New approach to robust stabilization for a class of singular systems with time-delays

Robust stabilization for a class of singular systems was studied by a new method based on time discretization, and a sufficient condition of the robust stabilization was obtained. Firstly, an approximate system of the closed-loop system of the singular system with time-delays was obtained. The approximate system is a singular system in standard state space. Then, the robust stabilization of the singular system was investigated with time-delays by researching the stability of the approximate system using all the exiting analysis method. Finally, a numerical example was presented to verify the effectiveness of the new method.

Primary frequency control considering communication delay for grid-connected offshore wind power systems

Offshore wind farms are becoming increasingly distant from onshore centralized control centers,and the communication delays between them inevitably introduce time delays in the measurement signal of the primary frequency control.This causes a deterioration in the performance of the primary frequency control and,in some cases,may even result in frequency instability within the power system.Therefore,a frequency response model that incorporates communication delays was established for power systems that integrate offshore wind power.The Padéapproximation was used to model the time delays,and a linearized frequency response model of the power system was derived to investigate the frequency stability under different time delays.The influences of the wind power proportion and frequency control parameters on the system frequency stability were explored.In addition,a Smith delay compensation control strategy was devised to mitigate the effects of communication delays on the system frequency dynamics.Finally,a power system incorporating offshore wind power was constructed using the MATLAB/Simulink platform.The simulation results demonstrate the effectiveness and robustness of the proposed delay compensation control strategy.

时标上带有多重时滞的BAM神经网络的反周期解的存在性和指数稳定性

利用压缩映射原理及时标上的Gronwall不等式理论得到了时标T上带有时滞的BAM神经网络的反周期解的存在性和指数稳定性的充分条件.

Analysis of robust stability for switched systems with multiple time-delays

The sufficient conditions of delay-dependent exponential stability for switched systems and robust exponential stability for uncertain switched systems with two time-delays are presented by using average dwell time method and free-weighting matrix method.The interaction between different time-delays is considered.The sufficient conditions do not need that every subsystem is stable.The designed methods of the switching law are also given.The sufficient conditions are given in the form of linear matrix inequalities that can be solved easily.The result is proven to be valid by the simulation at last.

Synthetic aperture sonar movement compensation algorithm based on time-delay and phase estimation

The effects of movement errors on imaging results of synthetic aperture sonar and the necessity of movement compensation are discussed. Based on analyzing so-called displaced phase center algorithm, an improved algorithm is proposed. In this method, the time delay is estimated firstly, then the phase is estimated for the residual error, so that the range of movement error suited to the algorithm is extended to some extent. Some simulation results on computer and experimental results in the test tank using the proposed algorithm are given as well.

Experimental investigation on the time-delay signature of chaotic output from a 1550 nm VCSEL subject to FBG feedback

The time-delay signature(TDS) of chaos output in a 1550 nm vertical-cavity surface-emitting laser(VCSEL) subject to fiber Bragg grating(FBG) feedback is investigated experimentally. Autocorrelation function(ACF) and mutual information(MI) are used for quantitatively identifying the TDS of chaos. For various bias currents, the TDS evolution with the feedback strength is different, as the FBG provides wavelength-selective feedback. Furthermore,based on the TDS map of the FBG feedback VCSEL(FBGF-VCSEL) in the parameter space of feedback strength and bias current, the optimal TDS suppression regions, where the dominant polarization mode of FBGF-VCSEL locates at the edge of the main lobe of FBG reflection spectrum, have been determined. Finally, for comparative purpose,the TDS of chaos in mirror feedback VCSEL(MF-VCSEL) also has been presented, and the results show that an FBGF-VCSEL possesses better TDS suppression performance than an MF-VCSEL.

Optical true time-delay for two-dimensional phased array antennas using compact fiber grating prism

A two-dimensional(2D) optical true-time delay(TTD) beam-forming system using a compact fiber grating prism(FGP) for a planar phased array antenna(PAA) is proposed. The optical beam-forming system mainly consists of a TTD unit based on the same compact FGP, one tunable laser for elevation beam steering, and a controlled wavelength converter for azimuth beam steering. A planar PAA using such 2D optical TTD unit has advantages such as compactness, low bandwidth requirement for tunable laser sources, and potential for large-scale system implementations. The proof-of-concept experiment results demonstrate the feasibility of the proposed scheme.

Input-to-state stability theorem and strict Lyapunov functional constructions for time-delay systems on time scales

In this paper,input-to-state stability of nonlinear time-delay systems on time scales is investigated.Due to the advantages of the strict Lyapunov functionals in uncertainty quantification and robustness analysis,one always prefers to construct the strict Lyapunov functionals to analyse stability of time-delay systems.However,it may be not an easy task to do this for some timedelay systems.This paper proposes an input-to-state stability theorem based on a time-scale uniformly asymptotically stable function.The advantage of this theorem is that it is dependent on the non-strict Lyapunov functional,whose time-scale derivative can be non-negative on some time intervals.Then,some approaches are established to construct the strict Lyapunov functionals based on the non-strict ones.It is shown that input-to-state stability theorems can be also formulated in terms of these strict Lyapunov functionals.Finally,to illustrate the effectiveness of the main results,an example is given.

Simultaneous estimation of time-delay and direction of arrival for underwater multitarget by using extended ESPRIT

Multiple sources localization is an important technique applied in many areasl such as sonar, radar, biomedical, and geology exploration. High resolution localization needs to employ jointly two sorts of high resolution estimators, time-delay estimator and Direction Of Arrival (DOA) estimator, both of which are tough problems attracting many signal processing researchers. There is also another difficulty that is to pair two groups of parameters in timedelay and DOA domains. In underwater environment, multiple sources localization research faces more difficulties because of the long duration emitted wave, limit aperture of array, and short data record of echoes. In this paper, an new extended ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique) method is presented. With a single echo wave, both time-delay and DOA parameters of multiple sources are estimated simultaneously.No additional pairing algorithm is needed to obtain the source locations. The performance of the new estimators and the probability of correct pairing is given by computer simulations, andthe results shows that good estimation can be obtained in low SNR (Signal to Noise Ratio) for multiple sources localization.

Less is more: a new machine-learning methodology for spatiotemporal systems

Machine learning provides a way to use only portions of the variables of a spatiotemporal system to predict its subsequent evolution and consequently avoids the curse of dimensionality.The learning machines employed for this purpose,in essence,are time-delayed recurrent neural networks with multiple input neurons and multiple output neurons.We show in this paper that such kinds of learning machines have a poor generalization ability to variables that have not been trained with.We then present a one-dimensional time-delayed recurrent neural network for the same aim of model-free prediction.It can be trained on different spatial variables in the training stage but initiated by the time series of only one spatial variable,and consequently possess an excellent generalization ability to new variables that have not been trained on.This network presents a new methodology to achieve finegrained predictions from a learning machine trained on coarse-grained data,and thus provides a new strategy for certain applications such as weather forecasting.Numerical verifications are performed on the Kuramoto coupled oscillators and the Barrio-Varea-Aragon-Maini model.

DR-model-based estimation algorithm for NCS

A novel estimation scheme based on dead reckoning(DR)model for networked control system(NCS)is proposed in this paper.Both the detailed DR estimation algorithm and the stability analysis of the system are given.By using DR estimation of the state,the effect of communication delays is overcome.This makes a controller designed without considering delays still applicable in NCS.Moreover,the scheme can effectively solve the problem of data packet loss or timeout.