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Adaptive robust control methodology for active roll control system with uncertainty

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Abstract

The active roll control system (ARCS) can impose anti-roll moment quickly to prevent the vehicle rolling when the vehicle generates the roll tendency and effectively enhance the vehicle dynamic performance without sacrificing the ride comfort. In the dynamic model of the ARCS, the sprung mass of the vehicle is considered to be the uncertain parameter, which is (possibly) fast-varying. However, what we know about the uncertainty is just that it is bounded. Furthermore, the bound is unknown. The target roll angle is regarded as the constraint when the vehicle equipped with the ARCS is running under a given case. Taking the parameter uncertainty and possible initial condition deviation from the constraint into account, an adaptive robust control scheme based on the Udwadia and Kalaba’s approach is proposed to drive the ARCS to follow the pre-specified constraint approximately. The adaptive law is of leakage type which can adjust itself based on the tracking error. Numerical simulation shows that by using the adaptive robust control scheme, the error between the actual roll angle and the desired roll angle converges to zero quickly in 0.3 s from initial error 0.287 deg, and the final error is of the order of \(10^{-7}\). Thus, the control design renders the ARCS practically stable and achieves constraints following maneuvering.

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Acknowledgements

The research is supported by the China Postdoctoral Science Foundation (No. 2016M590563), the National Natural Science Foundation of China (No. 51505116), and the Fundamental Research Funds for the Central Universities (No. JZ2016HGTB0716).

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Correspondence to Hao Sun.

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Sun, H., Chen, YH. & Zhao, H. Adaptive robust control methodology for active roll control system with uncertainty. Nonlinear Dyn 92, 359–371 (2018). https://doi.org/10.1007/s11071-018-4060-1

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