Adaptive Sliding-Mode Control for Nonlinear Active Suspension Vehicle Systems Using T–S Fuzzy Approach

By Hongyi Li, Jinyong Yu, Chris Hilton, Honghai Liu. IEEE transactions on industrial electronics (1982. Print), 2013

712 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Dissipativity-Based Fuzzy Integral Sliding Mode Control of Continuous-Time T-S Fuzzy Systems (2018, methodology): “Thus, the FISMC methods proposed in [31] and [33] cannot be implemented.”
Dynamic Surface Control Using Neural Networks for a Class of Uncertain Nonlinear Systems With Input Saturation (2015, methodology): “In [20], an adaptive sliding-mode control was proposed for nonlinear active suspension vehicle systems using Takagi–Sugeno fuzzy approach.”
Adaptive Sliding Mode Control for Interval Type-2 Fuzzy Systems (2016, methodology): “In our future work, we will attempt to use the proposed control method in this paper to control the uncertain nonlinear vehicle suspension systems [64]–[68].”
A Review on Basic Data-Driven Approaches for Industrial Process Monitoring (2014, methodology): “Based on the physical and mathematical knowledge of the industrial processes, the wellestablished model-based techniques have been successfully applied on plenty of processes for industrial electronics [1]– [8], automatic control systems [9]–[14], etc.”