Adaptive vehicle posture and height synchronization control of active air suspension systems with multiple uncertainties

Xie

et al. 2021

Sensors

Self Cite

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.

“…Aiming to deal with the aforesaid problems, many results have been reported, such as robust

control [ 15 , 16 ], sliding mode control (SMC) [ 11 , 17 , 18 ], fuzzy logic [ 19 ], neural network-based [ 20 ], and backstepping control techniques [ 14 , 21 ]. In [ 16 ], a robust

controller for AAS systems was proposed, where the ride comfort and time domain hard constraints were considered.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Xie

et al. 2021

Sensors

Self Cite

“…The adaptive control was established in Ref. [10] with synchronization control to synchronize the height of four suspensions of the vehicle.…”

mentioning

confidence: 99%

Approximation-free control based on the bioinspired reference model for suspension systems with uncertainty and unknown nonlinearity

Hu¹,

Wen²,

Yin³

et al. 2022

Preprint

Uncertainty and unknown nonlinearity are often inevitable in the suspension systems, which were often solved using fuzzy logic system (FLS) or neural networks (NNs). However, these methods are restricted by the structural complexity of the controller and the huge computing cost. Meanwhile, the estimation error of such approximators is affected by adopted adaptive laws and learning gains. Thus, in view of the above problem, this paper proposes the approximation-free control based on the bioinspired reference model for a class of uncertain suspension systems with unknown nonlinearity. The proposed method integrates the superior vibration suppression of the bioinspired reference model and the structural advantage of the prescribed performance function (PPF) in approximation-free control. Then, the vibration suppression performance is improved, the calculation burden is relieved, and the transient performance is improved, which is analyzed theoretically in this paper. Finally, the simulation results validate the approach, and the comparisons show the advantages of the proposed control method in terms of good vibration suppression, fast convergence, and less calculation burden.

Adaptive ride height controller design for vehicle active suspension systems with uncertain sprung mass and time‐varying disturbance

Intl J Robust & Nonlinear

Xie

et al. 2022

Self Cite

In this article, we address the problem of ride height tracking control of the automotive active air suspension (AAS) system with uncertain sprung mass and external time‐varying disturbances. The proposed adaptive robust control approach guarantees that (i) the ride height converges towards, and stays within, an arbitrarily small neighborhood of the desired height, attaining uniform ultimate boundedness; (ii) the closed‐loop AAS system is (1) adaptive to uncertain sprung mass caused by the change of payload through the design of a projector‐based mass estimator; and, (2) robust to external time‐varying disturbance by developing a nonlinear disturbance observer. At last, co‐simulation (AMESim‐Matlab/Simulink) and experimental tests on a self‐fabricated quarter‐car test rig are conducted to demonstrate the effectiveness and performance of the proposed method.