Development of a Semi-Active Suspension Controller Using Adaptive-Fuzzy with Kalman Filter

Kaldas, Mina M.S.; Çalışkan, Kemal; Henze, Roman; Küçükay, Ferit

doi:10.4271/2011-01-0431

Cited by 21 publications

(12 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The controller provides the set of gains over different operating conditions and is based on the adapted estimates of vehicle parameters and states, and the adapted weighting parameters. Kaldas et al [4] developed a semi-active suspension system controller using an adaptive Fuzzy Logic algorithm together with a Kalman Filter for bounce velocity estimation. The benefit of using adaptive control with Fuzzy Logic to maintain the optimum performance over a wide range of road inputs is enhanced by the accuracy of the Kalman Filter in estimating the controller inputs.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Preview Enhanced Rule-Optimized Fuzzy Logic Damper Controller

Kaldas

Çalışkan

Henze

et al. 2014

SAE Int. J. Passeng. Cars - Mech. Syst.

Self Cite

View full text Add to dashboard Cite

New developments in road profile measurement systems and in semi-active damper technology promote the application of preview control strategies to vehicle suspension systems. This paper details a new semi-active suspension control approach in which a rule-optimized Fuzzy Logic controller is enhanced through preview capability. The proposed approach utilizes an optimization process for obtaining the optimum membership functions and the optimum rule-base of the preview enhanced Fuzzy Logic controller. The preview enhanced Fuzzy Logic controller uses the feedforward road input information and the feedback vehicle state information as the controller inputs. An eleven degree of freedom full vehicle model, which is validated through laboratory tests performed on a hydraulic four-poster shaker, is used for the controller synthesis. The cost function including both ride comfort and road holding performance of the full vehicle is minimized through a discrete optimization process utilizing Genetic Algorithm (GA). The preview distance is also considered as a design parameter during the optimization process. The performance of the preview enhanced rule-optimized Fuzzy Logic controller is evaluated by using a measured stochastic road profile as vehicle model input. The results demonstrate the potential of the preview enhanced controller in improving all aspects of system performance compared to the ruleoptimized Fuzzy Logic controller without preview.

show abstract

Section: Introductionmentioning

confidence: 99%

“…However, this is achieved at the expense of reduced ride comfort. The objective that attracts the current research studies is to improve the performance of semi-active control systems through different control approaches [1,2,3,4,5].…”

Section: Introductionmentioning

confidence: 99%

Preview Enhanced Rule-Optimized Fuzzy Logic Damper Controller

Kaldas

Çalışkan

Henze

et al. 2014

SAE Int. J. Passeng. Cars - Mech. Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…z s and z u denote the vertical displacements of the vehicle body and tire, respectively. 3 represents the tire deformation, and u z z 4 represents the vertical velocity of the unsprung mass. …”

Section: The 1/4 Vehicle Suspension Modelsmentioning

confidence: 99%

“…Currently, traditional suspension mathematical models are prevalent in analyzing and controlling the ride quality of vehicles [1][2][3][4], as shown in Fig. 1 [5].…”

Section: Introductionmentioning

confidence: 99%

Ride responses of macpherson suspension systems

Chiu

2017

MATEC Web Conf.

View full text Add to dashboard Cite

Abstract. The main purpose of this study is to obtain more correct vehicle ride responses by using a nonlinear ride model considering the effect of Macpherson suspension geometry. Traditional ride model applied to analysis and controller design uses a two degree of freedom linear model, which includes sprung mass and unsprung mass and a spring and a damper vertically connect them. In fact, suspension components do not vertically position above the tire. The motions of body and tire are not going straight up and down. Therefore, the analysis results obtained by the simple model are often different from the experimental values of the actual vehicle. Because of the difference between simple model and actual vehicle, the control strategy almost cannot apply to actual vehicle. In order to understand the effect of suspension geometry on the vehicle ride responses and design a more practical control strategy, a nonlinear model including the geometric parameters of the suspension is constructed in this study. To estimate the initial equilibrium position of the suspension assembly under load, the static equilibrium analysis and mechanism motion analysis are synchronous implemented at the same time. The nonlinear model describes not only the relative position and velocity but also the force transmission between body and tire. Furthermore, by linearize this nonlinear model the development of control strategy for subsequent (semi) active suspension system could be expected.

show abstract

“…The results showed that control is better than passive suspension, but the choice of weighting coefficients mainly depends on the designer's experience, lacking theoretical basis; [4] used robust control, however not only computing increase but controller is conservative and real-time is bad; Fuzzy control does not depend on the precise mathematical model and has advantages in dealing with non-linear problems. With characteristic of self-tuning adaptive control, it can get very good control effect [5].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Control for Aircraft Tractor’s Magneto Rheological Semi-active Suspension

Li¹,

Cheng²,

Qing³

2015

Advances in Computer Science Research

View full text Add to dashboard Cite

Abstract. In order to improve aircraft tractor's ride comfort and traction friendly, this paper takes the MR semi-active suspension as the research object and establishes half body model. Through fitting, this paper obtained the magnetic rheological damper's damping expression, designed a magnetic rheological damper with low pressure nitrogen compensation structure. The fuzzy control is used to study suspension's performance. Aiming for reducing body acceleration, this paper introduced the thought of adaptive control to adjust the domain constantly. The simulation results shows that the adaptive fuzzy control can improve aircraft tractor's suspension function obviously with small amount of calculation, good real-time performance. This algorithm has self-adaptability to the changes in the suspension parameters, easy to meet the control system's requirement and realize in engineering.

show abstract

Development of a Semi-Active Suspension Controller Using Adaptive-Fuzzy with Kalman Filter

Cited by 21 publications

References 6 publications

Preview Enhanced Rule-Optimized Fuzzy Logic Damper Controller

Preview Enhanced Rule-Optimized Fuzzy Logic Damper Controller

Ride responses of macpherson suspension systems

Adaptive Fuzzy Control for Aircraft Tractor’s Magneto Rheological Semi-active Suspension

Contact Info

Product

Resources

About