Nonlinear Adaptive Robust Precision Pointing Control of Tank Servo Systems

Abstract

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.

A Barrier Neuroadaptive Dynamic Surface Control Approach for Tank Gun Control Systems With Input Saturation

“…Theorem 1: Consider the closed-loop TGCS consisting of the plant (10), the control law ( 40)-( 43), and the virtual control law ( 32)-( 34), which meets |e 1 (0)| < b e (0)|. The following tracking performance and system stability can be guaranteed: t1).…”

“…Remark 1: For the second-order output-constrained system with input saturation (10), if we design the controller according to traditional backstepping control strategy, the coordinate transformation should be introduced as z…”

“…In [6]- [8], adaptive control technique is used to develop controller for TGCSs with unknown parameters. Adaptive robust control algorithms were developed for TGCSs in [9] and [10]. In [11], Hu et al developed adaptive neural network control law to solve the position tracking problem for TGCSs.…”

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

“…[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.…”

The stability of cannon position on tank prototype using PID controller

“…In the previous search, researchers in conducting their research on tank servo systems are using one or two axes coordinate [29], [30], discuss about controlling cannon on the elevation axis using PID [31], [1], [32], discuss about controlling tank using two axes coupling. To improve stability on the cannon, this study will discuss stabilizing cannon on yaw, pitch and roll coordinates when the tank moves from one place to another.…”