Leader-following formation control of multi-agent networks based on distributed observers

To investigate the leader-following formation control, in this paper we present the design problem of control protocols and distributed observers under which the agents can achieve and maintain the desired formation from any initial states, while the velocity converges to that of the virtual leader whose velocity cannot be measured by agents in real time. The two cases of switching topologies without communication delay and fixed topology with time-varying communication delay are both considered for multi-agent networks. By using the Lyapunov stability theory, the issue of stability is analysed for multi-agent systems with switching topologies. Then, by considering the time-varying communication delay, the sufficient condition is proposed for the multi-agent systems with fixed topology. Finally, two numerical examples are given to illustrate the effectiveness of the proposed leader-following formation control protocols.

Observers for Descriptor Systems with Slope-restricted Nonlinearities

This paper addresses the observer design problem for a class of nonlinear descriptor systems whose nonlinear terms are slope-restricted. The full-order observer is formulated as a nonlinear descriptor system. A linear matrix inequality （LMI） condition is derived to construct the full-order observer. The existence and uniqueness of the solution to the obtained observer system are guaranteed. Furthermore, under the same LMI condition and a common assumption, a reduced-order observer is designed. Finally, the design methods are reduced to a strict LMI problem and illustrated by a numerical example.

Stability analysis of the extended state observers by Popov criterion

The analysis and design of the extended state observer （ESO） involves a continuous non-smooth structure, thus the study of the ESO dynamic requires mathematical tools of the nonlinear systems analysis. This paper establishes the sufficient conditions for absolute stability of the ESO. Based on this study, a methodology to estimate several nonlinear functions in dy- namics systems is proposed.

Robust Fault Detection and Isolation Based on Finite-frequency H__/H_∞ Unknown Input Observers and Zonotopic Threshold Analysis

This work proposes a robust fault detection and isolation scheme for discrete-time systems subject to actuator faults,in which a bank of H_/H∞ fault detection unknown input observers(UIOs) and a zonotopic threshold analysis strategy are considered. In observer design, finite-frequency H_ index based on the generalized Kalman-Yakubovich-Popov lemma and H∞ technique are utilized to evaluate worst-case fault sensitivity and disturbance attenuation performance, respectively. The proposed H_/H∞ fault detection observers are designed to be insensitive to the corresponding actuator fault only, but sensitive to others.Then, to overcome the weakness of predefining threshold for FDI decision-making, this work proposes a zonotopic threshold analysis method to evaluate the generated residuals. The FDI decision-making relies on the evaluation with a dynamical zonotopic threshold. Finally, numerical simulations are provided to show the feasibility of the proposed scheme.

Sliding-mode observers for systems with unknown inputs and measurement disturbances

The method to design sliding-mode observers for systems with unknown inputs and measurement disturbances is presented in the paper. An augmented system is constructed by viewing the measurement disturbances as unknow inputs. For such an augmented system, the so-called observer matching condition is not satisfied. Based on the construction of auxiliary outputs, the observer matching condition may be satisfied. High-order sliding-mode differentiators are developed to obtain the estimates of those unmeasurable variables contained in the auxiliary output vector. Employing the estimate of auxiliary output vector, a sliding-mode observer is designed. The simulation results to a real model show that the proposed method is effective.

On “Over-Sized” High-Gain Practical Observers for Nonlinear Systems

In this paper,it is shown that the performances of a class of high-gain practical observers can be improved by estimating the time derivatives of the output up to an order that is greater than the dimension of the system, which is assumed to be in observability form and, possibly, time-varying. Such an improvement is achieved without increasing the gain of the observers, thus allowing their use in a wide variety of control and identification applications.

Fault diagnosis using robust cascade observers with application to spacecraft attitude control

This paper proposes a new gyro and star sensor fault diagnosis architecture that designs two groups of cascade H∞ optimal fault observers using LMI for spacecraft attitude control systems.The basic idea of the approach is to identify the gyro fault to good effect first and then makes a further diagnosis for the star sensor based on the former.The H∞ optimal fault observer in design has the robustness with respect to model uncertainties and diagnosis uncertainties.Its robustness to unknown inputs is as a special study in frequency domain.Finally,simulation results demonstrate the effectiveness and feasibility of the proposed control algorithm.

Robust fault detection in linear systemsbased on full-order state observers

A parametric approach to robust fault detection in linear systems with unknown disturbances is presented. The residual is generated using full-order state observers （FSO）. Based on an analytical solution to a type of Sylvester matrix equations, the parameterization of the observer gain matrix is given. In terms of the design degrees of freedom provided by the parametric observer design and a group of introduced parameter vectors, a sufficient and necessary condition for fullorder state observer design with disturbance decoupling is then established. By properly constraining the design parameters according to this proposed condition, the effect of the disturbance on the residual signal is also decoupled, and a simple algorithm is developed. The presented approach offers all the degrees of design freedom. Finally, a numerical example illustrates the effect of the proposed approach.

Conventional and Added-Order Proportional Nonlinear Integral Observers

In this paper, a kind of fire new nonlinear integrator and integral action is proposed. Consequently, a conventional Proportional Nonlinear Integral (P_NI) observer and two kinds of added-order P_NI observers are developed to deal with the uncertain nonlinear system. The conditions on the observer gains to ensure the estimated error to be ultimate boundness, which shrinks to zero as the states and control inputs converge to the equilibrium point, are provided. This means that if the observed system is asymptotically stable, the estimated error dynamics is asymptotically stable, too. Moreover, the highlight point of this paper is that the design of nonlinear integral observer is achieved by linear system theory. Simulation results showed that under the normal and perturbed cases, the pure added-order P_NI observer can effectively deal with the uncertain nonlinearities on both the system dynamics and measured outputs.

High-Gain Approach Based Full-Order Observers for Linear Systems with Unknown Inputs

In this paper, a full-order observer which can be fully decoupled from the unknown inputs as the conventional full-order observer does is designed by using auxiliary outputs, but the requirement of the matching condition is removed. The procedure of calculating the parameter matrices of the full-order observer is also presented. Compared with the existing auxiliary outputs based sliding-mode observers, the designed observer has a simpler design procedure, which is systematic and does not involve solving linear matrix inequalities. The simulation results show that the proposed method is effective.

Observers:让ZooKeeper更具可伸缩性

云计算时代，软件开发人员面临着越来越多分布式协作方面的问题。ZooKeeper是由Apache出品的一个分布式协作服务，新加入的Observer特性，进一步增强了ZooKeeper的可伸缩性。

Nonlinear Control of Bioprocess Using Feedback Linearization, Backstepping, and Luenberger Observers

This paper addresses the analysis, design, and application of observer-based nonlinear controls by combining feedback linearization (FBL) and backstepping (BS) techniques with Luenberger observers. Complete development of observer-based controls is presented for a bioprocess. Controllers using input-output feedback linearization and backstepping techniques are designed first, assuming that all states are available for feedback. Next, the construction of observer in the transformed domain is presented based on input-output feedback linearization. This approach is then extended to observer design based on backstepping approach using the error equation resulted from the backstepping design procedure. Simulation results demonstrating the effectiveness of the techniques developed are presented and compared.

Magnetopause properties at the dusk magnetospheric flank from global magnetohydrodynamic simulations,the kinetic Vlasov equilibrium,and in situ observations--Potential implications for SMILE

We derived the properties of the terrestrial magnetopause(MP)from two modeling approaches,one global–fluid,the other local–kinetic,and compared the results with data collected in situ by the Magnetospheric Multiscale 2(MMS2)spacecraft.We used global magnetohydrodynamic(MHD)simulations of the Earth’s magnetosphere(publicly available from the NASA-CCMC[National Aeronautics and Space Administration–Community Coordinated Modeling Center])and local Vlasov equilibrium models(based on kinetic models for tangential discontinuities)to extract spatial profiles of the plasma and field variables at the Earth’s MP.The global MHD simulations used initial solar wind conditions extracted from the OMNI database at the time epoch when the MMS2 observes the MP.The kinetic Vlasov model used asymptotic boundary conditions derived from the same in situ MMS measurements upstream or downstream of the MP.The global MHD simulations provide a three-dimensional image of the magnetosphere at the time when the MMS2 crosses the MP.The Vlasov model provides a one-dimensional local view of the MP derived from first principles of kinetic theory.The MMS2 experimental data also serve as a reference for comparing and validating the numerical simulations and modeling.We found that the MP transition layer formed in global MHD simulations was generally localized closer to the Earth(roughly by one Earth radius)from the position of the real MP observed by the MMS.We also found that the global MHD simulations overestimated the thickness of the MP transition by one order of magnitude for three analyzed variables:magnetic field,density,and tangential speed.The MP thickness derived from the local Vlasov equilibrium was consistent with observations for all three of these variables.The overestimation of density in the Vlasov equilibrium was reduced compared with the global MHD solutions.We discuss our results in the context of future SMILE(Solar wind Magnetosphere Ionosphere Link Explorer)campaigns for observing the Earth’s MP.

Dynamical Dark Energy in Light of Cosmic Distance Measurements.Ⅱ.A Study Using Current Observations

We extract key information on dark energy from current observations of BAO,OHD and H_(0),and find hints of dynamical behavior of dark energy.In particular,a dynamical dark energy model whose equation of state crosses-1 is favored by observations.We also find that the Universe has started accelerating at a lower redshift than expected.

Adaptive Robust State Observers of Uncertain Dynamical Systems with Time-Varying Delays

The problem of adaptive robust state observer design is considered for a class of uncertain dynamical systems with Time-varying delays. A new method is presented whereby a class of memoryless adaptive robust state observers with simpler structure is proposed. It is also shown that by employing the proposed adaptive robust state observer, the observation error between the observer state estimate and the true state can be guaranteed to be uniformly exponentially convergent towards a ball which can be as small as desired. Finally, a numerical example is given to demonstrate the validity of the results.

A Robust Fault Detection and Isolation Scheme Based on Unknown Input Observers for Discrete Time-delay System with Disturbance

This paper proposes a robust fault detection and isolation (FDI) scheme for discrete time-delay system with disturbance. The FDI scheme can not only detect but also isolate the faults. The lifting method is exploited to transform the discrete time-delay system into the non-time-delay form. A generalized structured residual set is designed based on the unknown input observer (UIO). For each residual generator, one of the system input signals together with the corresponding actuator fault and the disturbance signals are treated as an unknown input term. The residual signals can not only be robust against the disturbance, but also be of the capacity to isolate the actuator faults. The proposed method has been verified by a numerical example.

Observer-based robust high-order fully actuated attitude autopilot design for spinning glide-guided projectiles

This paper investigates the design of an attitude autopilot for a dual-channel controlled spinning glideguided projectile(SGGP),addressing model uncertainties and external disturbances.Based on fixed-time stable theory,a disturbance observer with integral sliding mode and adaptive techniques is proposed to mitigate total disturbance effects,irrespective of initial conditions.By introducing an error integral signal,the dynamics of the SGGP are transformed into two separate second-order fully actuated systems.Subsequently,employing the high-order fully actuated approach and a parametric approach,the nonlinear dynamics of the SGGP are recast into a constant linear closed-loop system,ensuring that the projectile's attitude asymptotically tracks the given goal with the desired eigenstructure.Under the proposed composite control framework,the ultimately uniformly bounded stability of the closed-loop system is rigorously demonstrated via the Lyapunov method.Validation of the effectiveness of the proposed attitude autopilot design is provided through extensive numerical simulations.

Deep learning to estimate ocean subsurface salinity structure in the Indian Ocean using satellite observations

Accurately estimating the ocean subsurface salinity structure(OSSS)is crucial for understanding ocean dynamics and predicting climate variations.We present a convolutional neural network(CNN)model to estimate the OSSS in the Indian Ocean using satellite data and Argo observations.We evaluated the performance of the CNN model in terms of its vertical and spatial distribution,as well as seasonal variation of OSSS estimation.Results demonstrate that the CNN model accurately estimates the most significant salinity features in the Indian Ocean using sea surface data with no significant differences from Argo-derived OSSS.However,the estimation accuracy of the CNN model varies with depth,with the most challenging depth being approximately 70 m,corresponding to the halocline layer.Validations of the CNN model’s accuracy in estimating OSSS in the Indian Ocean are also conducted by comparing Argo observations and CNN model estimations along two selected sections and four selected boxes.The results show that the CNN model effectively captures the seasonal variability of salinity,demonstrating its high performance in salinity estimation using sea surface data.Our analysis reveals that sea surface salinity has the strongest correlation with OSSS in shallow layers,while sea surface height anomaly plays a more significant role in deeper layers.These preliminary results provide valuable insights into the feasibility of estimating OSSS using satellite observations and have implications for studying upper ocean dynamics using machine learning techniques.

Trajectory tracking guidance of interceptor via prescribed performance integral sliding mode with neural network disturbance observer

This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.

Non Linear Dynamic Crack Model Applied to State Observers Methodology for Fault Detection, Localization and Evaluation in a Cantilever Beam

The purpose of this work is the study of a mathematical model to discretize cracks at continuous mechanical systems, applying all the available properties at computational algorithm using the methodology of state observers to detect, localize and evaluate the crack conditions, seeking the model limitations through an experiment developed at the mechanical department of UNESP, llha Solteira, S^o Paulo-Brazil. Three different notch sizes were placed, one by one, at the top surface of a cantilever beam （to be considered as a crack at the mechanical system） and harmonic forces were applied at the tip of the beam with three different frequencies, for each notch size, to obtain experimental data to run the diagnosis algorithm. From the results it was possible to infer that the observation system performance increases with the raising of the crack size, which can be explained by the model, that gets more accurate with bigger crack sizes, however, when the propagation of the crack is considered at the model, the diagnosis of the crack presence tends to be more difficult. It was also possible to conclude that the developed algorithm works properly for systems which excitation frequencies are higher than 20 Hz and different from the natural frequencies of the system, due to influence of dynamic response of the crack at the model.