Fast and precise positioning of rotary table systems by feedforward disturbance compensation considering interference force

Ito, Kazuaki; Maebashi, Wataru; Ikeda, Jun; Iwasaki, Makoto

doi:10.1109/iecon.2011.6119855

Cited by 7 publications

(5 citation statements)

References 10 publications

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“…The rotary table has been widely used in many areas such as synthetic aperture radar System (SAR) [1], industrial applications [2][3] [4][5] [6], calibration tools [7][8] [9], transportation systems [10] and so on. In order to get a satisfactory result, the rotary table has to meet high precision output which in this case is an accurate position of determined angle.…”

Section: Introductionmentioning

confidence: 99%

Position Control of 1-DOF High-Precision Rotary Table using Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller

Saputra

Nurhakim

Utomo

2019

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Research of position control of 1-DOF high-precision rotary table using adaptive Neuro-Fuzzy inference system (ANFIS) controller has been done. In the closed-loop system without a controller, the response was oscillating and pounding caused by inertial torque. It because a rotary table receives a considerable load. Based on this, the ANFIS controller is needed to eliminate oscillations and compensate for the inertia. The result shows that there was no oscillation or overshoot with the steady-state error value of 2.27% for the reference angle of 45Â°, valued at 0.10% reference angle of 180Â°, and valued at 0% reference angle of 360Â°. The result proves that ANFIS controllers can eliminate oscillations with and compensate for inertia.

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Section: Introductionmentioning

confidence: 99%

Position Control of 1-DOF High-Precision Rotary Table using Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller

Saputra

Nurhakim

Utomo

2019

emitter

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“…Therefore, this method offers low control accuracy and robustness. A feedforward scheme for a two axis inertial stabilized platform (ISP) was adopted to reject the periodic disturbing torque acting on the payload due to the static mass unbalance [9,10], but the accelerometer signal may be easily distorted by the centripetal acceleration [11]. The H ∞ control method presents strong robustness, but it is highly conservative and the control accuracy is usually sacrificed [12].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive B-Spline Neural Network and Its Application in Terminal Sliding Mode Control for a Mobile Satcom Antenna Inertially Stabilized Platform

Zhang

Zhao

Guo

et al. 2017

Sensors

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The mobile satcom antenna (MSA) enables a moving vehicle to communicate with a geostationary Earth orbit satellite. To realize continuous communication, the MSA should be aligned with the satellite in both sight and polarization all the time. Because of coupling effects, unknown disturbances, sensor noises and unmodeled dynamics existing in the system, the control system should have a strong adaptability. The significant features of terminal sliding mode control method are robustness and finite time convergence, but the robustness is related to the large switching control gain which is determined by uncertain issues and can lead to chattering phenomena. Neural networks can reduce the chattering and approximate nonlinear issues. In this work, a novel B-spline curve-based B-spline neural network (BSNN) is developed. The improved BSNN has the capability of shape changing and self-adaption. In addition, the output of the proposed BSNN is applied to approximate the nonlinear function in the system. The results of simulations and experiments are also compared with those of PID method, non-singularity fast terminal sliding mode (NFTSM) control and radial basis function (RBF) neural network-based NFTSM. It is shown that the proposed method has the best performance, with reliable control precision.

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“…In [17], an acceleration–based feedforward approach is proposed to realize imbalance torque compensation of a three-axis ISP. In [18], a model-based feedforward compensation approach is applied to a rotary table system. In [19], an anti-disturbance compensation control algorithm based on adaptive robust control idea is applied for a three-axis swing turntable system.…”

Section: Introductionmentioning

confidence: 99%

Experimental Validation of a Compound Control Scheme for a Two-Axis Inertially Stabilized Platform with Multi-Sensors in an Unmanned Helicopter-Based Airborne Power Line Inspection System

Zhou

Yuan

Zhao

et al. 2016

Sensors

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A compound control scheme is proposed to achieve high control performance for a two-axis inertially stabilized platform (ISP) with multi-sensors applied to an unmanned helicopter (UH)-based airborne power line inspection (APLI) system. Compared with the traditional two closed-loop control scheme that is composed of a high-bandwidth rate loop and a lower bandwidth position loop, a new current loop inside rate loop is particularly designed to suppress the influences of voltage fluctuation from power supply and motor back electromotive force (BEMF) on control precision. In this way, the stabilization accuracy of the ISP is greatly improved. The rate loop, which is the middle one, is used to improve sensor’s stability precision through compensating for various disturbances. To ensure the pointing accuracy of the line of sight (LOS) of multi-sensors, the position loop is designed to be the outer one and acts as the main feedback path, by which the accurate pointing angular position is achieved. To validate the scheme, a series of experiments were carried out. The results show that the proposed compound control scheme can achieve reliable control precision and satisfy the requirements of real APLI tasks.

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Fast and precise positioning of rotary table systems by feedforward disturbance compensation considering interference force

Cited by 7 publications

References 10 publications

Position Control of 1-DOF High-Precision Rotary Table using Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller

Position Control of 1-DOF High-Precision Rotary Table using Adaptive Neuro-Fuzzy Inference System (ANFIS) Controller

An Adaptive B-Spline Neural Network and Its Application in Terminal Sliding Mode Control for a Mobile Satcom Antenna Inertially Stabilized Platform

Experimental Validation of a Compound Control Scheme for a Two-Axis Inertially Stabilized Platform with Multi-Sensors in an Unmanned Helicopter-Based Airborne Power Line Inspection System

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