Solving the inverse dynamic problem with the use of simulation systems

2013 ◽  
Vol 13 (12) ◽  
Author(s):  
Vladimir Fedoruk ◽  
Vladimir Martynyuk ◽  
Vladimir Trusonoshin ◽  
Elena Fedoruk
Keyword(s):  
Dynamic Problem ◽  
Inverse Dynamic ◽  
Inverse Dynamic Problem ◽  
Simulation Systems

scholarly journals Predictive Assessment of Operator's Hand Trajectory with the Copying Type of Control for Solution of the Inverse Dynamic Problem

2019 ◽  
Vol 18 (1) ◽  
pp. 123-147 ◽  
Author(s):  
Viacheslav Petrenko ◽  
Fariza Tebueva ◽  
Mikhail Gurchinsky ◽  
Vladimir Antonov ◽  
Andrey Pavlov
Keyword(s):  
Motion Planning ◽  
Real Time ◽  
Dynamic Problem ◽  
Control Object ◽  
Movement Planning ◽  
Inverse Dynamic ◽  
Predictive Values ◽  
Generalized Coordinates ◽  
Hand Trajectory ◽  
Inverse Dynamic Problem

The most important task of modern robotics is the development of robots to perform the work in potentially dangerous fields which can cause the risk to human health. Currently robotic systems can not become a full replacement for man for solving complex problems in a dynamic environment despite an active development of artificial intelligence technologies. The robots that implement the copying type of control or the so-called virtual presence of the operator are the most advanced for use in the nearest future. The principle of copying control is based on the motion capture of the remote operator and the formation of control signals for the robot’s drives. A tracking system or systems based on movement planning can be used to control the drives. The tracking systems are simpler, but systems based on motion planning allow to achieve more smooth motion and less wear on the parts of the control object. An artificial delay between the movements of the operator and the control object for necessary data collection  is used  to implement the control-based motion planning. The aim of research is a reduction of delay, which appears when controlling the anthropomorphic manipulator drives based on the solution of the inverse dynamic problem, when real time copying type of control is used . For motion path planning it is proposed to use forecast values of the generalized coordinates for manipulator. Based on the measured values of the generalized coordinates of the operator's hand, time series are formed and their prediction is performed. Predictive values of generalized coordinates are used in planning the anthropomorphic manipulator trajectory and solving the inverse dynamic problem. Prediction is based on linear regression with relatively low computational complexity, which is an important criterion for the system operation in the real time operation mode. The developed mathematical apparatus, based on prediction parameters and maximum permissible accelerations of the manipulator drives, allows to find a theoretical estimate of error values limits for planning the operator's hand trajectory using the proposed approach for specific tasks. The adequacy of the maximum theoretical value of the prediction error, as well as the prospects of the proposed approach for testing in practice is confirmed by the software simulation in Matlab environment.

Inverse dynamic problem for a Krein–Stieltjes string

2019 ◽  
Vol 96 ◽  
pp. 195-201 ◽  
Author(s):  
Alexander Mikhaylov ◽  
Victor Mikhaylov
Keyword(s):  
Dynamic Problem ◽  
Inverse Dynamic ◽  
Stieltjes String ◽  
Inverse Dynamic Problem

Inverse Dynamics Based Trajectory Tracking for a One-Link Flexible Arm

1991 ◽  
Author(s):  
Santiago López-Linares ◽  
Roberto F. Jacobus ◽  
Eliodoro Carrera ◽  
Miguel A. Serna
Keyword(s):  
Trajectory Tracking ◽  
Dynamic Problem ◽  
Inverse Dynamics ◽  
Open Loop ◽  
Flexible Manipulator ◽  
Linear Quadratic ◽  
Unknown Parameters ◽  
Inverse Dynamic ◽  
Flexible Arm ◽  
Inverse Dynamic Problem

Abstract This paper presents a new method for controlling a one-link flexible manipulator, based on the solution to the Inverse Dynamic Problem and on a Linear Quadratic Gaussian regulator (LQG). The inverse dynamic solution provides the torque that must be applied by the actuator at the hub to obtain a given trajectory at the tip. This torque can then be used in an open-loop control but, in practice, errors in tip position will appear along the way due to friction, unknown parameters in the model, disturbances, etc. To cope with these problems a trajectory following control is suggested. The technique consists in designing an LQG capable of driving the arm to intermediate states computed in the Inverse Dynamic Problem. Computer simulations with a Finite Element Model of the flexible arm are presented showing a very accurate trajectory tracking.

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