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. 2021 Feb 23;21(4):1539.
doi: 10.3390/s21041539.

Nonlinear Ride Height Control of Active Air Suspension System with Output Constraints and Time-Varying Disturbances

Affiliations

Nonlinear Ride Height Control of Active Air Suspension System with Output Constraints and Time-Varying Disturbances

Rongchen Zhao et al. Sensors (Basel). .

Abstract

This paper addresses the problem of nonlinear height tracking control of an automobile active air suspension with the output state constraints and time-varying disturbances. The proposed control strategy guarantees that the ride height stays within a predefined range, and converges closely to an arbitrarily small neighborhood of the desired height, ensuring uniform ultimate boundedness. The designed nonlinear observer is able to compensate for the time-varying disturbances caused by external random road excitation and perturbations, achieving robust performance. Simulation results obtained from the co-simulation (AMESim-Matlab/Simulink) are given and analyzed, demonstrating the efficiency of the proposed control methodology.

Keywords: active air suspension; disturbance observer design; nonlinear height control; output constraints; random road excitation.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Schematic diagram of quarter vehicle with active air suspension (AAS).
Figure 2
Figure 2
Co-simulation block diagram.
Figure 3
Figure 3
Height tracking performance of quarter vehicle with AAS in co-simulation.
Figure 4
Figure 4
Height tracking error of quarter vehicle with AAS in co-simulation, where |z1| always stays within its corresponding bound.
Figure 5
Figure 5
Height comparison of quarter vehicle with AAS in co-simulation.
Figure 6
Figure 6
Error comparison of quarter vehicle with AAS in co-simulation, where |z1| exceeds its allowable maximum value.
Figure 7
Figure 7
Disturbance estimation of quarter vehicle with AAS in co-simulation.
Figure 8
Figure 8
Tracking height and error of quarter vehicle with measurement noise in co-simulation.
Figure 9
Figure 9
Height comparison of quarter vehicle with AAS in co-simulation.
Figure 10
Figure 10
Error comparison of quarter vehicle with AAS in co-simulation.
Figure 11
Figure 11
Tracking performance comparison of quarter vehicle with hybrid model predictive controller (HMPC) presented in [7].

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