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정슬 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.7
A time-delayed control (TDC) method is known as a simple, robust and non model-based control scheme that requires the fast sampling time, the accurate measurement of joint acceleration signals, and the accuracy of the inertia model of a robot manipulator. Among them, sampling time and acceleration signals are hardware dependent and can be solved. Then a user specified inertia model becomes a key role for the performance of TDC. When the selection of the diagonal element of the inertia matrix of a robot manipulator is used, the ill selection of the constantinertia matrix may lead to the poor tracking performance as well as instability. In addition, an appropriate selection of an inertia matrix for different tasks of the robot is not easy. Therefore, in this paper, an intelligent way of using a neural network is proposed to compensate for the deviation of the constant inertia matrix of a robot manipulator. The role of the neural network is to improve the tracking performance of a robot manipulator by compensating for the deviated error of the inertia matrix while satisfying the stability bound. Simulation studies of a three link robot. are presented to confirm the proposal.
Neural Network Compensation for Impedance Force Controlled Robot Manipulators
정슬 한국지능시스템학회 2014 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.14 No.1
This paper presents the formulation of an impedance controller for regulating the contactforce with the environment. To achieve an accurate force tracking control, uncertainties inboth robot dynamics and the environment require to be addressed. As part of the frameworkof the proposed force tracking formulation, a neural network is introduced at the desiredtrajectory to compensate for all uncertainties in an on-line manner. Compensation at the inputtrajectory leads to a remarkable structural advantage in that no modifications of the internalforce controllers are required. Minimizing the objective function of the training signal for aneural network satisfies the desired force tracking performance. A neural network actuallycompensates for uncertainties at the input trajectory level in an on-line fashion. Simulationresults confirm the position and force tracking abilities of a robot manipulator.
정슬 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.2
Neural network control for robot manipulators is aimed to compensate for uncertainties in the robotdynamics. The location of a compensating point differentiates the control scheme into two categories, the feedbackerror learning (FEL) scheme and the reference compensation technique (RCT). The RCT scheme is relatively lessused although it has several structural advantages. In this paper, the global stability of the RCT scheme is analyzedon the basis of Lyapunov function. The analysis turns out that the stability depends upon the magnitude of thecontroller gains. Simulation studies of controlling the position of a two-link robot manipulator are conducted.
카테시안 공간에서 시간 지연제어기의 구현에 대한 튜토리얼
정슬 제어·로봇·시스템학회 2021 제어·로봇·시스템학회 논문지 Vol.27 No.6
This paper presents a tutorial on the implementation of the time-delayed controller in the Cartesian space for robot manipulators. Although the Cartesian space position is actually controlled in the joint space through the inverse kinematics, the direct control of the Cartesian position is required for force control applications. For the implementation of Cartesian space controllers, there are several schemes due to the requirement of the transformation from the Cartesian space to the joint space. One is to use the acceleration relation between the joint space and the Cartesian space, which requires the inverse and the derivative of the Jacobian. Another is to use the transpose of the Jacobian. Accordingly, the time-delayed controller can be constructed in either the joint space or the Cartesian space for the Cartesian space control. Advantages of each implementation of the time-delayed controller for the Cartesian space are discussed. Extensive simulation studies for a robot manipulator to follow a circular trajectory are performed to explain the advantages of implementation of the time-delayed controller in the Cartesian space. .