Online Identification and Adaptive Control Method for Servo Transmission Device in Weapon Station

doi:10.12382/bgxb.2023.0342

Abstract

Abstract:

The control accuracy and safety of pitch axis servo transmission device in weapon stations may be reduced when the weapon load changes. An adaptive composite control method based on multi-parameter online identification is proposed for the issues above. A model framework for identifying the servo transmission devices with nonlinear transmission clearance, motor, and load friction is constructed based on the linearization method of symbolic functions. The explicit iterative equations for the identified parameters are derived, and the online parameter identification is achieved using a recursive augmented least squares algorithm. On this basis, a composite control method combining an adaptive proportional integral controller and an adaptive state-augmented Kalman filter is proposed. The experimental results show that the parameter identification method can achieve the accurate online identification of 9 key dynamic parameters of servo transmission devices, with steady-state identification errors not exceeding 10%. The adaptive composite control method reduces the root mean square of the system speed following residual by 28.24%, effectively improving the control accuracy and stability margin of the pitch axis when the weapon load changes.

Key words: weapon station, servo transmission device, online identification, adaptive control

CLC Number:

TH132

XIE Xin, ZHENG Jieji, LI Baoyu, YU Bin, FAN Dapeng. Online Identification and Adaptive Control Method for Servo Transmission Device in Weapon Station[J]. Acta Armamentarii, 2024, 45(6): 1761-1775.

Figures/Tables 17

Fig.1 Typical weapon station

Fig.2 Framework of parameters online identification model

Fig.3 Framework of adaptive composite control method

Fig.4 Principle of measurement method for transmission backlash reverse motion

Fig.5 Framework of adaptive composite controller

Fig.6 Framework of adaptive proportional integral controller

Fig.7 Servo transmission device testing platform

Table 1 Component models and parameter values of servo transmission device testing platform

部件名称	型号	参数	数值
		额定功率/W	750
		额定转矩/(N·m)	2.39
永磁同步电机	ASM80B1007-30M	额定转速/(r·min^-1)	3000
		转矩常数/ (N·m·A^-1)	0.48
		转动惯量/(kg·m²)	1.14×10^-4
驱动器	YD8000	转换系数/(A·V^-1)	0.49
		额定扭矩/(N·m)	150
联轴器	GSG-82×68	容许转速/(r·min^-1)	4000
		扭转刚度/ (N·m·rad^-1)	168000
		转动惯量/(kg·m²)	2.7×10^-4
		减速比	161
		最大输出转矩/(N·m)	450
精密减速器	ZKRV-20E-161-B	最大输出转速/ (r·min^-1)	75
		传动间隙/arcmin	≤1
		传动刚度/ (N·m·rad^-1)	5×10⁵
绝对编码器	BCE112K50	角度分辨率/bit	19
惯量盘		转动惯量/(kg·m²)	0.22
砝码		质量/kg	5
		个数	12

Table 2 Set values of parameters to be identified in the simulation model

参数/单位	空载	带载
负载转动惯量J_l/(kg·m²)	0.22	0.45
传动刚度K_s/(N·m·rad^-1)	1×10⁶	1×10⁶
电机黏滞阻尼系数B_m/(N·m·rad^-1·s)	0.005	0.005
负载黏滞阻尼系数B_l/(N·m·rad^-1·s)	20	20
电机正库伦摩擦力矩 $T f c m +$ /(N·m)	0.1	0.1
电机负库伦摩擦力矩 $T f c m -$ /(N·m)	-0.1	-0.1
负载正库伦摩擦力矩 $T f c l +$ /(N·m)	5	5
负载负库伦摩擦力矩 $T f c l -$ /(N·m)	-5	-5
传动间隙2θ_b/arcmin	1	1

Table 2 Set values of parameters to be identified in the simulation model

参数/单位	空载	带载
负载转动惯量J_l/(kg·m²)	0.22	0.45
传动刚度K_s/(N·m·rad^-1)	1×10⁶	1×10⁶
电机黏滞阻尼系数B_m/(N·m·rad^-1·s)	0.005	0.005
负载黏滞阻尼系数B_l/(N·m·rad^-1·s)	20	20
电机正库伦摩擦力矩 $T f c m +$ /(N·m)	0.1	0.1
电机负库伦摩擦力矩 $T f c m -$ /(N·m)	-0.1	-0.1
负载正库伦摩擦力矩 $T f c l +$ /(N·m)	5	5
负载负库伦摩擦力矩 $T f c l -$ /(N·m)	-5	-5
传动间隙2θ_b/arcmin	1	1

Fig.8 Convergence process of online identification of model parameters

Table 3 Steady state convergence results of online identification of model parameters

参数	空载		带载
参数	辨识值	辨识误差/%	辨识值	辨识误差/%
负载转动惯量J_l/(kg·m²)	0.22	0	0.451	0.22
传动刚度K_s/(N·m·rad^-1)	1×10⁶	0	1×10⁶	0
电机黏滞阻尼系数B_m/(N·m·rad^-1·s)	0.0046	6.6	0.0047	6
负载黏滞阻尼系数B_l/(N·m·rad^-1·s)	20.54	2.7	20.55	2.75
电机正库伦摩擦力矩 $T f c m +$ /(N·m)	0.0904	9.6	0.091	9
电机负库伦摩擦力矩 $T f c m -$ /(N·m)	-0.1034	0.34	-0.103	0.3
负载正库伦摩擦力矩 $T f c l +$ /(N·m)	4.612	7.76	4.607	7.86
负载负库伦摩擦力矩 $T f c l -$ /(N·m)	-4.68	6.4	-4.675	6.5
传动间隙2θ_b/arcmin	1~1.1	10	1.1	10

Table 3 Steady state convergence results of online identification of model parameters

参数	空载		带载
参数	辨识值	辨识误差/%	辨识值	辨识误差/%
负载转动惯量J_l/(kg·m²)	0.22	0	0.451	0.22
传动刚度K_s/(N·m·rad^-1)	1×10⁶	0	1×10⁶	0
电机黏滞阻尼系数B_m/(N·m·rad^-1·s)	0.0046	6.6	0.0047	6
负载黏滞阻尼系数B_l/(N·m·rad^-1·s)	20.54	2.7	20.55	2.75
电机正库伦摩擦力矩 $T f c m +$ /(N·m)	0.0904	9.6	0.091	9
电机负库伦摩擦力矩 $T f c m -$ /(N·m)	-0.1034	0.34	-0.103	0.3
负载正库伦摩擦力矩 $T f c l +$ /(N·m)	4.612	7.76	4.607	7.86
负载负库伦摩擦力矩 $T f c l -$ /(N·m)	-4.68	6.4	-4.675	6.5
传动间隙2θ_b/arcmin	1~1.1	10	1.1	10

Fig.9 Convergence process of online identification of servo transmission device parameters

Table 4 Steady state convergence results of online identification of servo transmission device parameters

参数	空载	带载
负载转动惯量J_l/(kg·m²)	0.246	0.453
传动刚度K_s/(N·m·rad^-1)	9.7×10⁵	8.9×10⁵
电机黏滞阻尼系数B_m/(N·m·rad^-1·s)	2.4×10^-3	2.4×10^-3
负载黏滞阻尼系数B_l/(N·m·rad^-1·s)	23.17	25.23
电机正库伦摩擦力矩 $T f c m +$ /(N·m)	0.1	0.11
电机负库伦摩擦力矩 $T f c m -$ /(N·m)	-0.095	-0.12
负载正库伦摩擦力矩 $T f c l +$ /(N·m)	1.9	2.89
负载负库伦摩擦力矩 $T f c l -$ /(N·m)	-1.86	-2.01
传动间隙2θ_b/arcmin	0.82	1.74

Table 4 Steady state convergence results of online identification of servo transmission device parameters

参数	空载	带载
负载转动惯量J_l/(kg·m²)	0.246	0.453
传动刚度K_s/(N·m·rad^-1)	9.7×10⁵	8.9×10⁵
电机黏滞阻尼系数B_m/(N·m·rad^-1·s)	2.4×10^-3	2.4×10^-3
负载黏滞阻尼系数B_l/(N·m·rad^-1·s)	23.17	25.23
电机正库伦摩擦力矩 $T f c m +$ /(N·m)	0.1	0.11
电机负库伦摩擦力矩 $T f c m -$ /(N·m)	-0.095	-0.12
负载正库伦摩擦力矩 $T f c l +$ /(N·m)	1.9	2.89
负载负库伦摩擦力矩 $T f c l -$ /(N·m)	-1.86	-2.01
传动间隙2θ_b/arcmin	0.82	1.74

Fig.10 Comparison results of fitting degrees among different models and actual systems

Table 5 Root mean squares of fitting errors among different models and actual systems

工况	线性模型			本文模型
工况	参数固定不变	参数在线更新	降低/ %	参数固定不变	降低/ %	参数在线更新	降低/ %
空载	5.23	5.16	1.34	2.12	59.46	2.11	59.66
带载	6.83	4.36	36.16	3.52	48.46	2.37	65.30

Fig.11 Validation test results of adaptive composite control method

Table 6 Root mean squares of speed following residuals for different control methods

工况	定值复合控制方法	自适应复合控制方法	降低/%
空载	5.92	5.87	0.84
带载	10.34	7.42	28.24

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