Experimental validation of a new adaptive control approach for a hybrid suspension system

Koch, Guido; Spirk, Sebastian; Pellegrini, Enrico; Pletschen, Nils; Lohmann, Boris

doi:10.1109/acc.2011.5991450

Cited by 13 publications

(17 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…and u hy (t) = 0 m = const., or for an actively controlled setting. In the controlled case, the reference-model based control concept presented in Koch et al (2011) is employed. The approach solely relies on measurable quantities and directly provides separate control inputs u cvd (t) and u hy (t).…”

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

“…While the damper's valve current is available as a measurement and thus the dynamics of the electrical domain are inherently included, the force rise dynamics of the damper are not. If approximated by a first order lag element a mechanical time constant T mech ≈ 10 msec results to account for the hydraulic properties of the damper, see Koch et al (2011).…”

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

“…In this work, we address the so-called hybrid suspension configuration that has been studied e. g. in Koch et al (2011) and Pletschen et al (2013). This set-up consists of a slow-active spring mount adjustment, i. e. an actuator with a bandwidth of up to 5 Hz in series to the primary spring, in combination with a continuously variable damper, see Fig.…”

Section: Vehicle Suspension Modelmentioning

confidence: 99%

“…1 (left). For accurate simulation and control input calculation, the parameters and major nonlinear effects have been identified at the test rig and are taken into account, see Koch et al (2011). Nonlinearities within the force transfer between chassis and wheel mass result from…”

Section: Quarter-car Test Rig With Hybrid Suspension Strutmentioning

confidence: 99%

See 3 more Smart Citations

Nonlinear State Estimation in Suspension Control Based on Takagi-Sugeno Model

Pletschen

Badur

2014

IFAC Proceedings Volumes

Self Cite

View full text Add to dashboard Cite

We present a new nonlinear state estimation approach based on Kalman filter theory and Takagi-Sugeno (TS) modeling for an active vehicle suspension application in this paper. The nonlinear state equations of a so-called hybrid suspension configuration, which result from nonlinear spring and damping characteristics, are exactly represented by means of a continuoustime TS system, i. e. a convex combination of local linear state space models. We derive observer gain matrices for each linear subsystem on the basis of standard Kalman filter theory, before we construct the global observer for the overall nonlinear system. Convergence of the global observer is ensured in terms of linear matrix inequality conditions. We then study the estimation performance of the TS Kalman filter in simulations and experiments on a hybrid quarter-car test rig using a measured road profile as disturbance input. The approach achieves a high estimation accuracy of well above 90 % in the simulation and 70 − 90 % in the experiments.

show abstract

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

Section: Simulation and Experimental Resultsmentioning

confidence: 99%

Section: Vehicle Suspension Modelmentioning

confidence: 99%

Section: Quarter-car Test Rig With Hybrid Suspension Strutmentioning

confidence: 99%

See 2 more Smart Citations

Nonlinear State Estimation in Suspension Control Based on Takagi-Sugeno Model

Pletschen

Badur

2014

IFAC Proceedings Volumes

Self Cite

View full text Add to dashboard Cite

show abstract

“…1 (le.). For accurate simulation results and control input calculation, the major nonlinear effects such as a progressive spring characteristic, degressive force-velocity characteristics of the semi-active damper with an asymmetric behavior in the compression and tension direction and the frequency-dependent characteristics of the tire have been identified at the test rig and are taken into account, see Koch et al (2011b). In order to complete the realistic setup, the measurement signals used for suspension control are…”

Section: Suspension Modelmentioning

confidence: 99%

Frequency-Selective Adaptive Control of a Hybrid Suspension System

Pletschen

Spirk

Lohmann

2013

IFAC Proceedings Volumes

Self Cite

View full text Add to dashboard Cite

This paper deals with a frequency-selective reference model that is used within an adaptive control structure for mechatronic vehicle suspensions. Based on a hybrid actuator configuration which consists of a slow-active actuator and a semi-active damper, the basic idea of the control approach is to emulate the dynamic behavior of a passive, but time-variant reference suspension being optimally attuned for the current driving state. The new reference incorporates the limited bandwidth of the active device in the design step and is also able to address the divergent damping demand of sprung and unsprung mass of modern vehicles. An additional potential of the resulting frequency-selective reference model of up to 25 % in comfort is revealed in comparison to the original reference without frequency-dependent properties. However, as suggested by a comparative study in terms of simulation results of a quarter-car setting based on real series suspension components this potential depends heavily on the restrictions that are imposed by the available damper characteristics.

show abstract

Wheel Load Oriented Control of Semi-Active and Active Suspension Systems Using Pre-Located Road Sampling

Spirk

Henning

2012

Lecture Notes in Electrical Engineering

View full text Add to dashboard Cite

Experimental validation of a new adaptive control approach for a hybrid suspension system

Cited by 13 publications

References 15 publications

Nonlinear State Estimation in Suspension Control Based on Takagi-Sugeno Model

Nonlinear State Estimation in Suspension Control Based on Takagi-Sugeno Model

Frequency-Selective Adaptive Control of a Hybrid Suspension System

Wheel Load Oriented Control of Semi-Active and Active Suspension Systems Using Pre-Located Road Sampling

Contact Info

Product

Resources

About