scholarly journals Grid-Tied Distribution Static Synchronous Compensator for Power Quality Enhancement Using Combined-Step-Size Real-Coefficient Improved Proportionate Affine Projection Sign Algorithm

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 197
Author(s):  
Arobinda Dash ◽  
Durgesh Prasad Bagarty ◽  
Prakash Kumar Hota ◽  
Manoj Kumar Sahu ◽  
Twinkle Hazra ◽  
...  
Keyword(s):  
Steady State ◽  
Convergence Rate ◽  
Adaptive Filter ◽  
Reactive Power ◽  
Real Coefficient ◽  
Step Size ◽  
Static Synchronous Compensator ◽  
Affine Projection ◽  
Three Phase ◽  
Sign Algorithm

A control structure design of a three-phase three-leg four-wire grid-tied Distribution Static Synchronous Compensator (DSTATCOM) based on a combined-step-size real-coefficient improved proportionate affine projection sign algorithm (CSS-RIP-APSA) has been presented. The three-phase four-wire DSTATCOM is used for reactive power compensation along with harmonic current minimization. This strategy also helps in load balancing and neutral current compensation. The affine projection sign algorithm (APSA) is a member of the adaptive filter family, which has a slow convergence rate. The conventional adaptive filter deals with the trade-off between the convergence rate and the steady-state error. In the proposed algorithm, the RIP-APSA adaptive filter with two different step sizes has been designed to decrease the computational burden while achieving the advantages of a fast convergence rate and reduced steady-state error. The proposed controller also makes the inverter function a shunt compensator. The controller primarily evaluates the fundamental weight component of distorted load currents. The aim of the proposed system is to compensate for reactive power and to ensure unity power factor during the faulty conditions as well as for unbalancing grid conditions. The proposed control algorithm of the grid-tied DSTATCOM works effectively on the laboratory prototype as verified from the experimental results.

scholarly journals A Variable Step Size for Acoustic Echo Cancellation Using Normalized Sub band Adaptive Filter

2013 ◽  
Vol 6 (3) ◽  
pp. 449-455
Author(s):  
Harjeet Kaur Ojhla ◽  
Dr. Rajneesh Talwar ◽  
Jyoti Darekar
Keyword(s):  
Steady State ◽  
Convergence Rate ◽  
Adaptive Filter ◽  
Weight Vector ◽  
Variable Step Size ◽  
Mean Square ◽  
Step Size ◽  
Variable Step ◽  
Subband Adaptive Filter ◽  
Normalized Subband Adaptive Filter

Numerous various step size normalized least mean square (VSS-NLMS)Algorithms have been derived to solve the problem of fast convergence rate and low mean square error.Here we find out the ways to control the step size. A normalized subband adaptive filter algorithm uses a fixed and variable step size, which is chosen as a trade-off between the steady-state error and the convergence rate. A variable step size for normalized subband adaptive filter is derived by minimizing the mean-square deviation between the optimal weight vector and the estimated weight vector at each instant of time. The variable step size is presented in terms of error variance. Therefore, we verify thedifferent  algorithmseither they are capable of tracking in stationary and non-stationary environments. The results show good tracking ability and low misalignment of the algorithm in system identification. Parameters are tracking, steady state errors, and misalignment, environment, step size.

scholarly journals Modified Combined-Step-Size Affine Projection Sign Algorithms for Robust Adaptive Filtering in Impulsive Interference Environments

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 385
Author(s):  
Guoliang Li ◽  
Hongbin Zhang ◽  
Ji Zhao
Keyword(s):  
Computational Complexity ◽  
System Identification ◽  
Taylor Series Expansion ◽  
Step Size ◽  
Affine Projection ◽  
Active Function ◽  
Independent Variable ◽  
Robust Adaptive ◽  
Sign Algorithm ◽  
Extra Parameter

In this paper, to further improve the filtering performance and enhance the poor tracking capability of the conventional combined step-size affine projection sign algorithm (CSS-APSA) in system identification, we propose a simplified CSS-APSA (SCSS-APSA) by applying the first-order Taylor series expansion to the sigmoidal active function (of which the independent variable is symmetric) of CSS-APSA. SCSS-APSA has lower computational complexity, and can achieve comparable, or even better filtering performance than that of CSS-APSA. In addition, we propose a modification of the sigmoidal active function. The modified sigmoidal active function is a form of scaling transformation based on the conventional one. Applying the modified function to the CSS-APSA, we can obtain the modified CSS-APSA (MCSS-APSA). Moreover, the extra parameter of MCSS-APSA provides the power to accelerate the convergence rate of CSS-APSA. Following the simplification operations of SCSS-APSA, the computational complexity of MCSS-APSA can also be reduced. Therefore, we get the simplified MCSS-APSA (SMCSS-APSA). Simulation results demonstrate that our proposed algorithms are able to achieve a faster convergence speed in system identification.

scholarly journals Robust Normalized Subband Adaptive Filter Algorithm with a Sigmoid-Function-Based Step-Size Scaler and Its Convex Combination Version

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zijie Shen ◽  
Lin Tang ◽  
Li Yang
Keyword(s):  
Steady State ◽  
Cost Function ◽  
Adaptive Filter ◽  
Convex Combination ◽  
Sigmoid Function ◽  
Function Structure ◽  
Step Size ◽  
Subband Adaptive Filter ◽  
Norm Constraint ◽  
Normalized Subband Adaptive Filter

In this paper, by inserting the logarithm cost function of the normalized subband adaptive filter algorithm with the step-size scaler (SSS-NSAF) into the sigmoid function structure, the proposed sigmoid-function-based SSS-NSAF algorithm yields improved robustness against impulsive interferences and lower steady-state error. In order to identify sparse impulse response further, a series of sparsity-aware algorithms, including the sigmoid L0 norm constraint SSS-NSAF (SL0-SSS-NSAF), sigmoid step-size scaler improved proportionate NSAF (S-SSS-IPNSAF), and sigmoid L0 norm constraint step-size scaler improved proportionate NSAF (SL0-SSS-IPNSAF), is derived by inserting the logarithm cost function into the sigmoid function structure as well as the L0 norm of the weight coefficient vector to act as a new cost function. Since the use of the fix step size in the proposed SL0-SSS-IPNSAF algorithm, it needs to make a trade-off between fast convergence rate and low steady-state error. Thus, the convex combination version of the SL0-SSS-IPNSAF (CSL0-SSS-IPNSAF) algorithm is proposed. Simulations in acoustic echo cancellation (AEC) scenario have justified the improved performance of these proposed algorithms in impulsive interference environments and even in the impulsive interference-free condition.

scholarly journals Normalized Combinations of Proportionate Affine Projection Sign Subband Adaptive Filter

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Tong An ◽  
Tao Zhang ◽  
Yanzhang Geng ◽  
Haiquan Jiao
Keyword(s):  
Steady State ◽  
Adaptive Filter ◽  
Future Research ◽  
L1 Norm ◽  
Power Normalization ◽  
Affine Projection ◽  
Mixing Parameter ◽  
Subband Adaptive Filter ◽  
Accelerated Gradient ◽  
The Cost

The proportionate affine projection sign subband adaptive filter (PAP-SSAF) has a better performance than the affine projection sign subband adaptive filter (AP-SSAF) when we eliminate the echoes. Still, the robustness of the PAP-SSAF algorithm is insufficient under unknown environmental conditions. Besides, the best balance remains to be found between low steady-state misalignment and fast convergence rate. In order to solve this problem, we propose a normalized combination of PAP-SSAF (NCPAP-SSAF) based on the normalized adaption schema. In this paper, a power normalization adaptive rule for mixing parameters is proposed to further improve the performance of the NCPAP-SSAF algorithm. By using Nesterov’s accelerated gradient (NAG) method, the mixing parameter of the control combination can be obtained with less time consumed when we take the l1-norm of the subband error as the cost function. We also test the algorithmic complexity and memory requirements to illustrate the rationality of our method. In brief, our study contributes a novel adaptive filter algorithm, accelerating the convergence speed, reducing the steady-state error, and improving the robustness. Thus, the proposed method can be utilized to improve the performance of echo cancellation. We will optimize the combination structure and simplify unnecessary calculations to reduce the algorithm’s computational complexity in future research.

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