Flexible Control of Flexible Objects. Focus on “An Experimentally Confirmed Mathematical Model for Human Control of a Non-Rigid Object”

Kurt A. Thoroughman

doi:10.1152/jn.01060.2003

Experimentally Confirmed Mathematical Model for Human Control of a Non-Rigid Object

Journal of Neurophysiology ◽

10.1152/jn.00704.2003 ◽

2004 ◽

Vol 91 (3) ◽

pp. 1158-1170 ◽

Cited By ~ 64

Author(s):

Jonathan B. Dingwell ◽

Christopher D. Mah ◽

Ferdinando A. Mussa-Ivaldi

Keyword(s):

Mathematical Model ◽

Human Subjects ◽

Movement Planning ◽

Relative Speed ◽

Rigid Object ◽

Hand Motion ◽

Human Control ◽

Rigid Objects ◽

Minimum Jerk ◽

Neuroscience Research

Determining the principles used to plan and execute movements is a fundamental question in neuroscience research. When humans reach to a target with their hand, they exhibit stereotypical movements that closely follow an optimally smooth trajectory. Even when faced with various perceptual or mechanical perturbations, subjects readily adapt their motor output to preserve this stereotypical trajectory. When humans manipulate non-rigid objects, however, they must control the movements of the object as well as the hand. Such tasks impose a fundamentally different control problem than that of moving one's arm alone. Here, we developed a mathematical model for transporting a mass-on-a-spring to a target in an optimally smooth way. We demonstrate that the well-known “minimum-jerk” model for smooth reaching movements cannot accomplish this task. Our model extends the concept of smoothness to allow for the control of non-rigid objects. Although our model makes some predictions that are similar to minimum jerk, it predicts distinctly different optimal trajectories in several specific cases. In particular, when the relative speed of the movement becomes fast enough or when the object stiffness becomes small enough, the model predicts that subjects will transition from a uni-phasic hand motion to a bi-phasic hand motion. We directly tested these predictions in human subjects. Our subjects adopted trajectories that were well-predicted by our model, including all of the predicted transitions between uni- and bi-phasic hand motions. These findings suggest that smoothness of motion is a general principle of movement planning that extends beyond the control of hand trajectories.

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Research and automation of the process of electrocoagulation wastewater treatment on the basis of the developed mathematical model

Modeling, Control and Information Technologies ◽

10.31713/mcit.2020.17 ◽

2020 ◽

pp. 59-62

Author(s):

Andrii Safonyk ◽

Sergiy Koval ◽

Olga Safonyk ◽

Andre Batako

Keyword(s):

Mathematical Model ◽

Wastewater Treatment ◽

Control System ◽

Computer Simulations ◽

Spatial Model ◽

Model Problem ◽

Purification Process ◽

Flexible Control ◽

Flexible Control System ◽

The Mathematical Model

The paper presents the principles of the construction of an automated wastewater treatment system based on a generalized spatial model. A model problem, which contains descriptions of the main processes occurring in the electrocoagulation reactor taking into account the placement of the plates was developed. To verify the adequacy, a comparison between computer simulations and the results of a field experiment was made. The influence of reactor size, current density, location of electrode plates on the efficiency of chromium extraction was investigated. As a result of the study, it was proved that the mathematical model is effective for determining the parameters of the purification process, and the obtained coefficients are effective for optimizing the purification process. Based on these studies, a scheme for automation of the process of wastewater treatment from chromium was built. With the help of SCADA - WinCC, a flexible control system with the ability to control the performance of the entire installation in real time was developed.

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Fast and Slow Learning in Human-Like Intelligence

10.1093/oso/9780198862536.003.0016 ◽

2021 ◽

pp. 316-337

Author(s):

Denis Mareschal ◽

Sam Blakeman

Keyword(s):

Knowledge Bases ◽

Prediction Errors ◽

Flexible Control ◽

Human Control ◽

Reward Prediction ◽

High Reward ◽

Equal Capacity ◽

Inference Systems ◽

Flexible Control System ◽

Slow Learning

In this chapter we review the extent to which rapid one-short learning or fast-mapping exists in human learning. We find that it exists in both children and adults, but that it is almost always accompanied by slow consolidated learning in which new knowledge is integrated with existing knowledge-bases. Rapid learning is also present in a broad range of non-human species, particularly in the context of high reward values. We argue that reward prediction errors guide the extent to which fast or slow learning dominates, and present a Complementary Learning Systems neural network model (CTDL) of cortical/hippocampal learning that uses reward prediction errors to adjudicate between learning in the two systems. Developing human-like artificial intelligence will require implementing multiple learning and inference systems governed by a flexible control system with an equal capacity to that of human control systems.

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Die toepassing van wasige logika in industriële beheerstelsels

Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie ◽

10.4102/satnt.v14i2.608 ◽

1995 ◽

Vol 14 (2) ◽

pp. 55-65

Author(s):

I. S. Shaw

Keyword(s):

Mathematical Model ◽

Fuzzy Logic ◽

Fuzzy Sets ◽

Know How ◽

Human Control ◽

Process Dynamics ◽

Accurate Knowledge ◽

Human Operators ◽

Control Operators ◽

Theory Of Fuzzy Sets

The theory of fuzzy sets is a methodology for the handling of qualitive, inexact, imprecise information in a systematic and rigorous way. Conventional control approaches require a mathematical model of the process or system to be controlled. However, when an accurate knowledge of the process dynamics is not available, or the process is highly complex or non linear, conventional techniques do not give satisfactory results and human control operators must still be used. In contrast, fuzzy logic captures and utilizes the accumulated empirical know-how of human operators expressed in qualitative, inexact, imprecise ways.

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