Lianming Sun

Output intersampling approach to direct closed-loop identification

A new direct closed-loop identification method, which uses the output intersampling technique, is proposed in this note. By using the intersampled plant input-output data, the proposed method removes the traditional restrictive identifiability condition, and does not require an external persistently exciting (PE) test signal.

Over-sampling approach to closed-loop identification

A new identification algorithm for a linear discrete-time closed-loop system is proposed based on an output over-sampling scheme. Even if the ordinary identifiability conditions are not satisfied, a closed-loop system can be identified by using the over-sampled output data which contain more information about the system structure without utilizing any external test signal. It is a distinctive advantage of the proposed approach compared to conventional ones.

Direct closed-loop identification of magnetic suspension system

A new direct closed-loop identification method only using the plant input/output data acquired through an output inter-sampling scheme is presented. By taking the faster sampling of the system output than the control interval, we can clarify that the inter-sampled plant model can also be described by a SIMO model structure, which can provide the identifiability of the closed-loop. One of the advantages is that the proposed identification method using the inter-sampled output observations can remove the ordinary restrictive identifiability condition, and it is not required that the reference input holds the persistently exciting property. Its effectiveness is demonstrated through an experimental study using a magnetic suspension system.

Channel identification and interference compensation for OFDM system in long multipath environment

Guard interval (GI) is usually applied to reduce the influence caused by multipath interferences in orthogonal frequency division multiplexing (OFDM) systems. However, the long multipath interferences will deteriorate the orthogonality of the sub-carriers if they have longer delay time than GI. It is illustrated that not only inter-symbol interference (ISI) but also inter-carrier interference (ICI) is caused by the collapse of orthogonality in the received signal. As a result, both the channel identification and equalization become difficult, and the communication performance cannot be guaranteed. In this work, a new channel identification algorithm is proposed to estimate the frequency response function from the spectral periodograms which are compensated by the replica of leakage error. Since most of the computation is performed in the frequency domain through fast Fourier transform, the algorithm has such low computational complexity that it can be implemented easily in applications.

Direct closed-loop identification approach to unstable plant

Deals with the problem of direct closed-loop identification for unstable plant models disturbed by stochastic noise. The unstable plant is stabilized by a digital feedback controller. Then by introducing the output inter-sampling scheme, the plant model is identified from the inter-sampled input-output data of the plant even though the external reference or the test signal does not hold a persistently exciting property. Both time and frequency domain approaches are developed and numerical examples are performed to demonstrate the effectiveness of the proposed approaches.

Frequency domain approach to closed-loop identification based on output inter-sampling scheme

A novel frequency domain closed-loop identification algorithm is proposed using the output inter-sampling scheme. It is illustrated that the inter-sampled plant output has cyclo-stationary property that can be used to eliminate the correlation between the plant input and output noise even though no persistently exciting test signal is available. It can be applied for the unstable plant identification problem, and can be extended to the situation where the output disturbance noise is colored. An experiment of magnetic suspension system is performed to demonstrate the effectiveness of the proposed approach.

Output Over-Sampling Approach to Direct Closed-Loop Identification and Its Performance

Abstract Polynomial input–output recursive models are widely used in nonlinear model identification for their flexibility and representation capabilities. Several identification algorithms are available in the literature dealing both with model selection and parameter estimation, based on various criteria. Previous works have shown the limits of the classical prediction error minimization approach, and suggested the use of a simulation error minimization approach for better model selection. The present paper goes a step further by integrating the model selection procedure with a simulation oriented parameter estimation algorithm. Notwithstanding the algorithmic and computational complexity of the proposed method, it is shown that it can achieve significant performance improvements with respect to previously proposed approaches.

CYCLIC SPECTRAL BASED APPROACH TO CLOSED-LOOP IDENTIFICATION

Abstract The direct closed-loop identification algorithm based on cyclic spectral is considered in frequency domain in this paper. It is illustrated that the input and output signals obtained through inter-sampling technique have cyclic spectral, and the cyclic spectral contain plant model information, then the plant model can be estimated just from the cyclic spectral of the plant input and output signals. It is clarified that the test signal is not necessary, and the new algorithm does not depend on the controller structure. The effectiveness of the proposed algorithm is also demonstrated through several numerical examples.

New Closed-Loop Identification Approach Based on Output Over-Sampling Scheme

Abstract A new identification algorithm is investigated for direct closed-loop identification by using the cyclostationarity of output over-sampled data. It has been shown that the plant model can be directly identified from the input and output data in the output over-sampling scheme even less excitation is available in the test input. However, the numerical optimization in conventional direct algorithms ordinarily depends on the initial values and estimation of noise process, whereas the estimation accuracy of the noise model is fragile to the poles and zeros of its transfer function. The properties of instinct cyclostationarity and the associated subspace characteristics of the sampled data in the output over-sampling scheme are analyzed in the paper. It illustrates that these properties can be applied for identification, and can reduce the influence of sensitivity to the noise model estimation and initial values in the numerical optimization. The simulation examples illustrate that the proposed algorithm can significantly improve the identification performance in direct closed-loop identification.

Algorithm and Implementation of Direct Closed-Loop Identification via Output Over-Sampling Scheme

Identification algorithm and its implementation are considered for direct closed-loop identification through output over-sampling. It is shown that the plant model can be identified from the input and output data obtained by output over-sampling even though the conventional identifiability conditions are not satisfied. Furthermore, its implementation for the controller and measurement device with fixed-point number is also investigated. The numerical simulations illustrate the effectiveness of the proposed algorithm for practical applications.