Active Disturbance Rejection Adaptive Control of Tank Turret-gun Control Systems

Yuan, Shusen; Yao, Jianyong; Deng, Wenxiang; Yang, Guolai; Ma, Xiaoqian

doi:10.23919/ccc50068.2020.9188695

Cited by 7 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The mechatronic dynamics model of the tank vehicle stabilization system is developed, but the effects of unmodeled Electronics 2024, 13,1988 2 of 26 disturbances and other uncertainties of the system are neglected [8]. The coupling, nonlinearity, and uncertainty of the tank vehicle stabilization system are considered in [9], but the essence of its dynamic modeling is only its mechanical dynamic modeling, without considering the electrical dynamic modeling of the actuator, which does not conform to the actual driving mechanism of the vehicle stabilization system. A comprehensive mathematical dynamics equation for the tank vehicle stabilization system is effectively demonstrated in [10].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Robust Control of Vehicle Stabilization System with Uncertainty Based on Neural Network

Wang,

Yuan,

Wang

et al. 2024

Electronics

Self Cite

View full text Add to dashboard Cite

To effectively suppress the effects of uncertainties including unmodeled dynamics and external disturbances in the vehicle stabilization system, a nonlinear robust control strategy based on a multilayer neural network is proposed in this paper. First, the mechanical and electrical coupling dynamics model of the vehicle stabilization system, considering model uncertainty and actuator dynamics, is refined. Second, the lumped uncertainty of the vehicle stabilization system is estimated by a multi-layer neural network and compensated by feedforward control. The high robustness of the system is ensured by constructing the sliding mode feedback control law. The proposed control method overcomes the limitations of sliding mode technology and the neural network and is naturally applied to the vehicle stabilization system, avoiding the adverse effects of high-gain feedback. Based on Lyapunov theory, it is demonstrated that the proposed controller is able to achieve the desired stability tracking performance. Finally, the effectiveness of the proposed control strategy is verified by co-simulation and comparative experiments.

show abstract

Section: Introductionmentioning

confidence: 99%

Nonlinear Robust Control of Vehicle Stabilization System with Uncertainty Based on Neural Network

Wang,

Yuan,

Wang

et al. 2024

Electronics

Self Cite

View full text Add to dashboard Cite

show abstract

“…[5][6][7] Subsequently, the 2-degreeof-freedom (2-DOF) dynamics model of turret and barrel was established. [8][9][10] These dynamics modeling methods take the turret base as the reference plane and ignore the disturbance from the tank chassis to the gun control system. Therefore, the stability of the barrel axis in the inertial space is weak, and it is difficult to achieve the aiming and tracking of the gun under high marching speed.…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers have explored the application of ADRC in TGCSs. 8,[20][21][22][23] On the basis of previous work, an improved ADRC strategy is proposed to improve the response speed and stabilization accuracy of the TGCS from the switching problem of the nonlinear function f al (Á) at piecewise points and the theory of deviation.…”

Section: Introductionmentioning

confidence: 99%

Improved modeling and active disturbance rejection control of tank gun control system

Zheng

Rui

Zhang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

In order to improve the stability control performance of the tank barrel at high speed, a new 2-degree-of-freedom nonlinear dynamics model of yaw and pitch bodies is established, taking into account the 6-degree-of-freedom motion of the tank chassis. By analyzing the direction of the tank barrel in space, the barrel stability control scheme for the tank gun control system with the arbitrary motion of the tank chassis in space is realized. The new dynamics equations of the tank gun control system are established by analytical mechanics. It effectively solves the problem of modeling methods for the tank gun control system in azimuth and elevation when considering the 6-degree-of-freedom motion of tank chassis. Then, an improved active disturbance rejection control strategy for tank gun control system is proposed. A smooth nonlinear function faln(·) is constructed to avoid the switching problem of the function fal(·) at the piecewise points. Next, an improved extended state observer is designed based on the deviation principle by means of the deviation between each state variable and its observation. Afterwards, the stability of the system is analyzed by constructing a Lyapunov function. Simulations were carried out with different input signals to verify the reliability of the dynamics model and control algorithm. The improved active disturbance rejection control has a faster response speed and smaller steady state error. The results show that the stability and tracking performance of the tank gun control system has been improved using the proposed method.

show abstract

“…The unmodeled disturbances include dynamic characteristics of the system and external disturbances which cannot be accurately considered during modeling. In [28][29], the unmodeled disturbances of the tank servo system were estimated by the extended state observer. In [30], the RBF neural network was used to adaptively approximate the system perturbation parameters and unmodeled disturbances to suppress the chattering of the system.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Adaptive Robust Precision Pointing Control of Tank Servo Systems

Yuan

Deng

et al. 2021

IEEE Access

Self Cite

View full text Add to dashboard Cite

This paper focuses on the high performance pointing control of tank servo systems with parametric uncertainties and uncertain nonlinearities including nonlinear friction, backlash and structural flexibility. A comprehensive dynamic nonlinear mathematical model of the two-DOF tank servo system is established. Specifically, to accurately describe the nonlinear friction characteristics in actual systems, a continuous friction model is employed. Moreover, a hybrid nonlinear model combining structural flexibility and transmission backlash is constructed to characterize the nonlinear characteristics of the backlash and flexible coupling between the input and output shafts of the drive end for the tank servo system. By using the backstepping method, a nonlinear adaptive robust controller is presented. In the controller, the adaptive law is compounded to dispose of parametric uncertainties and a well-designed continuous nonlinear robust control law is developed for the purpose of coping with unmodeled disturbances. The closed-loop system stability analysis indicates that the presented controller achieves an asymptotic tracking performance with parametric uncertainties and ensures the robustness against unmodeled disturbances theoretically. The effectiveness of the proposed control strategy is verified by a large number of comparative simulation results.

show abstract

Active Disturbance Rejection Adaptive Control of Tank Turret-gun Control Systems

Cited by 7 publications

References 9 publications

Nonlinear Robust Control of Vehicle Stabilization System with Uncertainty Based on Neural Network

Nonlinear Robust Control of Vehicle Stabilization System with Uncertainty Based on Neural Network

Improved modeling and active disturbance rejection control of tank gun control system

Nonlinear Adaptive Robust Precision Pointing Control of Tank Servo Systems

Contact Info

Product

Resources

About