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]

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.

Tracking Control of Periodic Signals With Varying Magnitude and Its Application to Hybrid Powertrain

2010 ◽  
Author(s):  
Xingyong Song ◽  
Pradeep Gillella ◽  
Zongxuan Sun
Keyword(s):  
Internal Model ◽  
Linear Time ◽  
Vibration Reduction ◽  
Repetitive Control ◽  
Periodic Signal ◽  
Asymptotic Performance ◽  
Hybrid Powertrain ◽  
Power Sources ◽  
Control Framework ◽  
Periodic Signals

Internal model based repetitive control for linear time invariant (LTI) system has been widely applied to track or reject periodic signals with only the period known. It is well understood that the discrete generating dynamics of the periodic signal can be obtained by finite sampling, and embedding it as the internal model will yield asymptotic performance. However, the traditional repetitive control framework will no longer work for periodic signals with varying peak to peak amplitude. As will be revealed in this paper, the generating dynamics of this kind of signals is time varying, and thus simply embedding its generating dynamics as the internal model will no longer ensure asymptotic performance. The necessity of investigating tracking or rejecting varying magnitude periodic signals comes from a wide class of anticipated applications, one example of which is the hybrid vehicle powetrain vibration reduction. In the hybrid vehicles, engine starting and stopping occur frequently to switch between power sources, which could cause driveline vibration. With proper formulation, the oscillation signal becomes periodic with varying magnitude. To suppress such vibration, in this paper, the generating dynamics of this unique signal is first derived, and then its corresponding controller design method is presented. After a series of simulations and case studies, the proposed control framework is demonstrated to be a promising solution for the hybrid powertrain vibration reduction problem.

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.

Sampled-data based asynchronous stabilization for switched systems with stochastic perturbations

2019 ◽  
Vol 42 (3) ◽  
pp. 439-450 ◽  
Author(s):  
Jianrong Zhao ◽  
Wen Wang ◽  
Dan Zhang
Keyword(s):  
Nonlinear Systems ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Average Dwell Time ◽  
Sampling Interval ◽  
Switched Nonlinear Systems ◽  
Sampled Data ◽  
Stochastic Perturbations ◽  
Asynchronous Control ◽  
Mass Spring

This paper studies the sampled-data based asynchronous control problem for switched nonlinear systems subject to stochastic perturbations. Applying the T-S fuzzy model, the sampled-data based asynchronous stabilization is studied for switched nonlinear systems subject to stochastic perturbations. Combining the sampled-data dependent Lyapunov functional with the mode-dependent average dwell-time technique, a fuzzy controller is obtained to stabilize switched nonlinear systems in the mean-square sense. No more than one switching and multiple switchings are both discussed in one sampling interval to achieve more common results. At last, a simulation example about nonlinear mass-spring mechanical systems subject to stochastic perturbations is given to illustrate the effectiveness of proposed results.

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.

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.

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