Adaptive finite-time command-filtered backstepping sliding mode control for stabilization of a disturbed rotary-inverted-pendulum with experimental validation

Abstract

In this paper, the finite-time stabilization of the disturbed and uncertain rotary-inverted-pendulum system is studied based on the adaptive backstepping sliding mode control procedure. For this purpose, first of all, the dynamical equation of the rotary-inverted-pendulum system is obtained in the state-space form in the existence of external disturbances and model uncertainties with unknown bound. Afterward, a novel command filter is defined to enhance the control strategy by consideration of a virtual control input. Therefore, the differential signal is replaced by the output of the command filter to reduce the complicated computing in the control process. Hence, the finite-time convergence of the sliding surface to the origin is attested by using the backstepping sliding mode control scheme according to the Lyapunov theory. Besides, the unknown upper bound of the exterior perturbation and uncertainty is approximated providing the adaptive control technique. Finally, simulations and experimental results are done to demonstrate the impression and proficiency of the suggested method.

A novel fixed‐time sliding mode control for nonlinear manipulator systems based on adaptive disturbance observer

“…Theorem 1. For the robotic manipulator system Equations ( 2) and (3), when using the ADO Equations ( 10) and (11), and the adaptive law Equation ( 12), the composite disturbance corresponding to the robotic manipulator system can be estimated at a fixed time, and the estimation error of the ADO converges to a given region at a fixed time.…”

“…However, since the robotic manipulator is a system with nonlinear and complex perturbations, the actual control is susceptible to modeling errors, friction, and external disturbances, which all increase the difficulty of control. In response to the problems of nonlinear systems, scholars have developed different control methods to improve them, such as neural network control [3,4], fuzzy control methods [5][6][7][8][9], backstepping control methods [10][11][12], and sliding mode control (SMC) methods [13][14][15][16][17][18].…”

Robust backstepping control for maneuver aircraft based on event-triggered mechanism and nonlinear disturbance observer

“…In the DSC method, the command filter is concatenated behind the virtual controls. By this means, the derivatives of the virtual controls are substituted with the output of the command filter, and the tracking performance of the command filter is guaranteed by the Lyapunov stability theory (Mofid et al , 2022). However, with the application of the DSC method, the coupling term of the system states and dynamic surface errors is inevitable in the stability analysis, which may affect the stability of the system.…”

Enhancing Stability Control of Inverted Pendulum Using Takagi-Sugeno Fuzzy Model with Disturbance Rejection and Input-Output Constraints

“…Over the years, numerous control approaches have been proposed and investigated to tackle the inverted pendulum control problem, each aiming to overcome the inherent instability and achieve robust stabilization. These include classical control techniques, such as PID control 8 , as well as modern control methodologies, such as adaptive finite-time command-filtered backstepping sliding mode control 9 , indirect adaptive fuzzy model predictive control 10 and adaptive neural network control 11 . While these methods have shown varying degrees of success, they often face limitations in terms of robustness, adaptability to nonlinearities, and handling uncertainties, which are critical factors in achieving stable and efficient control of the inverted pendulum system.…”