Approximation-Free Control for Vehicle Active Suspensions with Hydraulic Actuator

Yingbo Huang, Jing Na, Xing Wu, Guanbin Gao

Research output: Contribution to journalArticle (Academic Journal)peer-review

140 Citations (Scopus)


This paper presents a novel control strategy for nonlinear uncertain vehicle active suspension systems without using any function approximators (e.g. neural networks (NNs) or fuzzy logic systems (FLSs)). Unlike previous results that neglect the effect of actuator dynamics, this paper incorporates the dynamics of a hydraulic actuator that is used to create the required active suspension forces into the controller design. To address the nonlinearities of this hydraulic systems, an approximation-free control (AFC) method is introduced. In this method, the widely used NNs and FLSs are not needed. This leads to reduced computational burden and complexity, and thus it is more suited for practical application. Moreover, by introducing a prescribed performance function (PPF) and the associated error transform, the proposed controller can guarantee both the transient and steady-state suspension responses. The stability of the closed-loop system and the suspension performance requirements are rigorously proved. Finally, comparative simulations are conducted to validate the improved performance and robustness of the proposed method.

Original languageEnglish
JournalIEEE Transactions on Industrial Electronics
Early online date26 Jan 2018
Publication statusE-pub ahead of print - 26 Jan 2018


  • Active suspension control
  • Approximation-free control
  • Artificial neural networks
  • Dynamics
  • Hydraulic actuators
  • Prescribed performance
  • Steady-state
  • Suspensions
  • Transient analysis
  • Vehicle suspension systems


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