Bond Graph Modeling Of An Exoskeleton Actuator

Barjuei, Erfan Shojaei; Toxiri, Stefano; Medrano-Cerda, Gustavo A.; Caldwell, Darwin G.

doi:10.1109/ceec.2018.8674199

Cited by 13 publications

(11 citation statements)

References 23 publications

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“…Friction and damping parameters have a fundamental role in the system dynamic and characterizing these parameters improves the model accuracy.. The value of b f was estimated from the experimental tests from the work in [7] using the same actuator and it is given by b f = 0.48 × 10 −3 [N s rad −1 ].…”

Section: System Identificationmentioning

confidence: 99%

“…The simulation results from the block diagram and bond graph models are presented and discussed in this section. While the block diagram dynamic model of the exoskeleton robotic system is simulated via MATLAB software, the simulation of the bond graph modeling is carried out via 20-sim software [7]. The results from both simulation softwares are plotted with MATLAB.…”

Section: Comparison Between Block Diagram and Bond Graph Modelsmentioning

confidence: 99%

“…Finally, an excellent agreement between the block diagram model developed in MATLAB and bond graph model developed in 20-sim can be inferred from both Figures 10 and 11. It should be pointed out that using different numerical differential equation solvers with diverse configurations by MATALB and 20-sim is the main reason of the small errors between the simulation results [7].…”

Section: Comparison Between Block Diagram and Bond Graph Modelsmentioning

confidence: 99%

“…With the intention of applying control schemes to exoskeletons and improving the system performance, a comprehensive dynamic model to represent the behaviour of this robotic platform is needed [7]. Simple dynamic models for exoskeleton robotic platforms such as the biomechanical model in 2D dimensional space [8], the Lagrangian dynamics model, specialized with a serial rigid links chain [9] and the mathematical model based on user's movements [10] have been presented so far.…”

Section: Introductionmentioning

confidence: 99%

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Bond Graph Modeling and Kalman Filter Observer Design for an Industrial Back-Support Exoskeleton

Barjuei

Caldwell

Ortiz

2020

Designs

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This paper presents a versatile approach to the synthesis and design of a bond graph model and a Kalman filter observer for an industrial back-support exoskeleton. Actually, the main purpose of developing a bond graph model is to investigate and understand better the system dynamics. On the other hand, the design of the Kalman observer always should be based on a model providing an adequate description of the system dynamics; however, when back-support exoskeletons are considered, the synthesis of a state observer becomes very challenging, since only nonlinear models may be adopted to reproduce the system dynamic response with adequate accuracy. The dynamic modeling of the exoskeleton robotic platform, used in this work, comprises an electrical brushless DC motor, gearbox transmission, torque sensor and human trunk (biomechanical model). On this basis, a block diagram model of the dynamic system is presented and an experimental test has been carried out for identifying the system parameters accordingly. Both the block diagram and bond graph dynamic models are simulated via MATLAB and 20-sim software (bond graph simulation software) respectively. Furthermore, the possibility of employing the Kalman filter observer together with a suitable linear model is investigated. Subsequently, the performance of the proposed Kalman observer is evaluated in a lifting task scenario with the use of a linear quadratic regulator (LQR) controller with double integral action. Finally, the most important simulation results are presented and discussed.

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Section: System Identificationmentioning

confidence: 99%

Section: Comparison Between Block Diagram and Bond Graph Modelsmentioning

confidence: 99%

Section: Comparison Between Block Diagram and Bond Graph Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bond Graph Modeling and Kalman Filter Observer Design for an Industrial Back-Support Exoskeleton

Barjuei

Caldwell

Ortiz

2020

Designs

Self Cite

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“…However, these mechanisms still lack adjustable size, position, and orientation to accommodate wearers of different body profiles. Barjuei et al 25 showed the advantages of bond graph (BG) technique to model the exoskeleton's actuator that consists of brushless DC motor to have better insights of the system dynamics. Flynn 26 performed the synthesis of lower limb exoskeleton for clinical rehabilitation using BG modelling technique.…”

Section: Introductionmentioning

confidence: 99%

Comparative study of knee joint torque estimations for linear and rotary actuators using bond graph approach for stand–sit–stand motions

Jain

Bera

Rafique

et al. 2020

International Journal of Advanced Robotic Systems

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Stand–sit–stand (STS) motions are the most frequently performed activities of everyday life and require extensive movement of knee joint. People suffering from knee joint disorders face difficulties in performing this motion. The compact knee exoskeleton (KE) has proven to be a viable, less complex, and cheaper alternative to the available entire lower-, upper-, and full-body exoskeletons. With growing number of technical glitches and finite battery life problems, there exist risks of sudden failure of the actuator of KE that could be detrimental for the vulnerable users. To overcome this problem, there is a need to accommodate a backup actuator in KE which can continue providing assistance during movement if the primary actuator ceases to function. This article provides a performance comparison of a four-bar mechanism-driven KE that can accommodate both the linear and the rotary actuators. The modelling and simulation of the system are performed using the bond graph (BG) technique. The results successfully showed that both actuators offered desired ranges of motions needed for STS motion. Furthermore, the knee joint torques developed by the linear and rotary actuators were found to be 40 Nm and 57 Nm, respectively, which corresponds to 60% and 85% of the total torque required by the knee joint to perform STS motions, thereby reducing the user effort to 40% and 15%, respectively. Thus, both actuators are self-capable to provide necessary assistance at the knee joint even if the primary actuator ceases to work due to a sudden fault, the secondary actuator will provide the required rotation of the thigh link and will continue to deliver the assistive torque. The article also effectively shows the application of BG approach to model the multidisciplinary systems like KE as it conveniently models the system containing various elements in different energy domains.

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