Experimental Estimation of a Second Order, Double Inverted Pendulum Parameters for the study of Human Balancing

Cerda-Lugo, Angel; González, Alejandro H.; Cárdenas, Antonio; Piovesan, Davide

doi:10.1109/embc.2019.8857611

Cited by 6 publications

(1 citation statement)

References 12 publications

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“…It displays a perfect model of nonlinear and chaotic movements. Unlike the previous system, the simple pendulum is not as sophisticated and advanced as the double pendulum although its simple structure and instability are highly utilized for experimental research [6][7][8]. A double pendulum or the underactuated system has more joints than actuators, and its control is a subject of great interest for researchers because of its high applicability in robotics.…”

Section: Introductionmentioning

confidence: 99%

T-S Fuzzy System Controller for Stabilizing the Double Inverted Pendulum

Elkinany

Alfidi

Chaibi

et al. 2020

Advances in Fuzzy Systems

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This article provides a representation of the double inverted pendulum system that is shaped and regulated in response to torque application at the top rather than the bottom of the pendulum, given that most researchers have controlled the double inverted pendulum based on the lower part or the base. To achieve this objective, we designed a dynamic Lagrangian conceptualization of the double inverted pendulum and a state feedback representation based on the simple convex polytypic transformation. Finally, we used the fuzzy state feedback approach to linearize the mathematical nonlinear model and to develop a fuzzy controller H ∞ , given its great ability to simplify nonlinear systems in order to reduce the error rate and to increase precision. In our virtual conceptualization of the inverted pendulum, we used MATLAB software to simulate the movement of the system before applying a command on the upper part of the system to check its stability. Concerning the nonlinearities of the system, we have found a state feedback fuzzy control approach. Overall, the simulation results have shown that the fuzzy state feedback model is very efficient and flexible as it can be modified in different positions.

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Section: Introductionmentioning

confidence: 99%

T-S Fuzzy System Controller for Stabilizing the Double Inverted Pendulum

Elkinany

Alfidi

Chaibi

et al. 2020

Advances in Fuzzy Systems

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Development of a theoretical model for upright postural control in lower limb prosthesis users

Rusaw

Alinder

Edholm

et al. 2021

Sci Rep

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Methods used to assess quiet standing in unilateral prosthesis users often assume validity of an inverted pendulum model despite this being shown as invalid in some instances. The aim of the current study was to evaluate the validity of a proposed unilaterally-constrained pin-controller model in explaining postural control in unilateral prosthesis users. Prosthesis users were contrasted against the theoretical model as were able-bodied controls that stood on a platform which unilaterally constrained movement of the CoP. All participants completed bouts of quiet standing with eyes open, eyes closed and with feedback on inter-limb weight bearing asymmetry. Correlation coefficients were used to infer inverted pendulum behavior in both the anteroposterior and mediolateral directions and were derived from both kinematic (body attached markers) and kinetic (centre of pressure) experimental data. Larger, negative correlation coefficients reflected better model adherence, whilst low or no correlation reflected poorer model adherence. Inverted pendulum behavior derived from kinematic data, indicated coefficients of high magnitude in both mediolateral (all cases range 0.71–0.78) and anteroposterior (0.88–0.91) directions, irrespective of groups. Inverted pendulum behavior derived from kinetic data in the anteroposterior direction indicated validity of the model with large negative coefficients associated with the unconstrained/intact limbs (prosthesis users: − 0.45 to − 0.65, control group: − 0.43 to − 0.72), small coefficients in constrained/prosthetic limbs (prosthesis users: − 0.02 to 0.07, control group: 0.13–0.26) and large negative coefficients in combined conditions (prosthesis users: − 0.36 to − 0.56, control group: − 0.71 to − 0.82). For the mediolateral direction, coefficients were negligible for individual limbs (0.03–0.17) and moderate to large negative correlations, irrespective of group (− 0.31 to − 0.73). Data suggested both prosthesis users’ and able-bodied individuals’ postural control conforms well to that predicted by a unilaterally-constrained pin-controller model, which has implications for the fundamental control of posture in transtibial prosthesis users.

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