Secondary Path Identification Research Articles

Fractional-Order Least-Mean-Square-Based Active Control for an Electro–Hydraulic Composite Engine Mounts

For the vibration of automobile powertrain, this paper designs electro–hydraulic composite engine mounts. Subsequently, the dynamic characteristics of the hydraulic mount and the electromagnetic actuator were analyzed and experimentally studied separately. Due to the strong nonlinearity of the hybrid electromechanical engine mount, a Fractional-Order Least-Mean-Square (FGO-LMS) algorithm was proposed to model its secondary path identification. To validate the vibration reduction effect, a rapid control prototype test platform was established, and vibration active control experiments were conducted based on the Multiple–Input Multiple–Output Filter-x Least-Mean-Square (MIMO-FxLMS) algorithm. The results indicate that, under various operating conditions, the vibration transmitted to the chassis from the powertrain was significantly suppressed.

A Simplified Frequency-Domain Feedback Active Noise Control Algorithm

When the adaptive filter length is increased, the calculation complexity increases rapidly because the relationship between the calculation and the adaptive filter length N contains a power function with no secondary path identification algorithm. Under the basic premise of unreduced noise reduction, herein, a simplified frequency-domain feedback active noise control algorithm is proposed. To reduce the computation complexity, the total delay is adopted as the estimated secondary path; the filtered reference signal is produced in the frequency domain by using multiplication to replace convolution calculation in the time domain and then updating the adaptive filter coefficients in the frequency domain. Therefore, the computational complexity has a logarithmic function with the increased adaptive filter length in the proposed algorithm. If the adaptive filter length is 512, the existing WSMANC algorithm’s calculation is 271,360 real number multiplications, while that of the proposed algorithm is only 38,912 real number multiplications. To verify the proposed algorithm’s stability, convergence speed, and noise reduction, the single-frequency noise, narrowband white noise, and narrowband pink noise, respectively, are used as the primary noise types in the simulations. The results show that (1) the proposed SFDFBANC algorithm can obtain similar noise reduction performance to existing algorithm, (2) the convergence rate is faster than existing algorithm, and (3) if the adaptive filter length is more than 64, the proposed algorithm exhibits a lower computational complexity.

An adaptive algorithm for acoustic feedback compensation and secondary path identification of an active noise control system.

An adaptive variable step-size algorithm is proposed in this paper to address the impact of the real-time acoustic feedback and the real-time secondary path identification on the overall noise reduction performance of an active noise control system. An automated adjustment weight factor is introduced in the algorithm to accelerate the convergence of the acoustic feedback path as well as the secondary path identification, and to prevent possible system divergence. It is shown in this study that the proposed algorithm can resolve the trade-off between a fast convergence and a low misalignment of the virtual and the actual control paths typically found in conventional algorithms. An optimized control structure is also proposed in the study by enabling an adaptive gain adjustment based on the output of the auxiliary filter to enhance the practicality of the control system. The effectiveness of the algorithm is tested using two simulated multi-component signals and a broadband noise signal, and the results confirm that the proposed algorithm can achieve a good noise reduction with only a few iterations.

Dual-mode active noise control system with on-line identification of secondary path

Dual-mode active noise control system with on-line identification of secondary path

Genetic Algorithm-Based Adaptive Active Noise Control Without Secondary Path Identification

Genetic Algorithm-Based Adaptive Active Noise Control Without Secondary Path Identification

Improved stability performance of a feedback active noise control using a Steiglitz-McBride adaptive notch filter and robust secondary path identification based on variable step size Griffiths LMS algorithm

A stable feedback active noise control (FBANC) system with an improved performance in a broadband disturbance environment is proposed in this article. This is achieved by using a Steiglitz-McBride adaptive notch filter (SM-ANF) and robust secondary path identification (SPI) both based on variable step size Griffiths least mean square (LMS) algorithm. The broadband disturbance severely affects not only FBANC input synthesized but also the SPI.TheSM-ANFestimated signal has narrowband component that is utilized for the FBANC input synthesis. Further, the SM-ANF error has broadband component utilized to get the desired signal for SPI. The use of variable step size Griffiths gradient LMS algorithm for SPI enables the removal of broadband disturbance and non-stationary disturbance from the available desired signal for better SPI. For a narrowband noise field, the proposed FBANC improves the convergence rate significantly (20 times) and the noise reduction from 10 dB to 15 dB (50%improvement) over the conventional FBANC (without SM-ANF and variable step size Griffiths LMS adaptation for SPI).

Inspection of the secondary path modeling in active noise control from the viewpoint of channel identification in stereo acoustic echo cancellation.

The similarity between the identification of secondary path in feedforward active noise control and the channel identification in stereo echo cancellation is revealed in this paper. Accordingly, the convergence behavior of the ANC system can be analyzed by investigating the joint auto-correlation matrix of the reference and the filtered reference signal. It is proved that the straightforward secondary path modeling can be carried out without the injection of any additive noise as long as the control filter is of a sufficiently long length. Furthermore, by taking advantage of the time-varying characteristic of the control filter, effective modeling of the secondary path can even be achieved without any restriction on the control filter length.

An improved narrowband active noise control system without secondary path modelling based on the time domain

Several secondary path, acoustic noise cancellation modelling causes the problems to increase the complexity of ANC implementation, reduction of performance caused by modelling error and requirement of auxiliary noise for secondary path modelling. The acoustic noise generated is further compounded by using secondary path identification which makes the system complex. There are several available ANC algorithms that do not require secondary path estimation for modifying the FxLMS algorithms. Due to drawbacks such as slow convergence speed and, complexity of the phase shift mechanism, a novel approach with no secondary path modelling is adopted, in which the adaptation stability is guaranteed by switching the sign of the step size. It is combined with the online tuneable delay of the reference signal to significantly improve the adaptation convergence properties of the algorithm. A new mathematical modelling has been proposed to reduce the acoustic noise that increases the convergence criteria.

An improved narrowband active noise control system without secondary path modelling based on the time domain

Several secondary path, acoustic noise cancellation modelling causes the problems to increase the complexity of ANC implementation, reduction of performance caused by modelling error and requirement of auxiliary noise for secondary path modelling. The acoustic noise generated is further compounded by using secondary path identification which makes the system complex. There are several available ANC algorithms that do not require secondary path estimation for modifying the FxLMS algorithms. Due to drawbacks such as slow convergence speed and, complexity of the phase shift mechanism, a novel approach with no secondary path modelling is adopted, in which the adaptation stability is guaranteed by switching the sign of the step size. It is combined with the online tuneable delay of the reference signal to significantly improve the adaptation convergence properties of the algorithm. A new mathematical modelling has been proposed to reduce the acoustic noise that increases the convergence criteria.

Bio-inspired heuristics hybrid with interior-point method for active noise control systems without identification of secondary path

In this study, hybrid computational frameworks are developed for active noise control (ANC) systems using an evolutionary computing technique based on genetic algorithms (GAs) and interior-point method (IPM), following an integrated approach, GA-IPM. Standard ANC systems are usually implemented with the filtered extended least mean square algorithm for optimization of coefficients for the linear finite-impulse response filter, but are likely to become trapped in local minima (LM). This issue is addressed with the proposed GA-IPM computing approach which is considerably less prone to the LM problem. Also, there is no requirement to identify a secondary path for the ANC system used in the scheme. The design method is evaluated using an ANC model of a headset with sinusoidal, random, and complex random noise interferences under several scenarios based on linear and nonlinear primary and secondary paths. The accuracy and convergence of the proposed scheme are validated based on the results of statistical analysis of a large number of independent runs of the algorithm.

Data driven design of tonal noise feedback cancellers

This paper emphasizes the design methodology for active tonal noise feedback cancellers starting from data collected on the system. To design such control systems, an accurate dynamic model of the system is necessary. Physical modeling can provide qualitative results but fails to yield enough accurate models for control design. The main point in the methodology is concerned by the identification of primary path (noise propagation) and secondary path (compensation) models from data. The procedure is investigated in details starting with transfer functions’ order estimations, continuing with parameters estimation and model’s validation. The second aspect is the design of a noise canceller using the Internal Model Principle and the sensitivity function shaping in order to reduce the ”water-bed” effect. The estimated model’s quality for control design is illustrated by the experimental performance of a tonal noise feedback canceller implemented on a test bench.

Improved DCT domain variable step-size Griffith's LMS algorithm based active noise control using observation noise cancellers for secondary path identification

This paper proposes two improved DCT domain active noise control (ANC) systems using observation noise cancellers (NC) for the secondary path identification (SPI). This is achieved by identifying the main path by an adaptive filter which is based on input orthogonalisation by a DCT. Further for the proposed first ANC system, the available input orthogonal components are beneficially used in estimating the observation noise component required for the adaptive NC for the SPI. For the proposed second ANC system, the NC is based on an observation noise robust discrete cosine transform domain variable step-size Griffiths LMS (TVGLMS) algorithm. In both ANC systems, the NC enables improved SPI and this indirectly enables an improved ANC convergence performance. The second ANC system uses a noise robust variable step-size and gradient for its NC used in deriving the desired signal for SPI of an ANC system with TVGLMS noise canceller. The smoothed ensemble average square error (SEASE) is reduced by an additional 5 dB and its convergence rate is about 1.5 times faster over that of an ANC which uses only orthogonal components of its input. The performance of basic first ANC which uses input orthogonalisation only for its main path identification is very poor as its noise reduction is only -2.5 dB.

Improved DCT domain variable step-size Griffith's LMS algorithm based active noise control using observation noise cancellers for secondary path identification

Improved DCT domain variable step-size Griffith's LMS algorithm based active noise control using observation noise cancellers for secondary path identification

A modified adaptive filtering algorithm with online secondary path identification used for suppressing gearbox vibration

We determined the actuator location based on the dynamic modal of gear shaft, and analyzed the feasibility of a modified filtered-x least mean square algorithm with online secondary path identification. The proposed adaptive controller is designed to drive the actuators for preventing the vibration caused by gear backlash from a gear pair passing to the external gear housing structure. For the vital identification system, a changed identification input with error energy is presented to reduce the impact of additive random noise on the whole system. To ensure a realistic assessment of the proposed control strategy, numerical studies were implemented for a gearbox used by NASA-GRC. The simulation results validate the efficiency of the proposed approach through promising vibration control results that will guide future experimental work.

A Higher-Order Spectra Based Method of On-Line Secondary Path Model Identification for Active Noise Control Systems

The aim of this paper is to present a method of nonparametric and parametric secondary path model identification for adaptive active noise control systems with low-power non-Gaussian excitations of the form of a higher-order discrete-time multisine random process and data processing based on cross-higher-order spectra. Properties of the discussed method are illustrated by simulation experiments devoted to secondary path identification for feedforward and feedback active noise control systems. Its robustness to nonlinear distortions implied by data acquisition system and adaptation procedure is proved.

Active control of pressure pulsation in a switched inertance hydraulic system

The nature of digital hydraulic systems may cause severe pressure pulsation problems. For example, switched inertance hydraulic systems can be used to adjust or control flow and pressure by a means that does not rely on dissipation of power, but they have noise problems because of the pulsed nature of the flow. An effective method to reduce the noise is needed that does not impair the system performance and efficiency. This article reports on an initial investigation of an active attenuator for pressure pulsation cancellation in a switched inertance hydraulic system. Using the designed noise attenuator, the pressure pulsation can be decreased effectively by superimposing an anti-phase control signal. A high-performance piezoelectric valve was selected and used as the secondary path actuator in terms of its fast response and wide bandwidth. Adaptive notch filters with the filtered-X least mean square algorithm were applied for pressure pulsation attenuation, while a frequency-domain least mean square filter was used for secondary path identification. A ‘switched inertance hydraulic system’ in a flow booster configuration was used as the test rig. Experimental results show that excellent cancellation was achieved using the proposed method, which has several advantages over passive noise control systems, being effective for a wide range of frequencies without impairing the system’s dynamic response. The method is a very promising solution for pressure pulsation cancellation in hydraulic systems with severe noise or vibration problems.

Analysis and implementation of improved multi-input multi-output filtered-X least mean square algorithm for active structural vibration control

An improved multi-input multi-output filtered-X least mean square-based vibration control algorithm is proposed to solve the reference signal extraction problem for active vibration control system. The reference signal is constructed by the controller parameters and the vibration residual signal extracted directly from the vibrating structure, which is related to the external disturbance signal. Meanwhile, an FIR filter is adopted for online identification by adding white noise signal to the controller output as identification input signal; the identified model is substituted into the control algorithm, and the online secondary path identification is realized. Thus, the practical application problem of filtered-X least mean square algorithm is solved. The simulations and experiments show that the proposed algorithm is reliable and effective with good control performance. Copyright © 2013 John Wiley & Sons, Ltd.

Feedback active noise control based on forward–backward LMS predictor

In this paper, a new feedback active noise control (FBANC) system based on forward–backward error LMS (FBLMS) predictor is proposed. The misadjustment of the FBLMS predictor is about half that of the forward error LMS (FLMS) predictor. The new ANC system employs FBLMS predictors both for its main path (MP) predictor and for the noise canceler (NC) for the secondary path (SP) identification (SPI). To realize the MP predictor based on the FBLMS concept, a new FXLMS structure is proposed. But for the NC for the SPI, the FBLMS predictor is directly used. The MP predictor based on FBLMS reduces its misadjustment. Further the use of FBLMS predictor for the NC, as it gives a good prediction of primary noise component in the error (residual noise), improves the SNR for SPI. Thus, the improved SP estimate and the reduced misadjustment for the MP predictor achieved result in a significantly better overall noise reduction (of about 8 dB) over the ANC that uses the MP predictor and noise canceler for SPI, both based only on the forward error LMS algorithm. The computational load for the proposed algorithm is about twice that of FBANC that uses only forward error.

Particle Swarm Optimization Based Active Noise Control Algorithm Without Secondary Path Identification

In this paper, particle swarm optimization (PSO) algorithm, which is a nongradient but simple evolutionary computing-type algorithm, is proposed for developing an efficient active noise control (ANC) system. The ANC is conventionally used to control low-frequency acoustic noise by employing a gradient-optimization-based filtered-X least mean square (FXLMS) algorithm. Hence, there is a possibility that the performance of the ANC may be trapped by local minima problem. In addition, the conventional FXLMS algorithm needs prior identification of the secondary path. The proposed PSO-based ANC algorithm does not require the estimation of secondary path transfer function unlike FXLMS algorithm and, hence, is immune to time-varying nature of the secondary path. In this investigation, a small modification is incorporated in the conventional PSO algorithm to develop a conditional reinitialized PSO algorithm to suit to the time-varying plants of the ANC system. Systematic computer simulation studies are carried out to evaluate the performance of the new PSO-based ANC algorithm.

Active Noise Cancellation Without Secondary Path Identification by Using an Adaptive Genetic Algorithm

This paper presents an adaptive genetic algorithm (AGA) for an active noise control (ANC) system. The conventional ANC system often implements the filtered extended least mean square (FXLMS) algorithm to update the coefficients of the linear finite-impulse response (FIR) and nonlinear Volterra filters, owing to its simplicity; meanwhile, the FXLMS algorithm may converge to local minima. In this paper, the FXLMS algorithm is replaced with an AGA to prevent the local minima problem. Additionally, the proposed AGA method does not require identifying the secondary path for the ANC, explaining why no plant measurement is necessary when designing an AGA-based ANC system. Simulation results demonstrate that the effectiveness of the proposed AGA method can suppress the nonlinear noise interference under several situations without clearly identifying the secondary path.