H-infinity measurement-feedback control for discrete-time systems with a single measurement delay

H-infinity control problem for linear discrete-time systems with instantaneous and delayed measurements is studied. A necessary and sufficient condition for the existence of the H-infinity controller is derived by applying reorganized innovation analysis approach in Krein space. The measurement-feedback controller is designed by performing two Riccati equations. The presented approach does not require the state augmentation.

Stochastic bounded consensus tracking of leader-follower multi-agent systems with measurement noises based on sampled data with general sampling delay

In this paper we provide a unified framework for consensus tracking of leader-follower multi-agent systems with measurement noises based on sampled data with a general sampling delay. First, a stochastic bounded consensus tracking protocol based on sampled data with a general sampling delay is presented by employing the delay decomposition technique. Then, necessary and sufficient conditions are derived for guaranteeing leader-follower multi-agent systems with measurement noises and a time-varying reference state to achieve mean square bounded consensus tracking. The obtained results cover no sampling delay, a small sampling delay and a large sampling delay as three special cases. Last, simulations are provided to demonstrate the effectiveness of the theoretical results.

MEASUREMENT OF AMPLITUDE AND DELAY OF STIMULUS FREQUENCY OTOACOUSTIC EMISSIONS

Although stimulus frequency otoacoustic emissions (SFOAEs) have been used as a non-invasive measure of cochlear mechanics, clinical and experimental application of SFOAEs has been limited by difficulties in accurately deriving quantitative information from sound pressure measured in the ear canal. In this study, a novel signal processing method for multicomponent analysis (MCA) was used to measure the amplitude and delay of the SFOAE. This report shows the delay-frequency distribution of the SFOAE measured from the human ear. A low level acoustical suppressor near the probe tone significantly suppressed the SFOAE, strongly indicating that the SFOAE was generated at characteristic frequency locations. Information derived from this method may reveal more details of cochlear mechanics in the human ear.

Fractionally Delayed Kalman Filter

The conventional Kalman filter is based on the assumption of non-delayed measurements. Several modifications appear to address this problem, but they are constrained by two crucial assumptions: 1) the delay is an integer multiple of the sampling interval, and 2) a stochastic model representing the relationship between delayed measurements and a sequence of possible non-delayed measurements is known. Practical problems often fail to satisfy these assumptions, leading to poor estimation accuracy and frequent track-failure. This paper introduces a new variant of the Kalman filter, which is free from the stochastic model requirement and addresses the problem of fractional delay.The proposed algorithm fixes the maximum delay(problem specific), which can be tuned by the practitioners for varying delay possibilities. A sequence of hypothetically defined intermediate instants characterizes fractional delays while maximum likelihood based delay identification could preclude the stochastic model requirement. Fractional delay realization could help in improving estimation accuracy. Moreover, precluding the need of a stochastic model could enhance the practical applicability. A comparative analysis with ordinary Kalman filter shows the high estimation accuracy of the proposed method in the presence of delay.

Particle filter for nonlinear systems with multi-sensor asynchronous random delays

This paper is concerned with the recursive filtering problem for a class of discrete-time nonlinear stochastic systems in the presence of multi-sensor measurement delay. The delay occurs in a multi-step and asynchronous manner, and the delay probability of each sensor is assumed to be known or unknown. Firstly, a new model is constructed to describe the measurement process, based on which a new particle filter is developed with the ability to fuse multi-sensor information in the case of known delay probability.In addition, an online delay probability estimation module is introduced in the particle filtering framework, which leads to another new filter that can be implemented without the prior knowledge of delay probability. More importantly, since there is no complex iterative operation, the resulting filter can be implemented recursively and is suitable for many real-time applications. Simulation results show the effectiveness of the proposed filters.

Doppler radar by using single multicarrier pulse based on optical fibre delay lines

The proposed Doppler measurement technique shows that the Doppler measurements can be accomplished by a single pulse with multiple frequency components through optical fibre delay lines.Range and velocity ambiguity can be removed,and the velocity resolution can be improved dramatically by using long optical fibre delay lines.Furthermore,the velocity resolution can be modified by adjusting the length of optical fibre delay lines.In addition,the proposed radar can achieve high range resolution by using a single wideband pulse.As a result,the new approach can improve radar performance significantly.

Time-resolution enhanced multi-path OTD measurement using an adaptive filter based incoherent OFDR

High accuracy and time resolution optical transfer delay(OTD)measurement is highly desired in many multi-path applications,such as optical true-time-delay-based array systems and distributed optical sensors.However,the time resolution is usually limited by the frequency range of the probe signal in frequency-multiplexed OTD measurement techniques.Here,we proposed a time-resolution enhanced OTD measurement method based on incoherent optical frequency domain reflectometry(I-OFDR),where an adaptive filter is designed to suppress the spectral leakage from other paths to break the resolution limitation.A weighted least square(WLS)cost function is first established,and then an iteration approach is used to minimize the cost function.Finally,the appropriate filter parameter is obtained according to the convergence results.In a proof-of-concept experiment,the time-domain response of two optical links with a length difference of 900 ps is successfully estimated by applying a probe signal with a bandwidth of 400 MHz.The time resolution is improved by 2.78times compared to the theoretical resolution limit of the inverse discrete Fourier transform(iDFT)algorithm.In addition,the OTD measurement error is below±0.8 ps.The proposed algorithm provides a novel way to improve the measurement resolution without applying a probe signal with a large bandwidth,avoiding measurement errors induced by the dispersion effect.

Robust state estimation for uncertain linear discrete systems with d-step measurement delay and deterministic input signals

In this study,the state estimation problems for linear discrete systems with uncertain parameters,deterministic input signals and d-step measurement delay are investigated.A robust state estimator with a similar iterative form and comparable computational complexity to the Kalman filter is derived based on the state augmentation method and the sensitivity penalisation of the innovation process.It is discussed that the steady-state properties such as boundedness and convergence of the robust state estimator under the assumptions that the system parameters are time invariant.Numerical simulation results show that compared with the Kalman filter,the obtained state estimator is more robust to modelling errors and has nice estimation accuracy.

Optimal linear estimators for systems with random measurement delays

This paper is concerned with the optimal linear estimation problem for linear discrete-time stochastic systems with random measurement delays. A new model that describes the random delays is constructed where possible the largest delay is bounded. Based on this new model, the optimal linear estimators including filter, predictor and smoother are developed via an innovation analysis approach. The estimators are recursively computed in terms of the solutions of a Riccati difference equation and a Lyapunov difference equation. The steady-state estimators are also investigated. A sufficient condition for the convergence of the optimal linear estimators is given. A simulation example shows the effectiveness of the proposed algorithms.

Closed-loop fault detection for full-envelope fligh vehicle with measurement delays

Abstract A closed-loop fault detection problem is investigated for the full-envelope flight vehicle with measurement delays, where the flight dynamics are modeled as a switched system with delayed feedback signals. The mode-dependent observer-based fault detection filters and state estimation feedback controllers are derived by considering the delays＇ impact on the control system and fault detection system simultaneously. Then, considering updating lags of the controllers/filters＇ switching signals which are introduced by the delayed measurement of altitude and Mach number, an asynchronous H analysis method is proposed and the system model is further augmented to be an asynchronously switched time-delay system. Also, the global stability and desired performance of the augmented system are guaranteed by combining the switched delay-dependent Lyapunov Krasovskii functional method with the average dwell time method （ADT）, and the delaydependent existing conditions for the controllers and fault detection filters are obtained in the form of the linear matrix inequalities （LMIs）, Finally, numerical example based on the hypersonic vehicles and highly maneuverable technology （HiMAT） vehicle is given to demonstrate the merits of the proposed method.

Distributed Optimal Control of Nonlinear Time-Delay System Subject to Delayed Measurements and Communication Disruptions

This paper is focused on a distributed optimal control design for a class of nonlinear timedelay systems with delayed measurements and communication disruptions.The innovation lies in three aspects.The distributed optimal control method which includes an optimal controller and a bounded controller is designed based on Lyapunov function.The availability of data transmitted through the communication channel depends on a feasibility problem.And a sufficient condition to guarantee ultimate boundedness of the system is given based on appropriate assumptions.The significance of this paper is that this distributed optimal control method is applied to time-delay system.Finally,a simulation example is given to verify the effectiveness of the proposed method.

Delay Time Measurement and Comparison of Protection Strategies with One-Link Failed Domestic Optical Fiber Networks in Taiwan

In this paper, we study the protection strategies of domestic optical fiber networks in Taiwan. Delay time experiment of two one-link failed cases are also reported and compared. We can get best protection strategy and bypass the optical transmission signal at shortest delay time.

PULSE SHRINKING TIME-TO-DIGITAL CONVERTER FOR UWB APPLICATION

A kind of architecture of Time-to-Digital Converter(TDC) for Ultra-WideBand(UWB) application is presented. The proposed TDC is based on pulse shrinking, and implemented in a Field Programmable Gate Array(FPGA) device. The pulse shrinking is realized in a loop containing two Programmable Delay Lines(PDLs) or a two-channel PDL. One line(channel) delays the rising edge and the other line(channel) delays the falling edge of a circulating pulse. Delay resolution of PDL is converted into a digital output code under known conditions of pulse width. This delay resolution measurement mechanism is different from the conventional time interval measurement mechanism based on pulse shrinking of conversion of unknown pulse width into a digital output code. This mechanism automatically avoids the influence of unwanted pulse shrinking by any circuit element apart from the lines. The achieved relative errors for four PDLs are within 0.80%–1.60%.

State Estimation Using Non-uniform and Delayed Information: A Review

The study and application of methods for incorporating nonuniform and delayed information in state estimation tech- niques are important topics to advance in soft sensor development. Therefore, this paper presents a review of these methods and pro- poses a taxonomy that allows a faster selection of state estimator in this type of applications. The classification is performed according to the type of estimator, method, and used tool. Finally, using the proposed taxonomy, some applications reported in the literature are de- scribed.

Kalman filtering for time-delayed linear systems

This paper is to study the linear minimum variance estimation for discretetime systems. A simple approach to the problem is presented by developing re-organized innovation analysis for the systems with instantaneous and double time-delayed measurements. It is shown that the derived estimator involves solving three different standard Kalman filtering with the same dimension as the original system. The obtained results form the basis for solving some complicated problems such as H, fixed-lag smoothing, preview control, H, filtering and control with time delays.

Global Exponential Stability of Variable Delay and Time－varying Measure Differential Systems with Impulse Effect

This work concerns the stability properties of impulsive solution for a class of variable delay and time-varying measure differential systems. By means of the techniques of constructing broken line function to overcome the difficulties in employing comparison principle and Lyapunov function with discontinuous derivative, some criteria of global exponential asymptotic stability for the system are established. An example is given to illustrate the applicability of results obtained.