LMS-Based Notch Filter for AMB Unbalance Compensation Control

2012 ◽  
Vol 614-615 ◽  
pp. 498-503
Author(s):  
Huai Liang Li ◽  
Yu Sheng Wang ◽  
Yang Zhang
Keyword(s):  
Mutual Influence ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Force Balance ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Displacement Signal ◽  
Amb System

The stability and other properties of the active magnetic bearing system influenced by periodic vibration impact with the same frequency of the rotor speed are analyzed. Firstly, on the basis of the periodic displacement signal, the filtering theory of least mean square (LMS) algorithm and the deficiency of LMS algorithm in the application of AMB system, such as frequency mismatch, the relation of step-size and the frequency of displacement signal, and the mutual influence among the step-size length and frequency of the rotor and the PID controller coefficient, etc are studied. And then, a new strategy of variable step-size and real-time switching control with LMS and PID combination to filter the sinusoidal displacement signal to achieve adaptive force balance compensation is proposed. Finally, the feasibility of the new method for the adaptive compensation of the vibration of AMB system is tested by the experimental results.

Application of Improved LMS Adaptive Algorithm in Acoustics Pyrometry

2014 ◽  
Vol 672-674 ◽  
pp. 2025-2028
Author(s):  
Shi Ping Zhang ◽  
Guo Qing Shen ◽  
Lian Suo An
Keyword(s):  
Temperature Measurement ◽  
Discrete Cosine Transform ◽  
Time Delay Estimation ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Boiler Furnace ◽  
Cosine Transform ◽  
Variable Step

Acoustic pyrometry is a comparatively advanced method of temperature measurement developed in recent years, which possesses the essential characteristics of traditional temperature measurement approach. Considering the interferences, like strong background noise, reverberation and so on, in boiler furnace, the LMS (least mean square) adaptive filter algorithm should be improved to meet certain environment above. In order to make the LMS algorithm have the characteristic of fast convergence and small steady state error, an improved, power-normalized and variable step-size discrete cosine transform LMS algorithm is proposed, which combines the power-normalized discrete cosine transform LMS algorithm with the variable step size LMS algorithm that uses the sliding forgetting-weighted window. The time delay estimation simulation in the strong-noise environment verifies the improved DCT-MVSS LMS algorithm can achieve good performance.

scholarly journals New feedforward filtered-x least mean square algorithm with variable step size for active vibration control

2018 ◽  
Vol 38 (1) ◽  
pp. 187-198 ◽  
Author(s):  
Yubin Fang ◽  
Xiaojin Zhu ◽  
Zhiyuan Gao ◽  
Jiaming Hu ◽  
Jian Wu
Keyword(s):  
Vibration Control ◽  
Active Vibration Control ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Mean Square ◽  
Least Mean Square ◽  
Step Size ◽  
Large Step ◽  
Variable Step ◽  
Active Vibration

The step size of least mean square (LMS) algorithm is significant for its performance. To be specific, small step size can get small excess mean square error but results in slow convergence. However, large step size may cause instability. Many variable step size least mean square (VSSLMS) algorithms have been developed to enhance the control performance. In this paper, a new VSSLMS was proposed based on Kwong’s algorithm to evaluate the robustness. The approximate analysis of dynamic and steady-state performance of this developed VSSLMS algorithm was given. An active vibration control system of piezoelectric cantilever beam was established to verify the performance of the VSSLMS algorithms. By comparing with the current VSSLMS algorithms, the proposed method has better performance in active vibration control applications.

scholarly journals Efficient adaptive noise cancellation techniques in an IOT Enabled Telecardiology System

2018 ◽  
Vol 7 (2.17) ◽  
pp. 74 ◽  
Author(s):  
Asiya Sulthana ◽  
Md Zia Ur Rahman
Keyword(s):  
Health Care ◽  
Monitoring System ◽  
Mean Squared Error ◽  
Lms Algorithm ◽  
Frequency Resolution ◽  
Variable Step Size ◽  
Mean Square ◽  
Least Mean Square ◽  
Step Size ◽  
Health Care Monitoring

An increasing number of elderly­­­­ and disabled people urge the need for a health care monitoring system which has the capabilities for analyzing patient health care data to avoid preventable deaths. Medical Telemetry is becoming a key tool in assisting patients living remotely where a “Real-time Remote Critical Health Care Monitoring System” (RRCHCMS) can be utilized for the same. The RRCHCMS is capable of receiving and transmitting data from a remote location to a location that has the capability to diagnose the data and affect decision making and further providing assistance to the patient. During the cardiac analysis, several artifacts solidly affect the ST segment, humiliate the signal quality, frequency resolution, and results in large amplitude signals in ECG that simulate PQRST waveform and cover up the miniature features that are useful for clinical monitoring and diagnosis. In this paper, several leaky based adaptive filter structures for cardiac signal improvement are discussed. The Circular Leaky Least Mean Square (CLLMS) algorithm being the steepest drop strategy for dropping the mean squared error gives a better result in comparison with the Least Mean Square (LMS) algorithm. To enlarge the filtering ability some variants of LMS, Normalized Least Mean Square (NLMS), CLLMS, Variable Step Size CLLMS (VSS-CLLMS) algorithms are used in both time domain (TD) and frequency domain (FD). At last, we applied this algorithm on cardiac signals occurred due to MIT-BIH database. The performance of CLLMS algorithm is better compared to LLMS counterparts in conditions of Signal to Noise Ratio Improvement (SNRI), Excess Mean Square Error (EMSE) and Misadjustment (MSD). When compared to all other algorithms VSS-CLLMS gives superior SNRI. These values are 13.5616dB and 13.7592dB for Baseline Wander (BW) and Muscle Artifact (MA) removal.  

A Variable Step Size LMS Based on Sparsity for System Identification

2013 ◽  
Vol 475-476 ◽  
pp. 1060-1066
Author(s):  
X.Q. Chen ◽  
Hua Ju ◽  
Wei Fan ◽  
W.G. Huang ◽  
Z.K. Zhu
Keyword(s):  
Steady State ◽  
System Identification ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Practical Applications ◽  
Variable Step ◽  
Size Adjustment ◽  
State Error

In many practical applications, the impulse responses of the unknown system are sparse. However, the standard Least Mean Square (LMS) algorithm does not make full use of the sparsity, and the general sparse LMS algorithms increase steady-state error because of giving much large attraction to the small factor. In order to improve the performance of sparse system identification, we propose a new algorithm which introduces a variable step size method into the Reweighted Zero-Attracting LMS (RZALMS) algorithm. The improved algorithm, whose step size adjustment is controlled by the instantaneous error, is called Variable step size RZALMS (V-RZALMS). The variable step size leads to yielding smaller steady-state error on the premise of higher convergent speed. Moreover, the sparser the system is, the better the V-RZALMS performs. Three different experiments are implemented to validate the effectiveness of our new algorithm.

DCT-BASED VARIABLE STEP SIZE GRIFFITHS' LMS ALGORITHM FOR RANDOM NOISE CANCELLATION IN ECGs

2012 ◽  
Vol 12 (05) ◽  
pp. 1250025
Author(s):  
VEENA N. HEGDE ◽  
RAVISHANKAR DEEKSHIT ◽  
P. S. SATYANARAYANA
Keyword(s):  
Random Noise ◽  
Noise Cancellation ◽  
Lms Algorithm ◽  
Frequency Resolution ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Low Leakage ◽  
Variable Step ◽  
The Time Domain

This paper presents a new random noise cancellation technique for cancelling muscle artifact effects from ECG using ALE in the transformed domain. For this a transform domain variable step size griffith least mean square (TVGLMS) algorithm is proposed. The technique is based on the adaptation of the gradient of the error surface. The method frees both the step size and the gradient from observation noise and reduces the gradient mis-adjustment error. The sluggishness introduced due to the averaging of the gradient in the time domain is overcome by the transformed domain approach. The proposed algorithm uses a discrete cosine transform (DCT)-based signal decomposition due to its improved frequency resolution compared to a discrete Fourier transform (DFT). Furthermore, as the data used symmetrical, DCT usage results in low leakage (bias and variance). The performance of the proposed method has been tested on ECG signals combined with WGN, extracted from MIT database, and compared with several existing techniques like LMS, NLMS, and VGLMS.

An Improved Variable Step Size LMS Algorithm Based on Sigmoid Function

2014 ◽  
Vol 602-605 ◽  
pp. 3593-3596 ◽  
Author(s):  
Li Liu ◽  
Qiong Wang ◽  
Hong Ping Bai
Keyword(s):  
Lms Algorithm ◽  
Variable Step Size ◽  
Sigmoid Function ◽  
Least Mean Square ◽  
Error Performance ◽  
Step Size ◽  
Channel Tracking ◽  
Channel Characteristics ◽  
Variable Step ◽  
Improved Algorithm

LMS (Least Mean Square) algorithm performance is analyzed. Then something has been done on SVSLMS that is an improved variable step size LMS algorithm based on sigmoid function. The improved algorithm has faster convergence rate, stronger channel tracking capability, better anti-noise performance and steady-state error performance compared with SVSLMS, for it makes parameters and change with channel characteristics. Theoretical analysis is the same as computer simulation results, which proves that the performance of the improved algorithm is superior to SVSLMS algorithm.

A Novel Variable Step-Size LMS Harmonic Detecting Algorithm

2011 ◽  
Vol 464 ◽  
pp. 179-182
Author(s):  
Jian Ning Yang ◽  
Jia Jun Guan ◽  
Yan Min Ning ◽  
Chuan Gu
Keyword(s):  
Time Window ◽  
Tracking Error ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Matlab Simulation ◽  
Step Size ◽  
Load Current ◽  
Grid Load ◽  
Improved Algorithm

This paper proposed a novel adaptive algorithm applied to the harmonic detection that improves the power quality and suppressing grid harmonic. Considering the signal noise ratio (SNR) of the load current is low, the improved algorithm uses the coherent average estimation of the proportion of error signal in the total signal instead of system error to update the step-size, so the step-size only depends on the real system tracking error, and the steady state error is small when the system is close to stable. In addition, the algorithm adopts the time window action of mean estimation to control the influence of past signal on the present one, which produces a big step-size when the system changes. Compared with the fixed step-size least mean square (LMS) algorithm in a grid load current detected by matlab simulation, the improved algorithm has a faster convergence rate, a higher stability precision, and a better performance of anti-noise, the simulation shows the effectiveness of the method.

scholarly journals Variable step-size LMS adaptive filters for CDMA multiuser detection

2004 ◽  
Vol 17 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Karen Egiazarian ◽  
Pauli Kuosmanen ◽  
Ciprian Bilcu
Keyword(s):  
Multiuser Detection ◽  
Adaptive Filters ◽  
Convergence Speed ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Least Mean Square ◽  
Step Size ◽  
Trade Off ◽  
Variable Step ◽  
Code Division Multiple

Due to its simplicity the adaptive Least Mean Square (LMS) algorithm is widely used in Code-Division Multiple access (CDMA) detectors. However its convergence speed is highly dependent on the eigen value spread of the input covariance matrix. For highly correlated inputs the LMS algorithm has a slow convergence which require long training sequences and therefore low transmission speeds. Another drawback of the LMS is the trade-off between convergence speed and steady-state error since both are controlled by the same parameter, the step-size. In order to eliminate these drawbacks, the class of Variable Step-Size LMS (VSSLMS) algorithms was introduced. In this paper, we study the behavior of some algorithms belonging to the class of VSSLMS for training based multiuser detection in a CDMA system. We show that the proposed Complementary Pair Variable Step-Size LMS algorithms highly increase the speed of convergence while reducing the trade-off between the convergence speed and the output error.

Active control for vehicle interior noise using the improved iterative variable step-size and variable tap-length LMS algorithms

2019 ◽  
Vol 67 (6) ◽  
pp. 405-414 ◽  
Author(s):  
Ningning Liu ◽  
Yuedong Sun ◽  
Yansong Wang ◽  
Hui Guo ◽  
Bin Gao ◽  
...  
Keyword(s):  
Steady State ◽  
Noise Control ◽  
Convergence Speed ◽  
Interior Noise ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Vehicle Interior ◽  
Vehicle Interior Noise ◽  
Variable Step

Active noise control (ANC) is used to reduce undesirable noise, particularly at low frequencies. There are many algorithms based on the least mean square (LMS) algorithm, such as the filtered-x LMS (FxLMS) algorithm, which have been widely used for ANC systems. However, the LMS algorithm cannot balance convergence speed and steady-state error due to the fixed step size and tap length. Accordingly, in this article, two improved LMS algorithms, namely, the iterative variable step-size LMS (IVS-LMS) and the variable tap-length LMS (VT-LMS), are proposed for active vehicle interior noise control. The interior noises of a sample vehicle are measured and thereby their frequency characteristics. Results show that the sound energy of noise is concentrated within a low-frequency range below 1000 Hz. The classical LMS, IVS-LMS and VT-LMS algorithms are applied to the measured noise signals. Results further suggest that the IVS-LMS and VT-LMS algorithms can better improve algorithmic performance for convergence speed and steady-state error compared with the classical LMS. The proposed algorithms could potentially be incorporated into other LMS-based algorithms (like the FxLMS) used in ANC systems for improving the ride comfort of a vehicle.

Sign in / Sign up

Export Citation Format

Share Document