Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 51, Issue 4, Pages 1743-1755Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2020.2972322
Keywords
Suspensions; Biological system modeling; Adaptation models; Fuzzy logic; Adaptive systems; Stability analysis; Convergence; Active suspension systems; bioinspired dynamics; dead zone; finite-time convergence; fuzzy-logic systems (FLSs); PD-SMC method; saturation
Categories
Funding
- General Research Fund of HK Research Grants Council [15206717]
- Strategic Research Fund of Research Institute of Sustainable Urban Development of the Hong Kong Polytechnic University
- Key Research and Development (Special Public-Funded Projects) of Shandong Province [2019GGX104058]
- National Natural Science Foundation for Young Scientists of China [61903155]
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An adaptive fuzzy SMC method based on a bioinspired reference model is proposed to address the limitations of existing control strategies in active suspension systems, providing finite-time convergence and energy-saving performance simultaneously. This method effectively utilizes nonlinear stiffness and damping properties to achieve superior vibration suppression performance with less energy consumption and improved ride comfort.
Active suspension systems are widely used in vehicles to improve ride comfort and handling performance. However, existing control strategies may be limited by various factors, including insufficient consideration of different operation conditions, such as changing in vehicle mass, defects in strategy design leading to incapability for guaranteeing finite-time stability, lack of considering input effects of dead zone and saturation, excessive energy cost, etc. Importantly, very few results considered the energy-saving performance of active suspension systems although a well-perceived issue in practice. An adaptive fuzzy SMC method based on a bioinspired reference model is established in this article, which is to purposely address these problems and be able to provide finite-time convergence and energy-saving performance simultaneously. The proposed control method effectively utilizes beneficial nonlinear stiffness and nonlinear damping properties that the bioinspired reference model could provide. Therefore, superior vibration suppression performance with less energy consumption and improved ride comfort can all be obtained readily. By using a fuzzy-logic system (FLS), the proposed method is beneficial in compensating for system parameter uncertainties, external disturbances, input dead zones, and saturations. Furthermore, based on the adaptive PD-SMC method, the tracking errors can converge to zeros in finite time. The stability of the equilibrium point of all the states in active suspension systems is theoretically proven by Lyapunov techniques. Finally, simulation results are provided to verify the correctness and effectiveness of the proposed control scheme.
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