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1.
本文提出一种新的基于α稳定分布噪声环境下的自适应滤波算法,这种算法针对变步长自适应滤波算法收敛速度和稳态误差相矛盾的不足,建立了步长μ(n)与误差信号e(n)之间的新的非线性函数关系。该函数能够削弱输入端不相关α稳定分布噪声对步长调整的影响,更好地解决稳态误差与收敛时间之间的矛盾。通过系统辨识仿真结果表明,新的算法α对稳定分布下的尖峰脉冲噪声有较强的韧性,比传统的NLMP算法有更快的参数辨识速度和更小的稳态误差,同时还具有很好地跟踪多时变系统的能力。  相似文献   

2.
An LMS adaptive algorithm with a new step-size control equation   总被引：2，自引：0，他引：2  
In this paper, we introduce a new variable step-size LMS (VSSLMS) adaptive algorithm. The algorithm step-size equations estimate an optimal derived step-size and are controlled by only one parameter. Mean-square performance analysis is provided for zero-mean stationary Gaussian input signal, and a simple expression that predicts the algorithm steady state misadjustment is derived for small step-size fluctuations. The algorithm is compared with other well-known VSSLMS algorithms through simulation experiments, which demonstrate the performance advantages of the proposed algorithm over these algorithms.  相似文献   

3.
Recently, the augmented complex-valued normalized subband adaptive filtering (ACNSAF) algorithm has been proposed to process colored non-circular signals. However, its performance will deteriorate severely under impulsive noise interference. To overcome this issue, a robust augmented complex-valued normalized M-estimate subband adaptive filtering (ACNMSAF) algorithm is proposed, which is obtained by modifying the subband constraints of the ACNSAF algorithm using the complex-valued modified Huber (MH) function and is derived based on CR calculus and Lagrange multipliers. In order to improve both the convergence speed and steady-state accuracy of the fixed step size ACNMSAF algorithm, a variable step size (VSS) strategy based on the minimum mean squared deviation (MSD) criterion is devised, which allocates individual adaptive step size to each subband, fully exploiting the structural advantages of SAF and significantly improving the convergence performance of the ACNMSAF algorithm as well as its tracking capability in non-stationary environment. Then, the stability, transient and steady-state MSD performance of the ACNMSAF algorithm in the presence of colored non-circular inputs and impulsive noise are analyzed, and the stability conditions, transient and steady-state MSD formulas are also derived. Computer simulations in impulsive noise environments verify the accuracy of theoretical analysis results and the effectiveness of the proposed algorithms compared to other existing complex-valued adaptive algorithms.  相似文献   

4.
The conventional logarithm cost-based adaptive filters, e.g., the least mean logarithmic square (LMLS) algorithm, cannot combat impulsive noises at the filtering process. To address this issue, we present a novel robust least mean logarithmic square (RLMLS) algorithm by using a generalized logarithmic cost function. The proposed RLMLS algorithm can provide robustness against impulsive noises with the improvement of filtering accuracy. For theoretical analysis, the mean square analysis of RLMLS is provided in terms of the mean square deviation (MSD) and excess mean-square error (EMSE) with a white Gaussian reference. For further performance improvement in different noises, the variable step-size RLMLS (VSSRLMLS) based on the statistics of error is proposed to improve the convergence rate and steady-state mean square error, simultaneously. Analytical results and superiorities of RLMLS and VSSRLMLS in the context of system identification are supported by simulations from the aspects of filtering accuracy and robustness in Gaussian and impulse noises.  相似文献   

5.
This article proposes an affine-projection-like maximum correntropy (APLMC) algorithm for robust adaptive filtering. The proposed APLMC algorithm is derived by using the objective function based on the maximum correntropy criterion (MCC), which can availably suppress the bad effects of impulsive noise on filter weight updates. But the overall performance of the APLMC algorithm may be decreased when the input signal is polluted by noise. To compensate for the deviation of the APLMC algorithm in the input noise interference environment, the bias compensation (BC) method is introduced. Therefore, the bias-compensated APLMC (BC-APLMC) algorithm is presented. Besides, the convergence of the BC-APLMC algorithm in the mean and the mean square sense is studied, which provides a constraint range for the step-size. Computer simulation results show that the APLMC, and BC-APLMC algorithms are valid in acoustic echo cancellation and system identification applications. It also shows that the proposed algorithms are robust in the presence of input noise and impulse noise.  相似文献   

6.
陈维  胡兵 《大众科技》2012,14(3):54-56
常数模算法（constant modulus algorithm,CMA）能够很好地克服无线信道引入的符号间干扰（ISI）,在信道均衡中广泛应用,但存在稳态误差大,相位旋转的问题;MMA算法解决了CMA算法的相位旋转问题,但仍然有较大的稳态误差。为了克服以上缺点,在研究各种算法的基础上,引入非线性函数来构造步长调整参数,计算机仿真结果表明,相比传统算法,变步长盲均衡算法有较快的收敛速度和更好的均衡效果。  相似文献   

7.
In this paper, the concept of proportionate adaptation is extended to the normalized subband adaptive filter (NSAF), and seven proportionate normalized subband adaptive filter algorithms are established. The proposed algorithms are proportionate normalized subband adaptive filter (PNSAF), μ‐law PNSAF (MPNSAF), improved PNSAF (IPNSAF), the improved IPNSAF (IIPNSAF), the set-membership IPNSAF (SM-IPNSAF), the selective partial update IPNSAF (SPU-IPNSAF), and SM-SPU-IPNSAF which are suitable for sparse system identification in network echo cancellation. When the impulse response of the echo path is sparse, the PNSAF has initial faster convergence than NSAF but slows down dramatically after initial convergence. The MPNSAF algorithm has fast convergence speed during the whole adaptation. The IPNSAF algorithm is suitable for both sparse and dispersive impulse responses. The SM-IPNSAF exhibits good performance with significant reduction in the overall computational complexity compared with the ordinary IPNSAF. In SPU-IPNSAF, the filter coefficients are partially updated rather than the entire filter at every adaptation. In SM-SPU-IPNSAF algorithm, the concepts of SM and SPU are combined which leads to a reduction in computational complexity. The simulation results show good performance of the proposed algorithms.  相似文献   

8.
In this paper, a novel augmented complex-valued normalized subband adaptive filter (ACNSAF) algorithm is proposed for processing the noncircular complex-valued signals. Based on the augmented statistics, the proposed algorithm is derived by computing a constraint cost function. Due to contain all second-order statistical properties, the ACNSAF algorithm can process the circular and noncircular complex-valued signals simultaneously. Moreover, the stability and mean square steady-state analysis of the proposed algorithm is derived by using the energy conservation principle. Computer simulation experiments on complex-valued system identification, prediction and noise cancelling show that the proposed algorithm achieves the improved mean square deviation and prediction gain compared to the ACNLMS algorithm. And the simulation results are consistent with the analysis results.  相似文献   

9.
This paper addresses the tracking control problem of TCP/AWM network systems in presence of nonresponsive data flows of category user datagram protocol (UDP) flows. Firstly, a modified network system model is established by a certain suitable variable transformation, and then a fuzzy logic system (FLS) emulator is used to approximate the nonlinear terms in the network dynamics representation system. Secondly, inspired by the idea of the prescribed performance control (PPC), a novel finite-time performance function (NFTPF) is proposed. In turn, an adaptive finite-time congestion control strategy is designed by compatible usage as appropriate of a barrier Lyapunov function (BLF), the backstepping control synthesis, and an event-triggered mechanism. The proposed control strategy can not only make the tracking error to satisfy the pre-assigned transient and steady-state performance, but also ensure that all the closed-loop signals remain semi-globally uniformly ultimately bounded (SGUUB). In addition, the designed congestion control strategy eliminates potential occurrence of Zeno behavior. A set of simulation results are presented to clarify the feasibility and effectiveness of proposed methodological approach and the designed congestion controller.  相似文献   

10.
Error entropy is a well-known learning criterion in information theoretic learning (ITL), and it has been successfully applied in robust signal processing and machine learning. To date, many robust learning algorithms have been devised based on the minimum error entropy (MEE) criterion, and the Gaussian kernel function is always utilized as the default kernel function in these algorithms, which is not always the best option. To further improve learning performance, two concepts using a mixture of two Gaussian functions as kernel functions, called mixture error entropy and mixture quantized error entropy, are proposed in this paper. We further propose two new recursive least-squares algorithms based on mixture minimum error entropy (MMEE) and mixture quantized minimum error entropy (MQMEE) optimization criteria. The convergence analysis, steady-state mean-square performance, and computational complexity of the two proposed algorithms are investigated. In addition, the reason why the mixture mechanism (mixture correntropy and mixture error entropy) can improve the performance of adaptive filtering algorithms is explained. Simulation results show that the proposed new recursive least-squares algorithms outperform other RLS-type algorithms, and the practicality of the proposed algorithms is verified by the electro-encephalography application.  相似文献   

11.
This paper is concerned with the problem of adaptive event-triggered (AET) based optimal fuzzy controller design for nonlinear networked control systems (NCSs) characterized by Takagi–Sugeno (T–S) fuzzy models. An improved AET communication scheme with a memory adaptive rule is proposed to enhance the utilization of the state response vertex data. Different from the existing ET based results, the improved AET scheme can save more communication resources and acquire better system performance. The sufficient criteria of performance analysis and controller design are presented for the closed-loop control system subject to mismatched membership functions (MFs) and AET scheme. And then, a new MFs online learning algorithm on the basis of the gradient descent approach is employed to optimize the MFs of fuzzy controller and obtain optimal fuzzy controller for further improving system performance. Finally, two simulation examples are presented to verify the advantage and effectiveness of the provided controller design technique.  相似文献   

12.
In this paper, a novel tracking control scheme for continuous-time nonlinear affine systems with actuator faults is proposed by using a policy iteration (PI) based adaptive control algorithm. According to the controlled system and desired reference trajectory, a novel augmented tracking system is constructed and the tracking control problem is converted to the stabilizing issue of the corresponding error dynamic system. PI algorithm, generally used in optimal control and intelligence technique fields, is an important reinforcement learning method to solve the performance function by critic neural network (NN) approximation, which satisfies the Lyapunov equation. For the augmented tracking error system with actuator faults, an online PI based fault-tolerant control law is proposed, where a new tuning law of the adaptive parameter is designed to tolerate four common kinds of actuator faults. The stability of the tracking error dynamic with actuator faults is guaranteed by using Lyapunov theory, and the tracking errors satisfy uniformly bounded as the adaptive parameters get converged. Finally, the designed fault-tolerant feedback control algorithm for nonlinear tracking system with actuator faults is applied in two cases to track the desired reference trajectory, and the simulation results demonstrate the effectiveness and applicability of the proposed method.  相似文献   

13.
The conventional interacting multiple model (IMM) algorithm will increase the computational load when applying a large number of models, meanwhile, it cannot yield accurate estimation results with a small number of models. Furthermore, the unknown target acceleration is regarded as an additional process noise to the target model, and its time-varying variance is hard to be approximated. The paper proposes a fuzzy-logic adaptive variable structure multiple model (FAVSMM) algorithm for tracking a high maneuvering target. The algorithm can optimize the model parameters using the model probability and construct an optimal model set quickly, and the fuzzy-logic IMM algorithm included in the FAVSMM algorithm is adopted for states estimation. The simulation results show that the proposed algorithm can match well with the actual target trajectory with less computational complexity and better accuracy.  相似文献   

14.
In this paper, a novel composite controller is proposed to achieve the prescribed performance of completely tracking errors for a class of uncertain nonlinear systems. The proposed controller contains a feedforward controller and a feedback controller. The feedforward controller is constructed by incorporating the prescribed performance function (PPF) and a state predictor into the neural dynamic surface approach to guarantee the transient and steady-state responses of completely tracking errors within prescribed boundaries. Different from the traditional adaptive laws which are commonly updated by the system tracking error, the state predictor uses the prediction error to update the neural network (NN) weights such that a smooth and fast approximation for the unknown nonlinearity can be obtained without incurring high-frequency oscillations. Since the uncertainties existing in the system may influence the prescribed performance of tracking error and the estimation accuracy of NN, an optimal robust guaranteed cost control (ORGCC) is designed as the feedback controller to make the closed-loop system robustly stable and further guarantee that the system cost function is not more than a specified upper bound. The stabilities of the whole closed-loop control system is certified by the Lyapunov theory. Simulation and experimental results based on a servomechanism are conducted to demonstrate the effectiveness of the proposed method.  相似文献   

15.
The fast affine projection (FAP) algorithm (Gay and Tavathia, Proceedings of the IEEE International Conference on Acoustic, Speech and Signal Processing, 1995, 3023) is known to outperform the NLMS with a slight increase in complexity, but it involves the fast calculation of the inverse of a covariance matrix of the input data that could undermine the performance of the algorithm. The block subband adaptive algorithm in (Courville and Duhamel, IEEE Trans. Signal Processing 46(9) (1998) 2359) has also illustrated significant improvement in performance over the NLMS and other frequency domain adaptive algorithms. However, it is known that block processing algorithms have lower tracking capabilities than the their sample-by-sample counterparts. In this paper, we present a sample-by-sample version of the algorithm in (Courville and Duhamel, IEEE Trans. Signal Processing 46(9) (1998) 2359) and develop a low complexity implementation of this algorithm. As a sample-by-sample algorithm, it avoids the reduced tracking capability of block algorithms. Because it does not use matrix inversion, it avoids the numerical problems of FAP algorithms. We will show that the new sample-by-sample algorithm approximates the affine projection algorithm and possesses a similar property in reducing coefficient bias that appears in monophonic and stereophonic teleconferencing when the receiving room impulse responses are undermodeled. The new fast sample-by-sample algorithm is extended for stereo acoustic echo cancellation. Simulations of echo cancellations in actual rooms are presented to verify our findings.  相似文献   

16.
In this paper, the appointed-time prescribed performance and finite-time tracking control problem is investigated for quadrotor unmanned aerial vehicle (QUAV) in the presence of time-varying load, unknown external disturbances and unknown system parameters. For the position loop, a novel appointed-time prescribed performance control (ATPPC) strategy is proposed based on adaptive dynamic surface control (DSC) frameworks and a new prescribed performance function to achieve the appointed-time convergence and prescribed transient and steady-state performance. For the attitude loop, a new finite-time control strategy is proposed based on a new designed sliding mode control technique to track the desired attitude in finite time. Some assumptions of knowing system parameters are canceled. Finally, the stability of the closed-loop system is proved via Lyapunov Theory. Simulations are performed to show the effectiveness and superiority of the proposed control scheme.  相似文献   

17.
In this paper, a new robust adaptive prescribed performance control (PPC, for short) scheme is proposed for quadrotor UAVs (QUAVs, for short) with unknown time-varying payloads and wind gust disturbances. Under the presented framework, the overall control system is decoupled into translational subsystem and rotational subsystem. These two subsystems are connected to each other through common attitude extraction algorithms. For translational subsystem, a novel robust adaptive PPC strategy is designed based on the sliding mode control technique to provide better trajectory tracking performance and well robustness. For rotational subsystem, a new robust adaptive controller is constructed based on backstepping technique to track the desired attitudes. Finally, the overall system is proved to be stable in the sense of uniform ultimate boundedness, and numerical simulation results are presented to validate the effectiveness of the proposed control scheme.  相似文献   

18.
An integral predictor-based dynamic surface control scheme is developed with prescribed performance (IPPDSC) for multi-motor driving servo systems in this paper. By employing a novel finite-time performance function and an improved error transformation, the tracking error is limited within a prescribed zone in any preset time without having the overrun and the singularity problem. Furthermore, integral state predictors are designed to update neural network weights to handle high-frequency oscillations under large adaptive gains. Different from the existing approaches, an integral term of prediction error is introduced to eliminate the steady-state error and avoid chattering. In addition, a synchronization controller based on the mean relative coupling structure is proposed to solve the coupling problem between synchronization and tracking. Finally, simulation and experimental results are presented to demonstrate the effectiveness of the designed approach.  相似文献   

19.
The performance of the current state estimation will degrade in the existence of slow-varying noise statistics. To solve the aforementioned issues, an improved strong tracking maximum correntropy criterion variational-Bayesian adaptive Kalman filter is presented in this paper. First of all, the inverse-Wishart distribution, as the conjugate-prior, is adopted to model the unknown and time-varying measurement and process noise covariances, then the noise covariances and system state are estimated via the variational Bayesian method. Secondly, the multiple fading-factors are obtained and evaluated to modify the prediction error covariance matrix to address the problems associated with inaccurate error estimation. Finally, the maximum correntropy criterion is employed to correct the filtering gain, which improves the filtering performance of the proposed algorithm. Simulation results show that the proposed filter exhibits better accuracy and convergence performance compared to other existing algorithms.  相似文献   

20.
Conventional Sliding Mode Controllers (SMCs) exhibit a robust performance against matched bounded uncertainties and disturbances by containing them under a fixed controller’s effort. Consequently, the controller is commonly found excessive, leading to chattering and straining the actuator. As a solution, the variable-gain SMCs adapt to the instantaneous system requirements, thus attenuating the aforesaid effects and keeping the SMC’s benefits. However, the reported adaptive laws underlying such behavior commonly require arbitrary design considerations and do not consider practical implementation. Unlikely, in this work, a hysteresis-based adaptability law to drive the sliding variable to a boundary layer around zero is proposed. The sliding boundary—hysteresis’ width—will consistently “bounce” over the sliding variable, trying to shrink against it while preserving the sliding mode. This behavior finds its steady-state once the sliding variable and the sliding boundary’s dynamics are synchronized, with no need of subjective or arbitrary adjustments. The close-loop tuning can be derived from the system’s parameters alone, and its steady-state performance can be quantitatively predicted. Furthermore, a method to adjust the sliding surface parameters according to the system’s desired behavior is provided, all in a closed, analytical way. Finally, the physical actuator limits are taken into account and never exceeded, and the discrete nature of the devices normally used for SMC implementation is incorporated throughout. Two examples are studied to portray the proposal’s advantages.  相似文献   

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