考虑输出约束和输入饱和的弹仓自适应控制

doi:10.12382/bgxb.2022.0896

摘要/Abstract

摘要：

针对存在参数不确定性和外部扰动的某链式回转弹仓的位置跟踪控制问题,提出一种自适应控制方案。该方案基于神经模糊系统(Neuro-Fuzzy System, NFS)、非线性扰动观测器(Nonlinear Disturbance Observer, NDO)及障碍Lyapunov函数(Barrier Lyapunov Function, BLF),在实现高精度控制的同时满足输出约束和输入饱和的工程条件。通过BLF的设计,保证弹仓的位移跟踪误差约束在给定范围内。结合神经网络的函数逼近能力和模糊逻辑系统的推理能力,用于估计系统中的不确定性,减小对模型的依赖;两者结合的NFS作为NDO的一部分,进一步补偿估计误差和外部扰动,提高控制性能。此外,控制器设计考虑了运动过程中的执行器输入饱和问题。仿真结果表明,所设计的控制器在3种典型工况以及系统参数变化情况下均可实现弹仓的高精度位置跟踪控制,满足系统的约束条件。

关键词: 链式回转弹仓, 自适应控制, 神经模糊系统, 输出约束, 输入饱和

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

中图分类号:

TJ301

鲍丹, 卫俞凯, 金鑫, 侯保林. 考虑输出约束和输入饱和的弹仓自适应控制[J]. 兵工学报, 2024, 45(3): 789-797.

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.

图/表 10

图1 自动弹仓的结构示意图

Fig.1 Schematic diagram of automatic magazine structure

图2 期望轨迹(位移、速度和加速度)

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

表1 各类参数设置

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

表1 各类参数设置

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

图3 3种工况下的跟踪误差

Fig.3 Tracking errors under three working conditions

图4 3种工况下的控制力矩

Fig.4 Control torques under three working conditions

图5 神经模糊网络和扰动观测器的耦合估计结果

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

图6 3种控制器作用下的跟踪误差

Fig.6 Tracking errors under the action of three controllers

图7 3种不同控制器作用下的控制力矩

Fig.7 Control torques under the action of three controllers

图8 不确定系统参数下的跟踪误差区间

Fig.8 Tracking error interval under uncertain system parameters

图9 不确定系统参数下的控制力矩区间

Fig.9 Control torque interval under uncertain system parameters

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