debugging,the parameters of each control link in the simulation analysis model are determined.The output characteristics of the servo systems under typical working conditions are analyzed using a simulation analysis model.The results show that the servo systems using TFOC has good tracking performance,but there are significant fluctuations in the motor current and reducer output speed.Secondly,using model predictive control(MPC)instead of PI control in the current loop,the model predictive current control(MPCC)strategy is formed to improve the performance of the current loop controller under constant control parameters.By processing the one beat delay of the d,q axis predicted current,the sampling delay of the MPCC servo systems is compensated,and the control performance of MPCC is optimized.Based on the MPCC control strategy,the control performance of MPCC on motor current in servo systems is simulated and analyzed.The ability of the control strategy to suppress motor current pulsation is evaluated.The relationship between the mismatch of electrical parameters such as stator resistance,permanent magnet flux,and d,q axis inductance and the prediction error of d,q axis current is quantitatively analyzed.Thirdly,to address the impact of PMSM electrical parameters mismatch on MPCC control performance,the snake optimization algorithm(SOA)is introduced to identify PMSM electrical parameters.Because of the shortcomings of standard SOA in electrical parameters identification,such as slow convergence speed,low identification accuracy,and easily falling into local optima,Tent chaotic mapping and quasi-opposition-learning-based strategy are introduced to enhance the diversity of initial snakes,the food quantity and environmental temperature threshold were optimized to improve the convergence speed of the algorithm,and Cauchy mutation cuckoo search algorithm is used to improve the global optimization search ability and robustness of the algorithm,which formed the improved snake optimization algorithm(ISOA).The simulation analysis of electrical parameters identification shows that compared to the standard SOA,ISOA has higher accuracy,faster convergence speed,and better robustness for PMSM electrical parameters identification.Using ISOA method to identify motor electrical parameters can enable the servo systems to achieve better current control performance.Finally,on the basis of the MPCC strategy,MPC is used to replace the PI control in the speed loop,and a sliding mode observer(SMO)is used to monitor the load torque in real-time and compensate for the q-axis reference current through feedback using load torque observation value,forming an improved control strategy for the servo systems based on PI+MPSC+MPCC+SMO.By comparing the control performance with the TFOC strategy,the PI+MPSC+MPCC+SMO control strategy significantly suppresses the output ripple of the harmonic reducer,improves the steady-state performance of the servo systems,and its ability to resist load torque disturbances.