학술논문

Online Input Signal Design for Kernel-Based Impulse Response Estimation
Document Type
Periodical
Author
Source
IEEE Transactions on Systems, Man, and Cybernetics: Systems IEEE Trans. Syst. Man Cybern, Syst. Systems, Man, and Cybernetics: Systems, IEEE Transactions on. 52(11):7211-7222 Nov, 2022
Subject
Signal Processing and Analysis
Robotics and Control Systems
Power, Energy and Industry Applications
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Estimation
Kernel
Signal design
Machine learning
Ovens
Manufacturing industries
Harmonic analysis
Cyber–physical systems
impulse responses
input design
kernel-based estimation
machine learning
system identification
Language
ISSN
2168-2216
2168-2232
Abstract
This article considers online input signal design for kernel-based estimation of impulse responses where the input signal is designed one bit at a time while simultaneously performing the identification. A method referred to as the direct spectrum shaping (DSS) method is proposed based on the biased Cramér–Rao lower bound, combined with detailed analysis of two popular choices of kernels. With no gradient computations, the DSS technique is able to achieve comparable accuracy but with a significant reduction in computational times by a factor of more than 370 compared with the existing Bayesian A-optimality (BAO) technique. The BAO technique, in general, attains higher estimation accuracy for oscillatory systems whereas the DSS approach is superior for systems with smoother impulse responses. The DSS method possesses further advantages of simplicity of implementation and low crest factor due to the signal being binary. An application example on a simulated curing oven in the glove manufacturing industry illustrates the potential impact of the DSS method.