Enhanced fuzzy sliding mode controller for active suspension systems

Lin, Jeen; Lian, Ruey-Jing; Huang, Chung-Neng; Sie, Wun-Tong

doi:10.1016/j.mechatronics.2009.03.009

Cited by 82 publications

(53 citation statements)

References 23 publications

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“…Besides, the unknown influence of environmental conditions on the system can also affect negatively on control systems. To face with these, sliding mode control technique (SMCT), fuzzy logic (FL), and artificial neural networks (ANN) together with solutions for noise compensation have been widely developed [9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26].…”

Section: Introductionmentioning

confidence: 99%

“…In this tendency, optimization methods such as the Evolutionary Algorithm (EA), Differential Evolution (DE) [31,33] or the algorithm rank-DE [34] could be employed to improve the system performance. Such advantages of the FSMC model have been effectively exploited in many fields, including suspension systems [15,16,20]. FSMC owns the advantages, this, however, may increase the time delay due to the high calculating cost in some cases [23].…”

Section: Introductionmentioning

confidence: 99%

“…Being viewed as a becoming solution for improving calculating cost, this however could not fully exploit the varying tendency of the sling surface to adjust appropriately the control law. In [20], a FSMC for an active suspension system was presented. In this, the sliding surface and its change were employed as input variables of a traditional fuzzy controller to update the control law.…”

Section: Introductionmentioning

confidence: 99%

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Designing Optimal Fuzzy Controller for MRD-Based Train-Car Suspension Systems

Nguyen¹

2018

JCC

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Abstract. Random time-varying chassis mass, which consists of passenger and cargo mass as well as the normalized wind force, causes reducing the effectiveness of smart vehicle suspensions. In order to deal with this, we develop a novel fuzzy-based dynamic inversion controller (FDIC) for the control of a train-car suspension system using a magneto-rheological damper (MRD) or MRDs. The FDIC is constituted of three main parts: i) an inverse MRD model (ANFIS-I-MRD) via a measured data set and an adaptive neuro-fuzzy inference system (ANFIS), ii) a fuzzy-based sliding mode controller (FSMC) and iii) a disturbance and uncertainty observer (DUO). The FSMC is designed via the two following steps. The first one is to establish and optimize parameters of a sliding mode controller (SMC). The next is to design a fuzzy logic system to expand the ability of the SMC to face with the larger ranges of the load variation. The DUO is used to compensate for disturbance and uncertainty. By using the ANFIS-I-MRD and the control force estimated by the FDIC, current for the MRD at each time for stamping out chassis vibration is specified. The stability of the FDIC is analyzed via Lyapunov stability theory. Surveys have shown that the FDIC could provide the improved control competence to reduce unwanted vibrations in an enlarged range of the varying chassis load.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Designing Optimal Fuzzy Controller for MRD-Based Train-Car Suspension Systems

Nguyen¹

2018

JCC

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“…Yoshimura et al [17] used SMC with linear quadratic control. Fuzzy sliding mode was proposed by Jeen et al [18]. Chen and Haung [19] used function approximation based adaptive SMC with fuzzy compensation for active suspension in which Fuzzy scheme is used to compensate for the model approximation error.…”

Section: Introductionmentioning

confidence: 99%

Sliding mode control of active suspension systems using a disturbance observer

Deshpande¹,

Bhaskara²,

Phadke

2012

2012 12th International Workshop on Variable Structure Systems

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In this paper a novel active suspension scheme that combines sliding mode control with a disturbance observer is proposed for a quarter car model. The disturbance observer estimates the uncertainties in the system and the unknown road disturbance acting on the unsprung mass. Two control strategies to compensate for the uncertainties and the road disturbance in order to improve the ride comfort are proposed. The stability of the suspension system and the disturbance observer is proved. The efficacy of the method is illustrated by simulation for a vehicle suspension system.

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“…In the passive suspension, trade-offs between the three performance criteria of ride comfort, suspension deflections, and road safety are necessary because of physical performance limitations [1]. Many active suspension control systems, such as active suspension [2][3][4], semi-active suspension [5][6][7], air suspension [8,9], active roll control (ARC) [10][11][12], and active body control (ABC) [13,14] have been researched and developed in order to overcome performance limitations and to improve simultaneously the riding performance, handling performance, and vehicle stability. Among the aforementioned control systems, the active suspension system can provide superior performance but is complex and expensive [15].…”

Section: Introductionmentioning

confidence: 99%

Sensor fault detection and isolation algorithm for a continuous damping control system

Kim

Lee

2011

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents an analytical sensor fault-detection and isolation algorithm for the vertical accelerometers of a continuous damping control (CDC) system, which are essential but vulnerable components in the CDC system. Because the sensor configuration of the target CDC system does not provide sufficient redundancy for fault diagnosis, two different vehicle suspension models, a modified full car model and a roll-and-pitch plane model, are derived and combined to establish analytical redundancy. Parity equations for the vertical motion of a sprung mass are derived using the combined model and applied in order to detect faults of the vertical accelerometers. In order to isolate the faults properly in practical situations, this paper proposes a fault isolation algorithm which calculates estimates of the vertical acceleration at the centre of gravity of the sprung mass using vertical acceleration signals and compares the residuals of these estimates. This paper also provides a detailed analysis regarding the detectability and isolability of vertical accelerometer faults. An adaptive threshold method is proposed to improve the performance of the suggested fault-detection and isolation algorithm. Simulation and test results demonstrate the feasibility and effectiveness of the proposed algorithm.

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Enhanced fuzzy sliding mode controller for active suspension systems

Cited by 82 publications

References 23 publications

Designing Optimal Fuzzy Controller for MRD-Based Train-Car Suspension Systems

Designing Optimal Fuzzy Controller for MRD-Based Train-Car Suspension Systems

Sliding mode control of active suspension systems using a disturbance observer

Sensor fault detection and isolation algorithm for a continuous damping control system

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