Occasional stabilisation of limit cycle walking and control of chaos in the passive dynamics of the compass-gait biped model

2021 ◽  
Vol 15 (2) ◽  
pp. 198
Author(s):  
Hassène Gritli
Keyword(s):  
Limit Cycle ◽  
Control Of Chaos ◽  
Passive Dynamics ◽  
Limit Cycle Walking ◽  
And Control

Analysis of limit-cycle walking for a compass-like biped robot *

2010 ◽  
Vol 43 (14) ◽  
pp. 1181-1186
Author(s):  
Leonid B. Freidovich ◽  
Anton S. Shiriaev
Keyword(s):  
Limit Cycle ◽  
Biped Robot ◽  
Limit Cycle Walking

scholarly journals Neural Networks for Prediction and Control of Chaotic Fluidized Bed Hydrodynamics

Fractals ◽  
1997 ◽  
Vol 05 (03) ◽  
pp. 523-530 ◽  
Author(s):  
R. Bakker ◽  
R. J. de Korte ◽  
J. C. Schouten ◽  
C. M. Van Den Bleek ◽  
F. Takens
Keyword(s):  
Fluidized Bed ◽  
Prediction Error ◽  
Control Of Chaos ◽  
Short Term ◽  
Prediction And Control ◽  
Short Term Prediction ◽  
Capacitance Tomography ◽  
And Control ◽  
Dynamic Invariants ◽  
Tomography Data

A neural-network-based model that has learnt the chaotic hydrodynamics of a fluidized bed reactor is presented. The network is trained on measured electrical capacitance tomography data. A training algorithm is used that does not only minimize the short-term prediction error but also the information needed to synchronize the model with the real system. This forces the model to focus more on learning the longer term dynamics of the system, expressed in the average multi-step-ahead prediction error and dynamic invariants such as correlation entropy and dimension. The availability of the model is an important step towards control of chaos in gas-solid fluidized beds.

scholarly journals Height control for a two-mass hopping robot based on stable limit cycle

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141665774
Author(s):  
Taihui Zhang ◽  
Honglei An ◽  
Qing Wei ◽  
Wenqi Hou ◽  
Hongxu Ma
Keyword(s):  
Limit Cycle ◽  
Control Algorithm ◽  
Stable Limit Cycle ◽  
Stable Limit ◽  
Inverted Pendulum Model ◽  
Hopping Robot ◽  
Control Objective ◽  
Upper Level ◽  
Mass Spring ◽  
And Control

Differing from the commonly used spring loaded inverted pendulum model, this paper makes use of a two-mass spring model considering impact between the foot and ground which is closer to the real hopping robot. The height of upper mass which includes the upper leg and body is the main control objective. Then we develop a new kind of control algorithm acting on two levels: The upper level aims to achieve the desired velocity of the upper mass based on a stable limit cycle, where three different controllers are used to regulate the limit cycle; the target of the lower level is to drive the system to converge to the desired state and control the contact force between the foot and ground within an appropriate range based on the inner force control at the same time. Simulation results presented in this paper confirm the efficiency of this control algorithm.

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