Hardware acceleration of multibody simulations for real-time embedded applications

Rodríguez, Antonio J.; Pastorino, Roland; Carro-Lagoa, Angel; Janssens, Karl; Naya, Miguel Ángel

doi:10.1007/s11044-020-09738-w

Cited by 12 publications

(10 citation statements)

References 32 publications

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“…In this work, the ALI3P formulation is selected following the work in [ 9 ]. First presented in [ 30 ], this formulation is widely used in multibody applications due to its efficiency and robustness [ 16 , 31 , 32 , 33 , 34 ]. The formulation is briefly described next.…”

Section: Methodsmentioning

confidence: 99%

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Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter

Rodríguez

Sanjurjo

Pastorino

et al. 2021

Sensors

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The aim of this work is to explore the suitability of adaptive methods for state estimators based on multibody dynamics, which present severe non-linearities. The performance of a Kalman filter relies on the knowledge of the noise covariance matrices, which are difficult to obtain. This challenge can be overcome by the use of adaptive techniques. Based on an error-extended Kalman filter with force estimation (errorEKF-FE), the adaptive method known as maximum likelihood is adjusted to fulfill the multibody requirements. This new filter is called adaptive error-extended Kalman filter (AerrorEKF-FE). In order to present a general approach, the method is tested on two different mechanisms in a simulation environment. In addition, different sensor configurations are also studied. Results show that, in spite of the maneuver conditions and initial statistics, the AerrorEKF-FE provides estimations with accuracy and robustness. The AerrorEKF-FE proves that adaptive techniques can be applied to multibody-based state estimators, increasing, therefore, their fields of application.

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Section: Methodsmentioning

confidence: 99%

“…Multibody models can be computationally expensive and achieving real-time performance in practical applications is a challenge [ 16 ]. Hence, executing several models in parallel following the MMAE approach would compromise real-time performance and, thus, the viability of the solution.…”

Section: Introductionmentioning

confidence: 99%

Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter

Rodríguez

Sanjurjo

Pastorino

et al. 2021

Sensors

Self Cite

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“…Besides, if one aims to perform an embedded simulation, the hardware is often limited. In this regard, some researches have achieved to run multibody models on other kinds of platforms, such as FPGA [ 20 ] or ARM-based systems [ 21 ]. In particular, the above-mentioned symbolic approach has been proved to be a good candidate to achieve real-time computation without having to resort to simplifications within the model [ 22 ].…”

Section: State-of-the-artmentioning

confidence: 99%

Haptic Devices Based on Real-Time Dynamic Models of Multibody Systems

Docquier

Timmermans

Paul

2021

Sensors

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Multibody modeling of mechanical systems can be applied to various applications. Human-in-the-loop interfaces represent a growing research field, for which increasingly more devices include a dynamic multibody model to emulate the system physics in real-time. In this scope, reliable and highly dynamic sensors, to both validate those models and to measure in real-time the physical system behavior, have become crucial. In this paper, a multibody modeling approach in relative coordinates is proposed, based on symbolic equations of the physical system. The model is running in a ROS environment, which interacts with sensors and actuators. Two real-time applications with haptic feedback are presented: a piano key and a car simulator. In the present work, several sensors are used to characterize and validate the multibody model, but also to measure the system kinematics and dynamics within the human-in-the-loop process, and to ultimately validate the haptic device behavior. Experimental results for both developed devices confirm the interest of an embedded multibody model to enhance the haptic feedback performances. Besides, model parameters variations during the experiments illustrate the infinite possibilities that such model-based configurable haptic devices can offer.

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“…Hydraulic systems are highly nonlinear systems, which are caused, in part, by the friction model of the hydraulic cylinders. The friction model of the hydraulic cylinders can introduce numerical stiffness [38], and as a consequence, time integration of hydraulically actuated systems may become cumbersome, especially, in real-time applications [30,31,50]. Moreover, a physically incorrect friction model of the hydraulic cylinders can lead to inaccurate simulations and control errors.…”

Section: Introductionmentioning

confidence: 99%

Efficiency comparison of various friction models of a hydraulic cylinder in the framework of multibody system dynamics

2021

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Dynamic simulation of mechanical systems can be performed using a multibody system dynamics approach. The approach allows to account systems of other physical nature, such as hydraulic actuators. In such systems, the nonlinearity and numerical stiffness introduced by the friction model of the hydraulic cylinders can be an important aspect to consider in the modeling because it can lead to poor computational efficiency. This paper couples various friction models of a hydraulic cylinder with the equations of motion of a hydraulically actuated multibody system in a monolithic framework. To this end, two static friction models, the Bengisu–Akay model and Brown–McPhee model, and two dynamic friction models, the LuGre model and modified LuGre model, are considered in this work. A hydraulically actuated four-bar mechanism is exemplified as a case study. The four modeling approaches are compared based on the work cycle, friction force, energy balance, and numerical efficiency. It is concluded that the Brown–McPhee approach is numerically the most efficient approach and it is well able to describe usual friction characteristics in dynamic simulation of hydraulically actuated multibody systems.

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Hardware acceleration of multibody simulations for real-time embedded applications

Cited by 12 publications

References 32 publications

Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter

Multibody-Based Input and State Observers Using Adaptive Extended Kalman Filter

Haptic Devices Based on Real-Time Dynamic Models of Multibody Systems

Efficiency comparison of various friction models of a hydraulic cylinder in the framework of multibody system dynamics

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