Development of adaptive modeling techniques for non-linear hysteretic systems

Smyth, Andrew W.; Masri, Sami F.; Kosmatopoulos, Elias B.; Chassiakos, Anastasios; Caughey, T. K.

doi:10.1016/s0020-7462(02)00031-8

Cited by 158 publications

(73 citation statements)

References 42 publications

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“…Using Case 1 and 2, asymmetric hysteretic loops (with respect to the origin) are seen in Figure 2, this behavior can also be offered in [17]. This hysteretic behavior may be attributed to materials that have an initial residual strain, like a building structural frame.…”

Section: Remark 1-function G(ẋ G(z)))) Is Positively Homogeneous Wimentioning

confidence: 81%

“…We set β − λ > 0, which corresponds to a special case of physical hysteretic behavior [3]. These parameters control the shape and size of the hysteresis loop [17]. So, the Bouc-Wen model parameters are α, k, D, A, β, n and λ.…”

Section: A Class Of Passive Hysteretic Modelsmentioning

confidence: 99%

“…For this purpose, consider the system (1)- (2) with [17]. The following cases are studied (hereafter we omit to specify time dependency to simplify writing):…”

Section: Remark 1-function G(ẋ G(z)))) Is Positively Homogeneous Wimentioning

confidence: 99%

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A velocity based active vibration control of hysteretic systems

Pujol

Acho

Pozo

et al. 2011

Mechanical Systems and Signal Processing

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Hysteresis is a property of systems that do not instantly follow the forces applied to them, but react slowly, or do not return completely to their original state. A velocity based active vibration control, along with a special class of hysteretic models using passive functions are presented in this paper. This hysteretic model is based on a modification of the Bouc–Wen model, where a nonlinear term is replaced by a passive function. The proposed class retains the rate-independence property of the original Bouc–Wen model, and it is able to reproduce several kinds of hysteretic loops that cannot be reproduced with the original Bouc–Wen model. Using this class of hysteretic models, a chattering velocity-based active vibration control scheme is developed to mitigate seismic perturbations on hysteretic base-isolated structures. Our hysteretic model is used because of its simplicity in proving the stability of the closed-loop system; i.e., a controller is designed using the proposed model, and its performance is tested on the original hysteretic system, modeled with Bouc–Wen. Numerical experiments show the robustness and efficiency of the proposed control algorithm.Peer ReviewedPostprint (author's final draft

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Section: Remark 1-function G(ẋ G(z)))) Is Positively Homogeneous Wimentioning

confidence: 81%

Section: A Class Of Passive Hysteretic Modelsmentioning

confidence: 99%

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A velocity based active vibration control of hysteretic systems

Pujol

Acho

Pozo

et al. 2011

Mechanical Systems and Signal Processing

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“…By selecting different model parameters, the hysteresis curve of various shapes can be simulated, including viscous stage and slip stage (Smyth et al, 2002). This method has the advantages of few parameters, simple format and convenient application, which is widely used in the modelling and control of hysteresis structure in engineering field (Ismail et al, 2009).…”

Section: Hysteresis Model Of the Notched Continuum Manipulator Based mentioning

confidence: 99%

Hysteresis analysis of a notched continuum manipulator driven by tendon

Yang

Dong

et al. 2018

Mech. Sci.

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Abstract. Continuum manipulators are widely used in minimally invasive surgical robot systems (MISRS) because of their flexibility and compliance, while their modelling and control are relatively difficult and complex. This paper proposes an improved hysteresis model of a notched continuum manipulator based on the classical Bouc-Wen model, which can reduce errors and increase the accuracy of the kinematic-mechanics coupled model. Then parameters are identified by the mean of genetic algorithm (GA). Hysteresis phenomenon of the mentioned manipulator is actually caused by many factors such as the hysteresis property of Hyperelastic Nitinol Alloy (HNA), the elastic deformation of tendon and the friction between the tendon and the tube. The results of both static and dynamic experiments show that the introduced hysteresis model can eliminate the positional difference between forward and reverse bending processes, and thus improve the forecast precision of deformation during motion. This model can also be used to compensate modelling errors caused by hysteresis of other similar systems.

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“…The Kalman filter removes noise by assuming a pre-defined model of a system [15]. Therefore, the Kalman filter model must be meaningful in the determination of accurate vehicle position.…”

Section: Accuracy In Gps Coordinatesmentioning

confidence: 99%

Modeling and Simulation of GPS Positioning and Iterative Vehicle Motion Using Kalman Filter in Vehicle Tracking System

Hamidu¹

2017

COM

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Abstract:This research is about modelling and simulation of the RFID based Transport Highway Integrated System (THIS) using the iterative motion of the vehicle plying the highway and the application of Kalman filter to aid in effective positioning after signal transmit. This approach will help to identify drivers, vehicles and track location appropriately. The design when able to be implemented with the use of Kalman filter to filter out the noise there will be much accuracy in the vehicle position prediction on the high-way. According to the graphs obtained through Kalman algorithm it was realized that: The noise level was appreciative as compared with the actual signal from the vehicle. If the vehicle model is created based on true situation our estimated state will be close to the true value. Even when measurements are very noisy that is a 20% error will only produce a 5% inaccuracy. The position prediction of a vehicle on the high-way is better as the Gaussian white noise is eliminated, tracking to know the exact location via GPS coordinate will reduce the error margin. If you have a badly defined model, you will not get a good estimate. But you can relax your model by increasing your estimated error. This will let the Kalman filter rely more on the measurement values, but still allow some noise removal.

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Development of adaptive modeling techniques for non-linear hysteretic systems

Cited by 158 publications

References 42 publications

A velocity based active vibration control of hysteretic systems

A velocity based active vibration control of hysteretic systems

Hysteresis analysis of a notched continuum manipulator driven by tendon

Modeling and Simulation of GPS Positioning and Iterative Vehicle Motion Using Kalman Filter in Vehicle Tracking System

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