Time-delay Identification Research Articles

Iterative Identification Algorithms for Continuous-Time Systems with Unknown Time Delay in the Presence of Measurement Noise

This paper considers the identification problem of continuous-time systems with unknown time delay from sampled input-output data. By using a digital pre-filter, an approximated discrete-time estimation model is first derived, in which the system parameters remain in their original form and the time delay need not be an integral multiple of the sampling period. Then an unseparable nonlinear least-squares (UNSEPNLS) method and a separable nonlinear least-squares (SEPNLS) method for identification of transfer function parameters and time delay are derived. Furthermore, an unseparable nonlinear instrumental variable (UNSEPNIV) method and a separable nonlinear instrumental variable (SEPNIV) method are proposed, to eliminate estimate bias due to measurement noise. Simulational results show that the UNSEPNIV and SEPNIV methods yield consistent estimates in the presence of measurement noise.

Simultaneous online identification of rational dynamics and time delay: a correlation-based approach

A new algorithm for simultaneous identification of a rational dynamic and an unknown or varying time delay is suggested in this communication. The proposed method is based on integration of two interacting estimation modules: First, a pseudo-pure delay system is obtained by filtering the input and output of the system. The time-delay is then identified via correlation technique. The rational dynamics is identified via standard recursive least-squares identification. An experimental study is included to illustrate the merits of this algorithm.

Stability chart for the delayed Mathieu equation

In the space of system parameters, the closedform stability chart is determined for the delayed Mathieu equation defined as (t)(cost)x(t) bx(t2). This stability chart makes the connection between t...

Parameter identification of continuous systems with multiple-input time delays via modulating functions

The identification of continuous systems with multiple-input delays is discussed. A batch algorithm for parametric identification of both multiple time delays and unknown parameters is proposed, using the modulating function approach. If the unknown delay is expressed as a linear combination of a bank of known delays, it is proven that the distribution of the identified coefficients is a sampling centred on the unknown delays; the result is then extended to the multiple delay case. The modulating function method guarantees a continuous-time approach and robustness for a high value of noise-to-signal ratio. Simulation results are included to illustrate the proposed technique.

Acoustic data preprocessing in the TOMOLAB/OCTOPUS project

This paper presents the acoustic data preprocessing task in the TOMOLAB graphic interface tool. TOMOLAB is a goal of the OCTOPUS project, under the MAST III program of the European Community. Data preprocessing consists in transforming raw tomographic data into compressed/correlated peaklike data. It is the first step before time delay estimation, time delay identification, and time delay inversion. The complete data processing must perform matched filtering, multisequence averaging, Doppler/phase compensation, and mooring motion correction. A synthetic view is given of several technical choices that integrate these tasks, jointly or successively. This work is based on internal studies and existing pieces of literature. The Hadamard transform, the Fourier matched filtering, fast Doppler processing, phase estimation/correction algorithm, delay shifting in the time or Fourier domain, data format and sampling are discussed. Efficient data processing has to account for the computing speed, the compression ratio, and achievable accuracy of delay estimation.

Fast ambiguity processing in SOFAR propagation involving periodic signals and M sequences

Fast ambiguity processing can be used in active time delay and Doppler identification in the sound fixing and ranging (SOFAR) propagation context. They need periodic signals generated from pseudo-random M sequences. In the particular case of the SOFAR, the range of the observed Doppler effect enables use of the fastest version, provided that the periodicity of the signal is correctly adjusted.

Effect of fixed time delay on stability and performance of actively controlled civil engineering structures

In this paper, a state-of-the-art review for the fixed time delay of actively controlled civil engineering structures is presented, including the identification of time delay, the effect of time delay on the stability and performance of the controlled structures, and the evaluation of the critical time delay. In particular, a critical review of the stability analysis methods currently available for the critical time delay of Multiple-Degree-of-Freedom (MDOF) systems is conducted and new simulation results are presented to show its limitation in practical applications. Further, a method of stability analysis for the critical time delay of MDOF systems equipped with single or multiple actuators is presented along with the simulation results to demonstrate its applications to seismic hazard mitigations. Under earthquake excitations, simulation results for the structural response indicate that the degradation of the control performance due to the fixed time delay is not significant until the time delay is close to the critical time delay. It is further demonstrated that the time-delay problem is more serious for structures with closely spaced vibrational modes, such as a building equipped with an active tuned mass damper. © 1997 John Wiley & Sons, Ltd.

Identification of Parameters and Time Delays of Continuous Systems using the Genetic Algorithm

This report proposes a novel method of identification of continuous time-delay systems from sampled inputoutput data. By the aid of a digital pre-filter, an approximated discrete-time estimation model is first derived, in which the system parameters remain in their original form and the time delay need not be an integral multiple of the sampling period. Then an identification method combining the common linear least squares (LS) method or the instrumental variable (IV) method with the genetic algorithm (GA) is proposed. That is, the time-delay is selected by the GA, and the system parameters are estimated by the LS or IV method. Furthermore, the proposed method is extended to the case of multi-input multi-output(MIMO) systems where the time-delays in the individual input channels may differ each other. Simulation results show that our method yields accurate estimates even in the presence of high measurement noises.

Design of Discrete-Time Adaptive Control in Presence Of Uncertain Time Delay

This paper deals with the problem of the adaptive control of discrete-time linear SISO plants with unknown time delay. In this context, a new control scheme is presented which does not require the explicit identification of the unknown time delay and is characterized by a complexity which is comparable with that of the undelayed discrete-time plant, i.e., that obtained by sampling the continuous-time plant neglecting the time delay. Moreover, the order of the resulting controller is known and independent of the sampling interval.

Identification of time delays in linear stochastic systems

Abstract This paper presents a new approach to the explicit identification of an input time delay in continuous-time linear systems. The system model is converted to a discrete-time version, assuming that a digital computer is to be used for time delay estimation and control. A recursive identification algorithm based on parallel Kalman filtering and Bayes' estimation is developed. The sampling rate is adapted during the time delay estimation process using the most recent estimate of the time delay. This method assures that the estimate of the time delay approaches the true value with each successive iteration. The proposed method also has the advantage of a fast convergence rate because prior knowledge of the delay, if available, can be effectively utilized.

On Identification of time Delay Via the Approximatione-TS≃1-sT/21+sT/2

This paper considers the identification of time delay, T, in the system, y(t) = u(t-T) by using the first order Padé approximation, [ 1 − sT / 2 1 + sT / 2 ] to e -Ts and a Luenberger observer or a Kaiman filter algorithm.

On-Line Identification of Time Delay And System Parameters of Continuous Systems Based on Discrete-Time Measurements

Abstract A simple approach is presented for simultaneous on-line identification of the time delay and the system parameters of continuous-time systems based on discrete-time measurements. The linear integral filter is used both to construct the derivatives of input-output signals and to avoid estimating the unknown initial conditions. The time delay and the system parameters are directly estimated by an on-line algorithm which is derived using Newton’s method. Severed identification methods such as the bias-compensating method and the instrumental variable methods are applied for eliminating the asymptotic bias of the parameter estimates in noisy situations. The present algorithm is applicable to the case when the time delay is not an integral multiple of the sampling interval, and can also be used for model reduction.

Identification of time delays in flight measurements

A computer program has been developed for the maximum likelihood estimation of parameters in general nonlinear systems. Sensitivity matrix elements are calculated numerically, overcoming the need for explicit sensitivity equations. Parameters such as break points and time delays are successfully determined using simulated data. Two examples using aircraft flight data are shown to demonstrate the identification of multiple time delays concurrently with other parameters.

Frequency Domain Parameter Estimation of Aeronautical Systems without and with Time Delay

The paper Considers the application of frequency domain methods, to flight test data from rotorcraft and fixed wing aircraft. In particular, a modified frequency domain output error method is presented, which can be applied to linear systems with time delays. In contrast to existing methods, the new approach enables the combination of data from several manoeuvres for one evaluation, the use of test records with arbitrary initial state conditions x(t=0), and the direct identification of time delays (instead of using Padé-approximation). Results are presented as well from the identification of a six-degrees-of-freedom helicopter model (Bo-105 Research Helicopter of the DFVLR) as from the identification of an equivalent low order system with time delay (HFB 320-In-Flight-Simulator of the DFVLR).

Identification of time delays using a polynomial identification method

An algorithm for the exact least-squares identification of an approximate continuous-time time-delay system is derived and its operation verified by simulation.

A method for the identification of time delays in linear systems

An automatic method is presented for the identification of time delays and parameters in linear systems. It is assumed that processes to be identified can be described by linear differential-difference equations. Unknown parameters in these equations are determined by a continuous steepest descent minimization of an error function. If the process parameters are constant, a region exists in the parameter space in which the tracking paramters converge to the process parameters. If all process time delays are known as well, the tracking parameters will always converge. Two examples are presented which show that the method may be used to identify slowly varying parameters. A third example indicates techniques leading to a more economical implementation of the method.