Genetic algorithm tuning of Lyapunov-based controllers: an application to a single-link flexible robot system

1996 ◽  
Vol 43 (5) ◽  
pp. 567-574 ◽  
Author(s):  
S.S. Ge ◽  
T.H. Lee ◽  
G. Zhu
Keyword(s):  
Genetic Algorithm ◽  
Flexible Robot ◽  
Robot System ◽  
Single Link

scholarly journals Evolutionary computing approaches to optimum design of fuzzy logic controller for a flexible robot system

2013 ◽  
Vol 23 (4) ◽  
pp. 395-412 ◽  
Author(s):  
Bidyadhar Subudhi ◽  
Subhakanta Ranasingh
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Fitness Function ◽  
Flexible Manipulator ◽  
Position Tracking ◽  
Flexible Robot ◽  
Robot System ◽  
Single Link ◽  
Tip Position

Abstract This paper presents the design of a Fuzzy Logic Controller (FLC) whose parameters are optimized by using Genetic Algorithm (GA) and Bacteria Foraging Optimization (BFO) for tip position control of a single link flexible manipulator. The proposed FLC is designed by minimizing the fitness function, which is defined as a function of tip position error, through GA and BFO optimization algorithms achieving perfect tip position tracking of the single link flexible manipulator. Then the tip position responses obtained by using both the above controllers are compared to suggest the best controller for the tip position tracking.

Comparison of models for a single-link flexible robot ARM

1994 ◽  
Vol 27 (14) ◽  
pp. 415-420
Author(s):  
E. Bove ◽  
S. Nicosia ◽  
M. Simonelli
Keyword(s):  
Robot Arm ◽  
Flexible Robot ◽  
Single Link

scholarly journals Fault Reconstruction Based on Sliding Mode Observer for Nonlinear Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
Jing He ◽  
Changfan Zhang
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode ◽  
Variable Structure ◽  
Unknown Input ◽  
Robot System ◽  
Third Order ◽  
Reconstruction Scheme ◽  
Fault Reconstruction ◽  
Single Link ◽  
Sliding Mode Variable Structure

This paper presents a precision fault reconstruction scheme for a class of nonlinear systems involving unknown input disturbances. First, using the coordinate transformation algorithm, the disturbances and faults of the system are fully decoupled. Therefore, it is possible to eliminate the influence of disturbances to the system, namely, better disturbances robustness. On this basis, the design of a sliding mode state observer makes the most genuine reconstruction realizable, instead of estimation of faults. Furthermore, with the equivalent principle of sliding mode variable structure, the precision reconstruction of arbitrary nonlinear faults is achieved. Finally, the applications of fault reconstruction in a third-order nonlinear theoretical model with disturbances and in a single-link robot system, respectively, have demonstrated the validity of the proposed scheme.

Estimation of Critical Damping in Robot Joints and Identification of the Joint for Design With Most Effective Damping Enhancement

1994 ◽  
Author(s):  
Ahmad A. Smaili ◽  
Muhammad Sannah
Keyword(s):  
Natural Frequency ◽  
System Stability ◽  
Flexible Robot ◽  
Robot System ◽  
Joint Compliance ◽  
Dynamics And Control ◽  
Joint Identification ◽  
The One ◽  
And Control ◽  
Critical Damping

Abstract A major hindrance to dynamics and control of flexible robot manipulators is the deficiency of its inherent damping. Damping enhancement, therefore, should result in lower vibration amplitudes, shorter settling times, and improvement of system stability. Since the bulk of robot vibrations is attributed to joint compliance, it is a prudent strategy to design joints with sufficient inherent damping. In this article, a method is proposed to estimate critical damping at each joint and identify the joint that should be targeted for design with sufficient built-in damping. The target joint identification process requires that a n-joint robot system is divided into n-subsystems. Subsystem i includes the compliance of joint i and the inertia of the succeeding links, joint mechanisms, and payload. An equivalent single degree of freedom torsional model is devised and the natural frequency and critical damping is evaluated for each subsystem. The estimated critical damping at the joints are used to determine the elastodynamic response of the entire robot system from a model that includes joint compliance, shear deformation, rotary inertia, and geometric stiffness. The response revealed the following conclusion: The joint of the manipulator that would result in lower amplitudes of vibrations and shorter settling times when designed with sufficient built-in damping is the one that renders a subsystem whose natural frequency is the lowest of all subsystems comprising the robot.

Neural-Network Based Learning Control of Flexible Mechanism With Application to a Single-Link Flexible Arm

1994 ◽  
Vol 116 (4) ◽  
pp. 792-795 ◽  
Author(s):  
Kazuhiko Takahashi ◽  
Ichiro Yamada
Keyword(s):  
Neural Network ◽  
Angular Position ◽  
Target System ◽  
Space Representation ◽  
Robot Arm ◽  
Flexible Robot ◽  
Neural Network Controller ◽  
Flexible Arm ◽  
Single Link ◽  
Flexible Mechanism

This paper shows the effectiveness of a neural-network controller for controlling a flexible mechanism such as a flexible robot arm. An adaptive-type direct neural controller is formulated using state-space representation of the dynamics of the target system. The characteristics of the controller are experimentally investigated by using it to control the tip angular position of a single-link flexible arm.

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