scholarly journals High Performance Motion Tracking Control for Electronic Manufacturing

2007 ◽  
Vol 129 (6) ◽  
pp. 767-776 ◽  
Author(s):  
Benjamin Potsaid ◽  
John Ting-Yung Wen ◽  
Mark Unrath ◽  
David Watt ◽  
Mehmet Alpay
Keyword(s):  
Motion Control ◽  
Impulse Response ◽  
Finite Impulse Response ◽  
Learning Control ◽  
Iterative Refinement ◽  
Performance Criteria ◽  
Mean Square ◽  
Least Mean Square ◽  
Positioning Systems ◽  
Electronic Manufacturing

Motion control requirements in electronic manufacturing demand both higher speeds and greater precision to accommodate continuously shrinking part/feature sizes and higher densities. However, improving both performance criteria simultaneously is difficult because of resonances that are inherent to the underlying positioning systems. This paper presents an experimental study of a feedforward controller that was designed for a point-to-point motion control system on a modern and state of the art laser processing system for electronics manufacturing. We systematically apply model identification, inverse dynamics control, iterative refinement (to address modeling inaccuracies), and adaptive least mean square to achieve high speed trajectory tracking. The key innovations lie in using the identified model to generate the gradient descent used in the iterative learning control, encoding the result from the learning control in a finite impulse response filter and adapting the finite impulse response coefficients during operation using the least-mean-square update based on position, velocity, and acceleration feedforward signals. Experimental results are provided to show the efficacy of the proposed approach, a variation of which has been implemented on the production machine.

scholarly journals A Proportionate Normalized Maximum Correntropy Criterion Algorithm with Correntropy Induced Metric Constraint for Identifying Sparse Systems

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 683 ◽  
Author(s):  
Yingsong Li ◽  
Yanyan Wang ◽  
Laijun Sun
Keyword(s):  
Impulse Response ◽  
Adaptive Filter ◽  
Finite Impulse Response ◽  
Least Mean Square ◽  
Sparse Systems ◽  
Simulation Results ◽  
Maximum Correntropy Criterion ◽  
Non Gaussian ◽  
Fir Systems ◽  
Filter Algorithms

A proportionate-type normalized maximum correntropy criterion (PNMCC) with a correntropy induced metric (CIM) zero attraction terms is presented, whose performance is also discussed for identifying sparse systems. The proposed sparse algorithms utilize the advantage of proportionate schemed adaptive filter, maximum correntropy criterion (MCC) algorithm, and zero attraction theory. The CIM scheme is incorporated into the basic MCC to further utilize the sparsity of inherent sparse systems, resulting in the name of the CIM-PNMCC algorithm. The derivation of the CIM-PNMCC is given. The proposed algorithms are used for evaluating the sparse systems in a non-Gaussian environment and the simulation results show that the expanded normalized maximum correntropy criterion (NMCC) adaptive filter algorithms achieve better performance than those of the squared proportionate algorithms such as proportionate normalized least mean square (PNLMS) algorithm. The proposed algorithm can be used for estimating finite impulse response (FIR) systems with symmetric impulse response to prevent the phase distortion in communication system.

An Improved ZA-LMS Algorithm for Sparse System Identification with Variable Sparsity

2014 ◽  
Vol 602-605 ◽  
pp. 2415-2419 ◽  
Author(s):  
Hui Luo ◽  
Yun Lin ◽  
Qing Xia
Keyword(s):  
System Identification ◽  
Impulse Response ◽  
Lms Algorithm ◽  
Mean Square ◽  
Least Mean Square ◽  
Sparse System ◽  
Sparse System Identification ◽  
Least Mean Square Algorithm ◽  
Improved Algorithm

The standard least mean square algorithm does not consider the sparsity of the impulse response,and the performs of the ZA-LMS algorithm deteriorates ,as the degree of system sparsity reduces or non-sparse . Concerning this issue ,the ZA-LMS algorithm is studied and modified in this paper to improve the performance of sparse system identification .The improved algorithm by modify the zero attraction term, which attracts the coefficients only in a certain range (the “inactive” taps), thus have a good performance when the sparsity decreases. The simulations demonstrate that the proposed algorithm significantly outperforms then the ZA-LMS with variable sparisity.

scholarly journals Adaptive Parameter Estimation of IIR System-Based WSN Using Multihop Diffusion in Distributed Approach

2020 ◽  
Vol 14 (4) ◽  
pp. 30-41
Author(s):  
Meera Dash ◽  
Trilochan Panigrahi ◽  
Renu Sharma ◽  
Mihir Narayan Mohanty
Keyword(s):  
Impulse Response ◽  
Sensor Node ◽  
Finite Impulse Response ◽  
Lms Algorithm ◽  
Sensor System ◽  
Superior Performance ◽  
Estimation Accuracy ◽  
Infinite Impulse Response ◽  
Communication Overhead ◽  
Least Mean Square

Distributed estimation of parameters in wireless sensor networks is taken into consideration to reduce the communication overhead of the network which makes the sensor system energy efficient. Most of the distributed approaches in literature, the sensor system is modeled with finite impulse response as it is inherently stable. Whereas in real time applications of WSN like target tracking, fast rerouting requires, infinite impulse response system (IIR) is used to model and that has been chosen in this work. It is assumed that every sensor node is equipped with IIR adaptive system. The diffusion least mean square (DLMS) algorithm is used to estimate the parameters of the IIR system where each node in the network cooperates themselves. In a sparse WSN, the performance of a DLMS algorithm reduces as the degree of the node decreases. In order to increase the estimation accuracy with a smaller number of iterations, the sensor node needs to share their information with more neighbors. This is feasible by communicating each node with multi-hop nodes instead of one-hop only. Therefore the parameters of an IIR system is estimated in distributed sparse sensor network using multihop diffusion LMS algorithm. The simulation results exhibit superior performance of the multihop diffusion LMS over non-cooperative and conventional diffusion algorithms.

Optimal FIR Input Shaper Designs for Motion Control With Zero Residual Vibration

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
Matthew O. T. Cole ◽  
Theeraphong Wongratanaphisan
Keyword(s):  
Motion Control ◽  
Impulse Response ◽  
Finite Impulse Response ◽  
Single Mode ◽  
Residual Vibration ◽  
Input Shaper ◽  
Orthogonality Conditions ◽  
Final Design ◽  
Actuation Signal ◽  
Impulse Response Filter

This paper considers the design of input shaping filters used in motion control of vibratory systems. The filters preshape a command or actuation signal in order to negate the effect of vibratory modes. A class of finite impulse response filter satisfying a set of orthogonality conditions that ensure zero residual vibration is introduced. Filter solutions having minimum quadratic gain, both with and without the inclusion of non-negativity (peak gain) constraints, are presented. Unlike impulse-based shapers, the filters have impulse responses with no singularities and therefore automatically remove discontinuities from an input signal. Minimum duration impulse response solutions are also presented. These contain singularities but may also have smooth components. Discrete-time designs can be obtained numerically from system modal parameters, accounting for all modes simultaneously so that convolving single-mode solutions, which leads to suboptimality of the final design, is not required. Selected designs are demonstrated experimentally on a flexible link planar manipulator.

Design of New Reconfigurable Architecture for Implementing a Least Mean Square Finite Impulse Response Filter Using Borrow Select Subtraction (BSLS)

2020 ◽  
Vol 17 (4) ◽  
pp. 1943-1948
Author(s):  
P. Mukunthan ◽  
N. C. Sendhilkumar ◽  
R. Pitchai
Keyword(s):  
Adaptive Filter ◽  
Finite Impulse Response ◽  
Full Adder ◽  
Fir Filter ◽  
Reconfigurable Architecture ◽  
Mean Square ◽  
Least Mean Square ◽  
Lms Filter ◽  
Ripple Carry Adder ◽  
Filter Architecture

A design of reconfigurable architecture of FIR filter has been implemented using a Least Mean Square (LMS) adaptive filter. LMS adaptive filter is mainly sued for reducing the coefficients of the filter. Generally, a LMS filter contains normal adder, subtractor, mixer and a delay part. Most of the concepts deal with an adder namely Full Adder (FA), Ripple Carry Adder (RCA), Carry Select Adder (CSLA), etc., Instead of using CSLA; Borrow Select Subtractor (BSLS) is used in LMS filter architecture. By using BSLA LMS adaptive filter in a reconfigurable FIR filter architecture in the proposed scheme, the area, power and delay will be reduced. The proposed scheme achieves better performance when compared to an existing scheme. The proposed method is implemented in ModelSim tool and efficiency has been calculated by using the device Virtex 6 Low Power in Xilinx ISE Design Suite 12.4.

Vibration Suppression Based on Adaptive Feedforward Control With Infinite Impulse Response Filter

2015 ◽  
Author(s):  
Shiying Zhou ◽  
Masayoshi Tomizuka
Keyword(s):  
Impulse Response ◽  
Vibration Suppression ◽  
Finite Impulse Response ◽  
Feedforward Control ◽  
Vibration Signal ◽  
Infinite Impulse Response ◽  
Least Mean Square ◽  
Parameter Adaptation ◽  
Iir Filter ◽  
Adaptive Feedforward

This paper presents adaptive feedforward control for vibration suppression based on an infinite impulse response (IIR) filter structure. The vibration signal and the output signal are available for the algorithm to adaptively update the parameters of the vibration transmission path (VTP) dynamics. Two designs for parameter adaptation are proposed. They provide different methods to get the necessary signals for parameter adaptation of the IIR filter which is different from the conventional finite impulse response (FIR) filter adaptation design. Performance of the proposed designs is compared with the conventional Filtered-x Least Mean Square (FxLMS) method on a hard disk drive (HDD) benchmark problem. The simulation results show that the proposed designs have smaller 3σ value and peak to peak value at steady state.

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