A sliding mode control algorithm based on improved super-twisting and its application to quadrotors

Zhao, Jing; Xie, Zuoyu; Xiao, Min; Xu, Fengyu; Gao, Zhifeng

doi:10.1080/23307706.2022.2094841

Cited by 4 publications

(1 citation statement)

References 16 publications

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“…32 Then, a quarter-dynamic model that considers the influence of the actuator will have five state variables. 33 According to Zhao et al, 34 the sliding surface is an important component of the SMC controller. The controlled object can travel around the sliding surface in order to reach a steady state.…”

Section: Introductionmentioning

confidence: 99%

Design a new control algorithm AFSP (Adaptive Fuzzy – Sliding Mode – Proportional – Integral) for automotive suspension system

Nguyen

2023

Advances in Mechanical Engineering

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When a vehicle is driving, the most significant source of oscillations is the irregularities in the surface of the road. An active suspension is utilized to enhance the vehicle’s stability and ride comfort. In this work, the dynamic model with multi variables is considered to simulate vehicle oscillations based on four excitation cases from the road surface. In addition, this research also established the AFSP complex control solution for an active suspension system. This is a completely novel algorithm with many outstanding advantages. The final control signal of the system is synthesized from the signals of the linear controller PI (Proportional – Integral) and the nonlinear controller SMC (Sliding Mode Control). The controller’s parameters will change continuously depending on the established fuzzy rule. According to simulation outcomes, the vehicle body displacement and acceleration dramatically declined when the AFSP algorithm directed an active suspension. The values of acceleration and displacement do not exceed 80% and 20%, compared to the scenario in which the vehicle just utilized the typical passive suspension system. Besides, a phenomenon of “chattering” also does not appear when combining the controllers. Overall, the efficiency of this algorithm is high. This algorithm can be applied to more complex models.

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Section: Introductionmentioning

confidence: 99%