Journal ArticleDOI
Parameter estimation for control systems based on impulse responses
TLDR
The impulse signal is an instant change signal in very short time, and since the cost function is highly nonlinear, the nonlinear optimization methods are adopted to derive the parameter estimation algorithms to enhance the estimation accuracy.Abstract:
The impulse signal is an instant change signal in very short time. It is widely used in signal processing, electronic technique, communication and system identification. This paper considers the parameter estimation problems for dynamical systems by means of the impulse response measurement data. Since the cost function is highly nonlinear, the nonlinear optimization methods are adopted to derive the parameter estimation algorithms to enhance the estimation accuracy. By using the iterative scheme, the Newton iterative algorithm and the gradient iterative algorithm are proposed for estimating the parameters of dynamical systems. Also, a damping factor is introduced to improve the algorithm stability. Finally, using simulation examples, this paper analyzes and compares the merit and weakness of the proposed algorithms.read more
Citations
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Control Algorithms of Magnetic Suspension Systems Based on the Improved Double Exponential Reaching Law of Sliding Mode Control
Jian Pan,Wei Li,Haipeng Zhang +2 more
TL;DR: The improved algorithm has better control performances than the traditional SMC and the power reaching law integral SMC algorithm, such as less chattering, smaller overshoots, and faster response speed.
Journal ArticleDOI
State estimation for bilinear systems through minimizing the covariance matrix of the state estimation errors
TL;DR: This paper proposes a state filtering method for the single-input–single-output bilinear systems by minimizing the covariance matrix of the state estimation errors by extending the extended Kalman filter algorithm to multiple- input–multiple-output Bilinear Systems.
Journal ArticleDOI
Hierarchical Parameter Estimation for the Frequency Response Based on the Dynamical Window Data
TL;DR: In this paper, a hierarchical multi-innovation stochastic gradient estimation method is derived through parameter decomposition, and the forgetting factor and the convergence factor are introduced to improve the performance of the algorithm.
Journal ArticleDOI
The least squares based iterative algorithms for parameter estimation of a bilinear system with autoregressive noise using the data filtering technique
Meihang Li,Ximei Liu +1 more
TL;DR: A two-stage least squares based iterative algorithm and a filtering based least squares iterative algorithms are proposed for estimating the parameters of bilinear systems with colored noises by using the hierarchical identification principle and the data filtering technique.
Journal ArticleDOI
Two-stage Gradient-based Iterative Estimation Methods for Controlled Autoregressive Systems Using the Measurement Data
TL;DR: A two-stage gradient-based iterative algorithm based on the multi-innovation identification theory is derived in order to improve the performance of the tracking the time-varying parameters of controlled autoregressive systems.
References
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Journal ArticleDOI
A filtering based multi-innovation extended stochastic gradient algorithm for multivariable control systems
TL;DR: A filtering based extended stochastic gradient algorithm and a filtering based multi-innovation ESG algorithm for improving the parameter estimation accuracy for a multivariable system with moving average noise.
Journal ArticleDOI
The damping iterative parameter identification method for dynamical systems based on the sine signal measurement
TL;DR: A damping parameter estimation algorithm for dynamical systems based on the sine frequency response is proposed and a damping factor is introduced in the proposed iterative algorithm in order to overcome the singular or ill-conditioned matrix during the iterative process.
Journal ArticleDOI
Parameter estimation and controller design for dynamic systems from the step responses based on the Newton iteration
Ling Xu,Lei Chen,Weili Xiong +2 more
TL;DR: In this article, a new Newton iterative identification method is presented for estimating the parameters of a second-order dynamic system utilizing the obtained data from the step response, in order to obtain the desired dynamic performance, a controller design method based on the root locus is presented to meet the requirement of the dynamic performance of the overshoot.
Journal ArticleDOI
A tutorial review on process identification from step or relay feedback test
TL;DR: The process models with time delay mainly adopted for identification in the literature are presented with a classification on different response types, along with two specific categories for robust identification against load disturbance and the identification of multivariable or nonlinear processes.
Journal ArticleDOI
Application of the Newton iteration algorithm to the parameter estimation for dynamical systems
TL;DR: Simulation results show that the obtained models can capture the dynamics of the systems, i.e., the estimated model's outputs are close to the outputs of the actual systems.
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