New skill learning paradigm using various kinds of neurons

Eom, Tae-Dok; Sugisaka, Masanori; Lee, Ju-Jang

doi:10.1016/s0096-3003(97)10011-x

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…Since Ott, Grebogi, and Yorke [6], in 1990, pointed out the existence of many unstable periodic orbits (UPOs) embedded in chaotic attractors that raise the possibility of using very small external forces to obtain various types of regular behavior, Pyragas [7] in 1992, proposed a so-called "Delayed Feedback Control (DFC)" idea that an appropriate continuous controlling signal formed from the difference between the current state and the delayed state is injected into the system, whose intensity is practically zero as the system evolves close to the desired periodic orbit but increases when it drifts away from the desired orbit, several techniques were devised for controlling chaos [8][9][10][11][12][13][14][15][16][17][18][19][20][21] during the past years and applied to various systems [22][23][24][25][26][27][28][29][30][31]. It is worth noting that in spite of the enormous number of applications among the chaos control, very few rigorous results are so far available.…”

Section: Introductionmentioning

confidence: 99%

Stabilization Control for the Giant Swing Motion of the Horizontal Bar Gymnastic Robot Using Delayed Feedback Control

Liu¹

2016

Complex Systems, Sustainability and Innovation

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Open-loop dynamic characteristics of an underactuated system with nonholonomic constraints, such as a horizontal bar gymnastic robot, show the chaotic nature due to its nonlinearity. This chapter deals with the stabilization problems of periodic motions for the giant swing motion of gymnastic robot using chaos control methods. In order to make an extension of the chaos control method and apply it to a new practical use, some stabilization control strategies were proposed, which were, based on the idea of delayed feedback control (DFC), devised to stabilize the periodic motions embedded in the movements of the gymnastic robot. Moreover, its validity has been investigated by numerical simulations. First, a method named as prediction-based DFC was proposed for a two-link gymnastic robot using a Poincaré section. Meanwhile, a way to calculate analytically the error transfer matrix and the input matrix that are necessary for discretization was investigated. Second, an improved DFC method, multiprediction delayed feedback control, using a periodic gain, was extended to a four-link gymnastic robot. A set of plural Poincare maps were defined with regard to the original continuous-time system as a T-periodic discrete-time system. Finally, some simulation results showed the effectiveness of the proposed methods.

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Section: Introductionmentioning

confidence: 99%

Stabilization Control for the Giant Swing Motion of the Horizontal Bar Gymnastic Robot Using Delayed Feedback Control

Liu¹

2016

Complex Systems, Sustainability and Innovation

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“…3 The organization of the paper is as follows. When a known stimulus is applied to pretrained sensory receptors, the chaotically wandering states converge to the one of their limit cycles to represent the meaning of the stimulus for the subject instead of the properties intrinsic to the stimulus.…”

Section: Introductionmentioning

confidence: 99%

Information processing using chaos with application to mobile robot navigation problems

Choi

Eom

Hong

et al. 1998

Artificial Life and Robotics

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Throughout this study on information processing using an artificial neural network (ANN) and chaos we are attempting to devise a memory model that resembles human behavioral characteristics. For that purpose we construct a framework of the macroscopic model of the responding process in biological systems. Incoming stimuli are applied to the sensory receptors and preprocessed. A pattern-matching block allows one of the chaotic memories to find a feasible response in an associative way. After the chaotic memory is stabilized on one of the stable equilibrium points or limit cycles, its performance is evaluated. Since chaotic memory and the performance evaluation block form a feedback loop, they can handle features of the information blocks and store newly updated information blocks. Two kinds of chaotic memories are established in this paper: one is a 1-D map in which many information blocks can be stored as unstable periodic orbits, and the other is the famous Lozi attractor with rich dynamics. Simulations are performed for the mobile robot navigation problem in each case.

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