Finite-time sliding mode tracking control for active suspension systems via extended super-twisting observer

Abstract

In this article, a novel sliding mode tracking control scheme for vehicle active suspension systems with matched and mismatched uncertainties is proposed based on super-twisting concept. In order to stabilize suspension deflection motion to the desired trajectory in finite time, a finite-time sliding mode controller is designed. Specifically, a novel trajectory function is proposed to adjust the suspension performances (e.g. ride comfort, tire dynamic load and suspension deflection). Compared with the first-order sliding mode control method, the proposed tracking control scheme can effectively improve the ride comfort and ensure the suspension deflection constraint. The control scheme requires only the suspension deflection and acceleration feedback and thus is easy to implement. The uncertainties of the active suspension system are considered as a total disturbance term which can be estimated online, and the estimated error can become a vanishing term in finite time using an extended super-twisting disturbance observer. Finally, the proposed control algorithm is applied to a quarter-car active suspension model, and numerical and experimental results are provided to show the merits and effectiveness of the proposed control scheme.

Adaptive Finite-Time NN Control for 3-DOF Active Suspension Systems With Displacement Constraints

“…It shows that the control singularity can be avoided since the controller doesn't contain the derivatives of term with fractional power. Different from the work [32], Wang et al [33] introduced terminal super-twisting algorithm into terminal sliding-mode method and further demonstrated a finite-time control approach that solved the total disturbance problem. The parameter uncertainties of ASSs aren't arouse attention in these works.…”

“…The parameter uncertainties of ASSs aren't arouse attention in these works. In addition, the displacement constraints problem of ASSs wasn't addressed in [32] and [33].…”

Comparative Analysis of Different Model-Based Controllers Using Active Vehicle Suspension System

“…Hence, HOSMC has all the qualities of SMC and it provides the sliding variable and its derivatives a finite time convergence [27]. Furthermore, the STA algorithm offers finite time stabilization for all the states [28].…”

Neuro Model for Passive Suspension of a Light Car

“…Generally, the suspension system has several types, they are classified as passive, semi-active, active and divers between systems [1][2][3][4]. Its physical features relate to the required energy and actuator characteristic frequencies [5]. The most common type is passive system, It uses several types of springs combined with hydraulic or pneumatic shock absorber [3,4].…”

“…Keywords: Mathematical model, light car, passive suspension, neuro model, artificial road surface quite rational for representing the real suspension system dynamics [2,8]. On most cases, a quarter car model offen uses for analysis of ride and the controller design of suspension [1,[3][4][5][6][7][8][9][10][11][12].…”