Adaptive robust control for tank stability: A constraint-following approach

Abstract

This article addresses a control problem for tank stability based on constraint following. The objective is to design a control to drive the tank stability control system to follow a pre-specified stability constraint approximately: with the consideration of (possibly) time-varying uncertainty (including system modeling error and road excitation), if the barrel deviates from the target angle, drive it to be arbitrarily close to the target angle; and if the barrel points to the target angle, drive it to stay there. This is formulated as a problem of approximate constraint-following control. First, as the model-based control design object, the dynamic equation of the tank stability control system with the system modeling error and the road excitation is obtained. Second, as the control objective, the stability constraint is formulated. Third, as the control strategy, an adaptive robust control is proposed for approximate constraint following. Fourth, as the control object, a virtual prototype model of tank driving on bumpy road is established with multi-body dynamics software RecurDyn. Finally, real-time servo control and target observation of the tank stability system are performed by co-simulation. It shows that the constraint-following error converges quickly to [Formula: see text] in 1.5 s. By this, the tank stability control system can be always stable even if the tank is driving and disturbed with frequent road excitation.

Sliding mode controller with neural network compensation for tank

“…2. The 3D model of E-level road surface is built according to the literature [8], and it is imported into the Recurdyn software. The controller is written in Matlab/Simulink.…”

Adaptive Robust Stability Control of All-Electrical Tank Gun Compensated by Radial Basis Neural Network

“…However, PID is always a linear controller, and it is difficult to cope with the complex nonlinearities in TGCS, resulting in a sharp decrease in system performance. Furthermore, the adaptive nonlinear robust control method is applied to the TGCS control system [12][13][14][15][16][17]. Specifically, Cai et al effectively suppressed the parameter uncertainty and other uncertainties of the tank gun control system by using adaptive robust control strategy [12].…”

“…Ma et al designed an adaptive robust controller based on constraint following for the two-axis coupled dynamic model of TGCS [13]. On this basis, considering the coupling, nonlinearity and uncertainty of the tank gun, the nonlinear adaptive robust controller was applied to the moving TCGS system [14]. During the control of the tank gun, the barrel is brought close to the target angle if it deviates from the target and kept at the target angle if it is on the target.…”

Constrained control methods for lower extremity rehabilitation exoskeleton robot considering unknown perturbations

“…The modeling process does not require any linearization and approximation, which greatly simplifies the computational process and control complexity. In recent years, many researchers have achieved significant scientific results through U-K theory [12][13][14][15][16]. Chen et al [17][18][19] realize the constraint tracking servo control of mechanical system based on U-K theory, and complete the optimal design of fuzzy mechanical system.…”