scholarly journals On Comparison Between Repetitive Controller and PI Controller Tracking Performance

Jurnal INKOM ◽  
2015 ◽  
Vol 8 (2) ◽  
pp. 95
Author(s):  
Edi Kurniawan
Keyword(s):  
Movement Control ◽  
Pi Controller ◽  
Tracking Performance ◽  
Periodic Signal ◽  
Tracking Accuracy ◽  
Internal Model Principle ◽  
Common Task ◽  
Control Schemes ◽  
Periodic Signals ◽  
Is Integration

Tracking periodic signals are common task in many control problems. One of the examples is movement control of pick and place robot in industry. The requirement of high tracking accuracy becomes very important in many applications. Therefore, a sophisticated control algorithm that manages to achieve high accuracy tracking of periodic command is required. Repetitive Control (RC) based on internal model principle is one of control schemes that can be employed to achieve perfect tracking of periodic signal. On the other hand, Proportional Integral (PI) controller can also be used for tracking. This paper compares the tracking performance of PI controller, RC, and PI with RC, where PI with RC here is integration between PI controller and RC. Step by step design to obtain the parameters of PI, RC and PI with RC are given. A simulation on servo motor system is carried out to assess the performance of RC, PI, andPI with RC respectively. From the simulation results, the transient response and tracking accuracy are thoroughly discussed.

Repetitive Control for Asymptotic Tracking of Periodic Signals With an Unknown Period

1998 ◽  
Vol 122 (2) ◽  
pp. 364-369 ◽  
Author(s):  
Tsu-Chin Tsao ◽  
Yao-Xin Qian and ◽  
Mahadevamurty Nemani
Keyword(s):  
Repetitive Control ◽  
Sampling Interval ◽  
Periodic Signal ◽  
Sampled Data ◽  
Motion System ◽  
Control Schemes ◽  
Asymptotic Tracking ◽  
Periodic Signals ◽  
Signal Period ◽  
Unknown Period

Repetitive control schemes for asymptotic tracking and disturbance rejection of periodic signals with an unknown period are presented. A sampled data recursive scheme for identifying the period of a periodic signal with a resolution finer than the sampling interval is presented. Discrete-time self-tuning repetitive controllers, which adapt both the periodic signal period and sampling interval, are proposed based on the period identification scheme. The fine adaptation of the controller sampling interval makes the identified signal period an exact integer multiples of the controller sampling interval and renders a superior tracking performance than that of the conventional fixed sampling interval repetitive controllers. Experimental results on a linear motion system are presented to demonstrate the effectiveness of the proposed control schemes. [S0022-0434(00)01402-7]

Virtual Instrument for Weak Signal Detecting on Monostable Stochastic Resonance

2011 ◽  
Vol 279 ◽  
pp. 361-366
Author(s):  
Quan Yuan ◽  
Yan Shen ◽  
Liang Chen
Keyword(s):  
Power Spectrum ◽  
White Noise ◽  
Stochastic Resonance ◽  
Virtual Instrument ◽  
Stable System ◽  
Periodic Signal ◽  
Nonlinear Phenomenon ◽  
Weak Signal ◽  
Additive White Noise ◽  
Periodic Signals

Stochastic resonance (SR) is a nonlinear phenomenon which can be used to detect weak signal. The theory of SR in a biased mono-stable system driven by multiplicative and additive white noise as well as a weak periodic signal is investigated. The virtual instrument (VI) for weak signal detecting based on this theory is designed with LabVIEW. This instrument can be used to detect weak periodic signals which meets the conditions given and can greatly improved the power spectrum of the weak signal. The results that related to different sets of parameters are given and the features of these results are in accordance with the theory of mono-stable SR. Thus, the application of this theory in the detecting of weak signal is proven to be valid.

scholarly journals Detection of Periodic Radio Signal from the Blazar J1043+2408

Galaxies ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 136 ◽  
Author(s):  
Gopal Bhatta
Keyword(s):  
Black Hole ◽  
Radio Signal ◽  
Field Configuration ◽  
Periodic Signal ◽  
Magnetic Field Configuration ◽  
Supermassive Black Hole ◽  
Central Engine ◽  
Direct View ◽  
Periodic Signals ◽  
Periodic Changes

The search for periodic signals from blazars has become a widely discussed topic in recent years. In the scenario that such periodic changes originate from the innermost regions of blazars, the signals bear imprints of the processes occurring near the central engine, which are mostly inaccessible to our direct view. Such signals provide insights into various aspect of blazar studies, including disk-jet connection, magnetic-field configuration and, more importantly, strong gravity near the supermassive black holes and release of gravitational waves from binary supermassive-black-hole systems. In this work, we report the detection of a periodic signal in the radio light curve of blazar J1043+2408 spanning ∼10.5 years. We performed multiple methods of time-series analysis, namely, epoch folding, Lomb–Scargle periodogram, and discrete autocorrelation function. All three methods consistently revealed a repeating signal with a periodicity of ∼560 days. To robustly account for the red-noise processes usually dominant in the blazar variability and other possible artefacts, a large number of Monte Carlo simulations were performed. This allowed us to estimate high significance (99.9% local and 99.4% global) against possible spurious detection. As possible explanations, we discuss a number of scenarios, including binary supermassive-black-hole systems, Lense–Thirring precession, and jet precession.

scholarly journals Design of Augmented Nonlinear PD Controller of Delta/Par4-Like Robot

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Amjad J. Humaidi ◽  
Ahmed Ibraheem Abdulkareem
Keyword(s):  
Trajectory Tracking ◽  
Lyapunov Method ◽  
Dynamic Performance ◽  
Parallel Robot ◽  
Pd Controller ◽  
Comparison Study ◽  
Tracking Accuracy ◽  
Control Schemes ◽  
The Stability ◽  
Made In

This work presents the design of two control schemes for a Delta/Par4-like parallel robot: augmented PD (APD) controller and augmented nonlinear PD (ANPD) controller. The stability of parallel robot based on nonlinear PD controller has been analyzed and proved based on Lyapunov method. A comparison study between APD and ANPD controllers has been made in terms of performance and accuracy improvement of trajectory tracking. Also, another comparison study has been presented between augmented nonlinear PD (ANPD) controller and nonaugmented nonlinear PD (NANPD) controller in order to show the enhancement of introducing the augmented structure on dynamic performance and trajectory tracking accuracy. The effectiveness of augmented PD controllers (APD and ANPD) and nonaugmented nonlinear PD (NANPD) controller for the considered parallel robot are verified via simulation within the MATLAB environment.

Variance Based Identification of Phase Transition in Duffing Oscillator for Weak Signal Detection

2011 ◽  
Vol 128-129 ◽  
pp. 354-358 ◽  
Author(s):  
Yuan Chang ◽  
Chun Wen Li ◽  
Yi Hao
Keyword(s):  
Phase Transition ◽  
Signal Detection ◽  
Periodic Motion ◽  
Sharp Increase ◽  
Duffing Oscillator ◽  
Periodic Signal ◽  
Weak Signal ◽  
Weak Signal Detection ◽  
Periodic Signals ◽  
Simulation Results

This paper studies the detection of weak signal detection using a Duffing Oscillator, which is sensitive to periodic signals but insensitive to noises. The system transits from chaotic to great periodic motion when coupled to the weak periodic signal to be detected. To efficiently determine the phase transition, a novel numerical criterion is proposed based on the sharp increase of variance when phase change happens. Simulation results verified the effectiveness of this method.

scholarly journals Multiple Harmonics Fitting Algorithms Applied to Periodic Signals Based on Hilbert-Huang Transform

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Hui Wang ◽  
Zhengshi Liu ◽  
Bin Zhu ◽  
Quanjun Song
Keyword(s):  
Signal Processing ◽  
Harmonic Distortion ◽  
Digital Signal ◽  
Periodic Signal ◽  
Sinusoidal Wave ◽  
Analog To Digital ◽  
Triangular Wave ◽  
Hilbert Huang Transform ◽  
Digital To Analog Converters ◽  
Periodic Signals

A new generation of multipurpose measurement equipment is transforming the role of computers in instrumentation. The new features involve mixed devices, such as kinds of sensors, analog-to-digital and digital-to-analog converters, and digital signal processing techniques, that are able to substitute typical discrete instruments like multimeters and analyzers. Signal-processing applications frequently use least-squares (LS) sine-fitting algorithms. Periodic signals may be interpreted as a sum of sine waves with multiple frequencies: the Fourier series. This paper describes a new sine fitting algorithm that is able to fit a multiharmonic acquired periodic signal. By means of a “sinusoidal wave” whose amplitude and phase are both transient, the “triangular wave” can be reconstructed on the basis of Hilbert-Huang transform (HHT). This method can be used to test effective number of bits (ENOBs) of analog-to-digital converter (ADC), avoiding the trouble of selecting initial value of the parameters and working out the nonlinear equations. The simulation results show that the algorithm is precise and efficient. In the case of enough sampling points, even under the circumstances of low-resolution signal with the harmonic distortion existing, the root mean square (RMS) error between the sampling data of original “triangular wave” and the corresponding points of fitting “sinusoidal wave” is marvelously small. That maybe means, under the circumstances of any periodic signal, that ENOBs of high-resolution ADC can be tested accurately.

scholarly journals Application of the second order generalized integrator in digital control systems

2014 ◽  
Vol 63 (3) ◽  
pp. 423-437 ◽  
Author(s):  
Kamil Możdżyński ◽  
Krzysztof Rafał ◽  
Małgorzata Bobrowska-Rafał
Keyword(s):  
Control Systems ◽  
System Performance ◽  
Second Order ◽  
Estimation Methods ◽  
Practical Implementation ◽  
Periodic Signal ◽  
Discretization Method ◽  
Digital Control Systems ◽  
Band Pass ◽  
Periodic Signals

Abstract The paper describes second order generalized integrator (sogi) which is specialized in band-pass filtering and orthogonalization of periodic signals. Modifications of the structure and the influence of parameters on the system performance is described. The article highlights the particular importance of model discretization method in the practical implementation, as well as reviews estimation methods of the: amplitude, frequency, offset and phase angle of the periodic signal. Examples of simulation and experimental results are presented

Precision Control of a Piezo-Actuate System Using Fuzzy Sliding-Mode Control with Feedforward Predictor-Based Compensation

2008 ◽  
Vol 594 ◽  
pp. 401-406 ◽  
Author(s):  
Jin Wei Liang ◽  
Hung Yi Chen ◽  
Shy Yaw Chiang
Keyword(s):  
Sliding Mode Control ◽  
Piezoelectric Actuator ◽  
Sliding Mode ◽  
Tracking Error ◽  
Tracking Accuracy ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Control Schemes ◽  
Fuzzy Sliding Mode ◽  
Hysteretic Characteristics

The fuzzy sliding-mode control strategy is used to tackle tracking problem of a piezo-actuated stage in this paper. The piezo-actuated system is composed of the piezoelectric actuator and a positioning mechanism. Due to hysteretic nonlinearity of the piezoelectric actuator, the tracking accuracy of the system is limited. To compensate for this nonlinearity, a feedback fuzzy sliding-mode control augmented with a predictor-based feedforward compensator is proposed. The controller, denoted as the feedforward-feedback fuzzy sliding-mode controller (FF-FSMC), can be applied to eliminate tracking error caused by the hysteretic characteristics. Experimental results on different types of reference inputs indicate that the proposed control schemes may suppress the tracking error of the piezo-actuated system effectively.

scholarly journals Simulation of closed-loop deep brain stimulation control schemes for suppression of pathological beta oscillations in Parkinson’s disease

2019 ◽  
Author(s):  
John E. Fleming ◽  
Eleanor Dunn ◽  
Madeleine M. Lowery
Keyword(s):  
Deep Brain Stimulation ◽  
Closed Loop ◽  
Pi Controller ◽  
Open Loop ◽  
Beta Band ◽  
Preclinical Testing ◽  
Control Schemes ◽  
The Mean ◽  
Band Activity ◽  
Deep Brain

AbstractThis study presents a computational model of closed-loop control of deep brain stimulation (DBS) for Parkinson’s disease (PD) to investigate clinically-viable control schemes for suppressing pathological beta-band activity. Closed-loop DBS for PD has shown promising results in preliminary clinical studies and offers the potential to achieve better control of patient symptoms and side effects with lower power consumption than conventional open-loop DBS. However, extensive testing of algorithms in patients is difficult. The model presented provides a means to explore a range of control algorithms in silico and optimize control parameters before preclinical testing. The model incorporates (i) the extracellular DBS electric field, (ii) antidromic and orthodromic activation of STN afferent fibers, (iii) the LFP detected at non-stimulating contacts on the DBS electrode and (iv) temporal variation of network beta-band activity within the thalamo-cortico-basal ganglia loop. The performance of on-off and dual-threshold controllers for suppressing beta-band activity by modulating the DBS amplitude were first verified, showing levels of beta suppression and reductions in power consumption comparable with previous clinical studies. Proportional (P) and proportional-integral (PI) closed-loop controllers for amplitude and frequency modulation were then investigated. A simple tuning rule was derived for selecting effective PI controller parameters to target long duration beta bursts while respecting clinical constraints that limit the rate of change of stimulation parameters. Of the controllers tested, PI controllers displayed superior performance for regulating network beta-band activity whilst accounting for clinical considerations. Proportional controllers resulted in undesirable rapid fluctuations of the DBS parameters which may exceed clinically tolerable rate limits. Overall, the PI controller for modulating DBS frequency performed best, reducing the mean error by 83% compared to DBS off and the mean power consumed to 25% of that utilized by open-loop DBS. The network model presented captures sufficient physiological detail to act as a surrogate for preclinical testing of closed-loop DBS algorithms using a clinically accessible biomarker, providing a first step for deriving and testing novel, clinically-suitable closed-loop DBS controllers.

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