One step ahead adaptive control technique featured by fuzzy-based least square estimator for wind systems

2021 ◽  
pp. 0309524X2110107
Author(s):  
Lorenzo Dambrosio
Keyword(s):  
Convergence Rate ◽  
Synchronous Generator ◽  
Least Square ◽  
Control Technique ◽  
Estimation Accuracy ◽  
Wind System ◽  
Horizontal Axis Wind Turbine ◽  
Least Square Estimator ◽  
One Step ◽  
The One

The present paper proposes the application to a wind system of the One Step Ahead control scheme featured by a Fuzzy-based Least Square Estimator. The considered wind system power generation supplies an electrical load disconnected from the power supply grid. It is composed of a three bladed horizontal-axis wind turbine which drives a synchronous generator by means of gearbox: the mathematical model for both the horizontal-axis wind-turbine and the synchronous generator will be briefly outlined. The adaptive nature of the One-Step-Ahead control algorithm relies on providing consistent estimation of the controlled system. This is achieved by means of a Least Square Algorithm that is able to provide a good estimation of a linear discrete time model of the controlled system, nevertheless its convergence rate reduces very quickly. For this reason, Least Square Algorithm needs a resetting strategy, which allows the achievement of a compromise between estimation accuracy and convergence rate. This not only represents a very problem-dependent issue but also introduces weaknesses in term of control tracking errors, which in turns needs an extra control contribution (integral correction). The proposed Least Square Algorithm enhancement overcomes these issues managing differently the estimation accuracy and the convergence rate. In the Results section, the achievements of the application of the One-Step-Ahead algorithm to the wind system will prove the reliability of the suggested enhanced control technique.

Enhanced one-step-ahead adaptive control technique for wind systems

2018 ◽  
Vol 42 (2) ◽  
pp. 141-150
Author(s):  
Lorenzo Dambrosio
Keyword(s):  
Wind Turbine ◽  
Control Algorithm ◽  
Horizontal Axis ◽  
Control Technique ◽  
Induction Generator ◽  
Control Problems ◽  
Wind System ◽  
Horizontal Axis Wind Turbine ◽  
One Step ◽  
The One

This article proposes an enhanced version of the one-step-ahead control algorithm applied to a wind system. The wind system is considered as an isolate source of power and it is composed of a horizontal-axis wind turbine connected to an induction generator: consistent mathematical models for the horizontal-axis wind turbine and the induction generator will be introduced. Although the main strength of the one-step-ahead control technique is its adaptivity, nevertheless its convergence rate reduces very quickly. This aspect shows the primary algorithm weakness and is the reason for the proposed enhancement. Finally, the results of control problems will prove the reliability of the suggested enhanced control technique.

WTLS-Bayes Filter-based Relative Pose Estimation for Space Non-cooperative Unknown Target Without a Priori Knowledge

2021 ◽  
Author(s):  
CHENGGUANG ZHU ◽  
zhongpai Gao ◽  
Jiankang Zhao ◽  
Haihui Long ◽  
Chuanqi Liu
Keyword(s):  
Pose Estimation ◽  
A Priori ◽  
Convergence Time ◽  
Estimation Accuracy ◽  
A Priori Knowledge ◽  
One Step ◽  
Relative Pose ◽  
The One ◽  
Negative Factors ◽  
Priori Knowledge

Abstract The relative pose estimation of a space noncooperative target is an attractive yet challenging task due to the complexity of the target background and illumination, and the lack of a priori knowledge. Unfortunately, these negative factors have a grave impact on the estimation accuracy and the robustness of filter algorithms. In response, this paper proposes a novel filter algorithm to estimate the relative pose to improve the robustness based on a stereovision system. First, to obtain a coarse relative pose, the weighted total least squares (WTLS) algorithm is adopted to estimate the relative pose based on several feature points. The resulting relative pose is fed into the subsequent filter scheme as observation quantities. Second, the classic Bayes filter is exploited to estimate the relative state except for moment-of-inertia ratios. Additionally, the one-step prediction results are used as feedback for WTLS initialization. The proposed algorithm successfully eliminates the dependency on continuous tracking of several fixed points. Finally, comparison experiments demonstrate that the proposed algorithm presents a better performance in terms of robustness and convergence time.

Data-Tuned Fuzzy Logic Controller Applied to a Horizontal Axis Wind System

2020 ◽  
Author(s):  
Lorenzo Dambrosio
Keyword(s):  
Fuzzy Logic ◽  
Wind Turbine ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Tracking Error ◽  
Synchronous Generator ◽  
Horizontal Axis ◽  
Fuzzy Rules ◽  
Wind System ◽  
Horizontal Axis Wind Turbine

Abstract This paper deals with the control problem concerning the output voltage frequency and amplitude regulation of a wind system power plant not connected to the supply grid. The wind system configuration includes a horizontal-axis wind-turbine which drives a synchronous generator. An appropriate modeling approach has been adopted for both the wind-turbine and the synchronous generator. The proposed controller makes use of the fuzzy logic environment in order to take advantage of the wind plant system informations integrated into a limited number of equilibrium condition points (input variable - output variable pairs). The fuzzy logic controller described in the present paper merges the most appropriate fuzzy rules clusters, based on the steady state working conditions. Then, thanks to a Least Square Estimator algorithm, the proposed control algorithm evaluates, for each sample time, the linear relation between control law correction and control tracking error levels. In order to demonstrate robustness of the suggested fuzzy control algorithm, two sets of results have been provided: the first one consider a fuzzy base with equally spaced rules, whereas, in the second set results, the number of fuzzy rules is reduced by a 25%.

Adaptive Mismatch Compensation for Rate Integrating Vibratory Gyroscopes With Improved Convergence Rate

2014 ◽  
Author(s):  
Fu Zhang ◽  
Ehsan Keikha ◽  
Behrooz Shahsavari ◽  
Roberto Horowitz
Keyword(s):  
Convergence Rate ◽  
Degrees Of Freedom ◽  
Rotation Angle ◽  
Least Square ◽  
Parameter Estimates ◽  
Unknown Parameters ◽  
Least Square Estimator ◽  
Vibratory Gyroscopes ◽  
Adaptive Compensator ◽  
Simulation Results

This paper presents an online adaptive algorithm to compensate damping and stiffness frequency mismatches in rate integrating Coriolis Vibratory Gyroscopes (CVGs). The proposed adaptive compensator consists of a least square estimator that estimates the damping and frequency mismatches, and an online compensator that corrects the mismatches. In order to improve the adaptive compensator’s convergence rate, we introduce a calibration phase where we identify relations between the unknown parameters (i.e. mismatches, rotation rate and rotation angle). Calibration results show that the unknown parameters lie on a hyperplane. When the gyro is in operation, we project parameters estimated from the least square estimator onto the hyperplane. The projection will reduce the degrees of freedom in parameter estimates, thus guaranteeing persistence of excitation and improving convergence rate. Simulation results show that utilization of the projection method will drastically improve convergence rate of the least square estimator and improve gyro performance.

Time-varying threshold cointegration with an application to the Fisher hypothesis

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Lixiong Yang
Keyword(s):  
Convergence Rate ◽  
Threshold Effect ◽  
Least Square ◽  
Time Varying ◽  
Threshold Cointegration ◽  
Test Statistics ◽  
Least Square Estimator ◽  
Proposed Model ◽  
Fisher Hypothesis ◽  
The Us

Abstract This paper extends the threshold cointegration model developed by Gonzalo, J., and J. Y. Pitarakis. 2006. “Threshold Effects in Cointegrating Relationships.” Oxford Bulletin of Economics & Statistics 68: 813–33 and Chen, H. 2015. “Robust Estimation and Inference for Threshold Models with Integrated Regressors.” Econometric Theory 31 (4): 778–810 to allow for a time-varying threshold, which is a function of candidate variables that affect the separation of regimes. We derive the asymptotic distribution of the proposed least-square estimator of the threshold, and study the convergence rate of the threshold estimator. We also suggest test statistics for threshold effect and threshold constancy. Monte Carlo simulations point out that the convergence rate of the threshold estimator is consistent with the asymptotic theory, and the proposed tests have good size and power properties. The empirical usefulness of the proposed model is illustrated by an application to the US data to investigate the Fisher hypothesis.

scholarly journals Design and Simulation of an LQR-PI Control Algorithm for Medium Wind Turbine

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2248 ◽  
Author(s):  
Kwansu Kim ◽  
Hyun-Gyu Kim ◽  
Yuan Song ◽  
Insu Paek
Keyword(s):  
Numerical Model ◽  
Wind Turbine ◽  
Control Algorithm ◽  
Hybrid Control ◽  
Linear Quadratic Regulator ◽  
Synchronous Generator ◽  
Control Technique ◽  
Pi Control ◽  
Linear Quadratic ◽  
Horizontal Axis Wind Turbine

In this paper, a new linear quadratic regulator (LQR) and proportional integral (PI) hybrid control algorithm for a permanent-magnet synchronous-generator (PMSG) horizontal-axis wind turbine was developed and simulated. The new algorithm incorporates LQR control into existing PI control structures as a feed-forward term to improve the performance of a conventional PI control. A numerical model based on MATLAB/Simulink and a commercial aero-elastic code were constructed for the target wind turbine, and the new control technique was applied to the numerical model to verify the effect through simulation. For the simulation, the performance data were compared after applying the PI, LQR, and LQR-PI control algorithms to the same wind speed conditions with and without noise in the generator speed. Also, the simulations were performed in both the transition region and the rated power region. The LQR-PI algorithm was found to reduce the standard deviation of the generator speed by more than 20% in all cases regardless of the noise compared with the PI algorithm. As a result, the proposed LQR-PI control increased the stability of the wind turbine in comparison with the conventional PI control.

scholarly journals 87ONE-STEP VERSUS TWO-STEP VITRIFICATION AND IN-STRAW DILUTION OF IN VITRO-PRODUCED BOVINE EMBRYOS

2004 ◽  
Vol 16 (2) ◽  
pp. 165
Author(s):  
L.F. Campos-Chillon ◽  
D.J. Walker ◽  
J.F. De La Torre-Sanchez
Keyword(s):  
Least Square ◽  
Bovine Embryos ◽  
Step Method ◽  
Slow Cooling ◽  
Standard Procedures ◽  
Step Procedure ◽  
Main Effect ◽  
One Step ◽  
The One

Slow-cooling techniques are widely used in cryopreservation of bovine embryos. We have previously developed a simple, two-step vitrification technique for direct transfer in the field; however, simplification to one-step vitrification would be attractive. Therefore, factorial combinations of two techniques (one-step and two-step) and two post-thaw temperatures until culture (24 and 37°C) were studied. Blastocysts (n=220) sired by two bulls were obtained in vitro in four replicates. Briefly, oocytes were aspirated from 2–8-mm follicles of ovaries obtained at a slaughterhouse, matured, fertilized and cultured in vitro with standard procedures using chemically defined media (CDM1/2 or G1/2). Two-step embryos were transferred in 1μL into 1mL of V1-CDM (5M ethylene glycol (EG) in HEPES-buffered holding medium (HCDM2)), and one-step embryos into a 7-μL droplet of V2-CDM (7M EG, 0.5M galactose and 18% w/v Ficoll 70 in HCDM2) for 3min at 24°C. Next, embryos for the two-step method were moved in 1μL into a 7μL droplet of V2-CDM at 24°C. Droplets containing embryos (one or two-step) were loaded into 0.25-mL straws preloaded with a 1-cm column of D-HCDM (0.5M galactose in HCDM2), then 0.5cm air, and then 7cm of D-HCDM followed by 0.5cm air. The column containing the embryos (0.5cm (7μL)) was followed with 0.5cm air and 1cm of D-HCDM. Straws were heat-sealed and plunged vertically, sealed end first, into liquid nitrogen just covering the embryo, and the rest of the straw was then slowly immersed. The time from loading to plunging was 40–50s. Straws were thawed in air (24°C) for 10s and then in water horizontally at 37°C until ice disappeared. Straws were gently shaken to mix the columns; then, after 5min at 24 or 37°C, embryos were expelled and cultured in CDM2+5% FCS. Re-expansion and hatching rates were evaluated 48 h post thaw. Data (Table 1) were calculated as a percentage of non-vitrified controls for respective replicates (control means: re-expansion 87%; hatching 74%) and analyzed by ANOVA. There were no main effects of post-thawing temperature (P>0.1), indicating that, after thawing, embryos can be kept at room or body temperature. Also, main effect means for re-expansion and hatching for one-step or two-step addition of cryoprotectant were similar (P>0.1), but there was a tendency for higher survival for the two-step procedure. Further refinements of the one-step technique including EG concentrations, embryological stages and equilibration times should be studied. Table 1 Main effect means (least-square means±SEM) of vitrified embryos (% of non-vitrified controls)

Performance of Gas Turbine Power Plants Controlled by One Step Ahead Adaptive Technique

2000 ◽  
Author(s):  
L. Dambrosio ◽  
S. M. Camporeale ◽  
B. Fortunato
Keyword(s):  
Gas Turbine ◽  
Control Algorithm ◽  
Control Technique ◽  
Electric Load ◽  
Control Effort ◽  
Controlled System ◽  
Control Scheme ◽  
One Step ◽  
Heavy Duty Gas Turbine ◽  
The One

The One Step Ahead Controllers represent a branch of the Minimum Prediction Error Adaptive Controllers. They combine the parameter estimation of the controlled system model with a particular control scheme; therefore, they are especially suitable for non-linear and time-varying systems. Since the estimated parameters are updated at each time step (by using the sampled data), these methods can be adopted for real-time applications. Consequently, the One Step Ahead Controllers do not require the knowledge of the dynamic characteristics of the controlled system (e.g. state space systems or transfer functions). The One Step Ahead Adaptive (OSAA) algorithm combines the Least Square Algorithm (LSA) parameter estimator with a Deterministic Auto-Regressive Moving Average (DARMA) control scheme. The DARMA model can be characterized with a different number of time steps in the past (order of the estimated model) in relation to the dynamic feature of the controlled system. Sometimes, an excessive control effort could arise, caused by sudden variations of the electric load. In order to reduce this control action, the OSAA control technique has been applied also in Weighted fashion. The Weighted One Step Ahead Adaptive (WOSAA) control algorithm considers a penalty associated with the control effort by use an appropriate cost function. In this way, the control variable does not assume too large values, even when the Gas Turbine undergoes sudden changes in the external load. As a consequence, the robustness and the stability features of the WOSAA control system are increased with respect to the OSAA algorithm. The proposed techniques have been applied to a single shaft heavy-duty gas turbine (WOSAA) and to a double-shaft aero-derivative gas turbine (OSAA). They have been tested in Single-Input Single Output (SISO) mode. In the simulation tests, the plant is assumed to undergo sudden variations of the electric load. Second order schemes of the OSAA estimated model have been derived and applied to the double-shaft aero-derivative gas turbine. The results show that the OSAA control technique, applied to the double-shaft aero-derivative gas turbine, effectively counteracts the load reduction with limited overshoot in the controlled variables and, introducing an integral correction, with a negligible static error. On the other hand, the WOSAA control algorithm is able to efficiently regulate the single shaft heavy-duty gas turbine, and to counteract the sudden variations of the electric load, with reduced control effort.

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