Balance Control for the First-order Inverted Pendulum Based on the Advantage Actor-critic Algorithm

2020 ◽  
Vol 18 (12) ◽  
pp. 3093-3100 ◽  
Author(s):  
Yan Zheng ◽  
Xutong Li ◽  
Long Xu
2021 ◽  
Author(s):  
Arnab Pal ◽  
Ramashis Banerjee ◽  
Debottam Mukherjee ◽  
Samrat Chakraborty ◽  
Pabitra Kumar Guchhait ◽  
...  

Robotics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 89 ◽  
Author(s):  
Giuseppe Menga ◽  
Marco Ghirardi

The zero moment point ( Z M P ) and the linearized inverted pendulum model linking the Z M P to the center of gravity ( C O G ) have an important role in the control of the postural equilibrium (balance) of biped robots and lower-limb exoskeletons. A solution for balance real time control, closing the loop from the joint actual values of the C O G and Z M P , has been proposed by Choi. However, this approach cannot be practically implemented: While the Z M P actual value is available from the center of pressure ( C o P ) measured under the feet soles, the C O G is not measurable, but it can only be indirectly assessed from the joint-angle measures, the knowledge of the kinematics, and the usually poorly known weight distribution of the links of the chain. Finally, the possible presence of unknown external disturbance forces and the nonlinear, complex nature of the kinematics perturb the simple relationship between the Z M P and C O G in the linearized model. The aim of this paper is to offer, starting from Choi’s model, a practical implementation of closed-loop balance control fusing C o P and joint-angle measures, eliminating possible inconsistencies. In order to achieve this result, we introduce a model of the linearized inverted pendulum for an extended estimation, not only of C O G and Z M P , but also of external disturbances. This model is then used, instead of Choi’s equations, for estimation and balance control, using H ∞ theory. As the C O G information is recovered from the joint-angle measures, the identification of a statistically equivalent serial chain ( S E S C ) linking the C O G to the joint angles is also discussed.


2020 ◽  
Vol 15 (9) ◽  
Author(s):  
Kyle W. Siegrist ◽  
Ryan M. Kramer ◽  
James R. Chagdes

Abstract Understanding the mechanisms behind human balance has been a subject of interest as various postural instabilities have been linked to neuromuscular diseases (e.g., Parkinson's, multiple sclerosis, and concussion). This paper presents a method to characterize an individual's postural stability and estimate of their neuromuscular feedback control parameters. The method uses a generated topological mapping between a subject's experimental data and a dataset consisting of time-series realizations generated using an inverted pendulum mathematical model of upright balance. The performance of the method is quantified using a set of validation time-series realizations with known stability and neuromuscular control parameters. The method was found to have an overall sensitivity of 85.1% and a specificity of 91.9%. Furthermore, the method was most accurate when identifying limit cycle oscillations (LCOs) with a sensitivity of 91.1% and a specificity of 97.6%. Such a method has the capability of classifying an individual's stability and revealing possible neuromuscular impairment related to balance control, ultimately providing useful information to clinicians for diagnostic and rehabilitation purposes.


Author(s):  
Akihiro HARA ◽  
Guillermo ENRIQUEZ ◽  
Huei Ee YAP ◽  
Shuji HASHIMOTO

Author(s):  
Akihiro HARA ◽  
Guillermo ENRIQUEZ ◽  
Huei Ee YAP ◽  
Shuji HASHIMOTO

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