Adaptive Control of Magazines Considering Output Constraints and Input Saturation

doi:10.12382/bgxb.2022.0896

Abstract

Abstract:

An adaptive control scheme is proposed for the position tracking control of a chain rotary magazine with parameter uncertainties and external disturbances. Based on neuro-fuzzy system ( NFS), nonlinear disturbance observer (NDO), and barrier Lyapunov function (BLF), the proposed scheme achieves high precision control while satisfying the engineering conditions of output constraint and input saturation. The BLF design ensures that the position tracking error of magazine is constrained within a bounded range. The function approximation ability of neural network and the reasoning ability of fuzzy logic system are combined to estimate the uncertainties of the system and reduce the dependence on the model. The combined NFS is used as part of NDO to further compensate for estimation errors and external disturbances and improve the control performance. In addition, the actuator input saturation problem is considered in the design of the controller. The simulated results show that the designed controller can realize the high-precision position tracking control of the magazine under three typical working conditions and system parameter changes, and meet the constraints of the system.

Key words: chain rotary magazine, adaptive control, neuro-fuzzy system, output constraint, input saturation

CLC Number:

TJ301

BAO Dan, WEI Yukai, JIN Xin, HOU Baolin. Adaptive Control of Magazines Considering Output Constraints and Input Saturation[J]. Acta Armamentarii, 2024, 45(3): 789-797.

Figures/Tables 10

Fig.1 Schematic diagram of automatic magazine structure

Fig.2 Desired trajectory (displacement, velocity, and acceleration)

Table 1 Parameter settings

参数	公式序号	数值	参数类型
κ₁	(22)	60	设计参数
κ₂	(26)	60	设计参数
k_s	(17)	60	设计参数
λ	(29)	0.5	设计参数
Γ	(29)	diag(3,…,3)	设计参数
M₀	(39)	2.7;5.7;8.3	系统参数
B_e	(40)	3.0;7.2;11.0	系统参数
A_s	(40)	100;100;100	系统参数
M_fc	(40)	2.5;6.8;7.8	系统参数
M_fs	(40)	8.0;24;26	系统参数
$q · s$	(40)	1.6;1.1;0.9	系统参数
k_b	(20)	0.01	约束参数
τ_max	(9)	250	约束参数

Table 1 Parameter settings

参数	公式序号	数值	参数类型
κ₁	(22)	60	设计参数
κ₂	(26)	60	设计参数
k_s	(17)	60	设计参数
λ	(29)	0.5	设计参数
Γ	(29)	diag(3,…,3)	设计参数
M₀	(39)	2.7;5.7;8.3	系统参数
B_e	(40)	3.0;7.2;11.0	系统参数
A_s	(40)	100;100;100	系统参数
M_fc	(40)	2.5;6.8;7.8	系统参数
M_fs	(40)	8.0;24;26	系统参数
$q · s$	(40)	1.6;1.1;0.9	系统参数
k_b	(20)	0.01	约束参数
τ_max	(9)	250	约束参数

Fig.3 Tracking errors under three working conditions

Fig.4 Control torques under three working conditions

Fig.5 Coupling estimation results of neuro-fuzzy network and disturbance observer

Fig.6 Tracking errors under the action of three controllers

Fig.7 Control torques under the action of three controllers

Fig.8 Tracking error interval under uncertain system parameters

Fig.9 Control torque interval under uncertain system parameters

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