scholarly journals Affine projection and recursive least squares adaptive filters employing partial updates

Author(s):  
P.A. Naylor ◽  
A.W.H. Khong
2020 ◽  
Vol 2020 ◽  
pp. 1-17 ◽  
Author(s):  
Zhiyu Ni ◽  
Shunan Wu ◽  
Yewei Zhang ◽  
Zhigang Wu

Manipulator systems are widely used in payload capture and movement in the ground/space operation due to their dexterous manipulation capability. In this study, a method for identifying the payload parameters of a flexible space manipulator using the estimated system of complex eigenvalue matrix is proposed. The original nonlinear dynamic model of the manipulator is linearized at a selected working point. Subsequently, the system state-space model and corresponding complex eigenvalue parameters are determined by the observer/Kalman filter identification algorithm using the torque input signal of the motor and the vibration output signals of the link. Therefore, the inertia parameters of the payload, that is, the mass and the moment of inertia, can be derived from the identified complex eigenvalue system and mode shapes by solving a least-squares problem. In numerical simulations, the proposed parameter identification method is implemented and compared with the classical recursive least-squares and affine projection sign algorithms. Numerical results demonstrate that the proposed method can effectively estimate the payload parameters with satisfactory accuracy.


Author(s):  
Pawel Konrad Orzechowski ◽  
Tsu-Chin Tsao ◽  
James Steve Gibson

In many adaptive control applications, especially where the recursive-least-squares (RLS) algorithms are used, the real-time implementation of high order adaptive filters for estimating the disturbance dynamics is computationally intensive. The delay associated with the computational burden is usually either underestimated as no delay or overestimated as one sample delay in the control system design and analysis. For a stochastic disturbance dynamics, the H2 optimal control performance for the case of one-step delay is worse than that of no delay due to the nonminimum phase plant zero introduced by the delay. The optimal performance for a fractional delay is bounded between these two extremes. The paper investigates the effect of the fractional computational delay on a variable order adaptive controller based on a recursive least-squares adaptive lattice filter. The trade-off between the adaptive filter order and the computational delay is analyzed and evaluated by an example.


Author(s):  
Hyungjoo Yoon ◽  
Brett E. Bateman ◽  
Brij N. Agrawal

The primary focus of this research is to develop and implement control schemes for combined broadband and narrowband disturbances to optical beams. The laser beam jitter control testbed developed at the Naval Postgraduate School is used for development of advanced jitter control techniques. First, we propose a least quadratic Gaussian feedback controller with integrator for cases when only the error signal (the difference between the desired and the actual beam positions) is available. An anti-notch filter is also utilized to attenuate a vibrational disturbance with a known frequency. Next, we develop feedforward adaptive filter methods for cases when a reference signal, which is highly correlated with the jitter disturbance, is available. A filtered-X recursive least-squares algorithm with an integrated bias estimator is proposed to deal with a constant bias disturbance. Finally, experimental results are provided to validate and compare the performance of the developed control techniques. The designed adaptive filter has a simple structure but shows good jitter rejection performance, thanks to the use of a reference signal.


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