This paper considers finite-time distributed state estimation for discrete-time nonlinear systems over sensor networks. The Round-Robin protocol is introduced to overcome the channel capacity constraint among nodes, and multiplicative noise employed model fading. In order improve performance of estimator under situation, where transmission resources are limited, fading channels with different stochastic properties used in each round by allocating resources. Sufficient conditions average...

This paper addresses the problem of state estimation for a class discrete-time stochastic complex networks with constrained and randomly varying coupling uncertain measurements. The is governed by Markov chain, capacity constraint handled introducing logarithmic quantizer. uncertainty measurements modeled multiplicative noise. An asynchronous estimator designed to overcome difficulty that each node cannot access information, an augmented error system obtained using Kronecker product....

Quantization has been an important research area for a long time networked control systems. This paper addresses the problem of reset state observer (RSO)-based (RSOC) linear systems using quantized measurements. According to characteristic logarithmic quantizer, RSOC is presented based on standard one suppress sensor quantization effects. By Lyapunov approach, closed-loop system still asymptotically stable when technique introduced. The and controller gains are obtained via solving matrix...

We investigate the optimal estimation problem in lossy networked control systems where packets are randomly dropped without acknowledgment to estimator. Most existing results for this setup concerned with design of controller, while and its performance evaluation have been rarely treated. In paper, we show that, unlike many other cases such as intermittent observations or TCP-like systems, system state follows a Gaussian mixture distribution exponentially increasing terms, which leads sum...

This paper studies the issue of robust state estimation for coupled neural networks with parameter uncertainty and randomly occurring distributed delays, where polytopic model is employed to describe uncertainty. A set Bernoulli processes different stochastic properties are introduced occurrences delays. Novel estimators based on local coupling structure proposed make full use information. The augmented error system obtained Kronecker product. new Lyapunov function, which depends both...

In order to deal with the networked control system (NCS) under random packet loss and uncertainties, an improved model predictive tracking is provided in this paper. proposed strategy, a novel state space introduced, where, unlike conventional models, error variables are combined optimized together. Based on model, more design degrees can be better performance acquired. A classical angular positioning uncertainties NCS introduced illustrate effectiveness of at same time, (MPC) approach as...

This paper investigates the issue of finite-time state estimation for coupled Markovian neural networks subject to sensor nonlinearities, where Markov chain with partially unknown transition probabilities is considered. A Luenberger-type estimator proposed based on incomplete measurements, and error system derived by using Kronecker product. By Lyapunov method, sufficient conditions are established, which guarantee that stochastically bounded stable, respectively. Then, gains obtained via...

This technical note studies fixed-time consensus tracking with disturbance rejection for first-order multiagent systems. The communication topology among the leader and followers contains a directed spanning tree. control input to is time-varying unknown followers, except that its upper bound known <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> . A novel protocol devised based on discontinuous nonlinear control. stability...

This work proposes an incremental Generalized Iterative Closest Point (GICP) based tightly-coupled LiDAR-inertial odometry (LIO), iG-LIO, which integrates the GICP constraints and inertial into a unified estimation framework. iG-LIO uses voxel-based surface covariance estimator to estimate covariances of scans, utilizes voxel map represent probabilistic models surrounding environments. These methods successfully reduce time consumption estimation, nearest neighbor search, management....

A sliding-mode observer is designed to estimate the vehicle velocity with measured acceleration, wheel speeds and braking torques. Based on Burckhardt tyre model, extended Kalman filter parameters of model estimated velocity, acceleration. According tyre/road friction coefficients optimal slip ratios are calculated. adaptive control (SMC) algorithm presented ratios. And adjustment method gain factors discussed. SMC algorithm, a vehicle's antilock system (ABS) built Simulink Toolbox. Under...

The problem of dissipativity-based resilient filtering for discrete-time periodic Markov jump neural networks in the presence quantized measurements is investigated this paper. Due to limited capacities network medium, a logarithmic quantizer applied underlying systems. Considering fact that filter realized through network, randomly occurring parameter uncertainties are modeled by two mode-dependent Bernoulli processes. By establishing Lyapunov function, sufficient conditions given ensure...

This paper studies the synchronization issue of time-varying Markovian jump neural networks (NNs). The denial-of-service (DoS) attack is considered in communication channel connecting master NNs and slave NNs. An observer designed based on measurements transmitted over this unreliable to estimate their states. deception used destroy controller by changing sign control signal. Then, mixed-type attacks are expressed uniformly, a error system established using function. A finite-horizon l2-l∞...

This paper studies the state estimator design for periodic neural networks, where stochastic weight matrices B(k) and packet dropouts are considered. The variables, which may influence each other, introduced to describe uncertainties of matrices. In order model time-varying conditions communication channel, a Markov chain is employed study jumping cases properties (i.e., Bernoulli process with means variances being used handle dropouts). A constructed such that augmented system...

The problem of quasi-synchronization (QS) for the Markovian jump master-slave neural networks with time-varying delay is studied in this article, where mismatch parameters and unreliable communication channels are considered as well. A set stochastic variables different expectations used to describe fading phenomena parallel channels. An impulsive-driven transmission strategy designed reduce load, a corresponding impulsive controller then designed. synchronization error system (SES)...

This article addresses reset moving horizon estimation for multiple output discrete-time systems with quantized measurements. A new state estimator is designed based on a one-dimensional noisy measurement to overcome underestimation or overestimation of the system state, and an iterative algorithm proposed deal systems. It shown that algorithm, error improved in presence over under estimation, boundedness established. The also achieves better estimate than existing one scalar static case....

In this paper, the partial-nodes-based (PNB) state estimation issue is investigated for a class of discrete-time complex networks with constrained bit rate and bounded noises. Measurements from only fraction nodes in network are acquired used estimation. The communication between sensor estimators accomplished over wireless digital limited bandwidth. A constraint model introduced to reflect bandwidth allocation rules partially accessible nodes. sufficient condition proposed under which PNB...

This article studies the security of distributed state estimation under data integrity attacks. Each sensor is equipped with a Kullback–Leibler (K–L) divergence detector to diagnose authenticity received data. A necessary and sufficient condition for insecurity estimator derived, in which stealthy attack can evade degrade performance. Furthermore, an algorithm proposed generate sequences. To overcome vulnerability, transmission strategy based on watermarking proposed. The effect parameters...

In this article, the problem of ultimately bounded state estimation is investigated for discrete-time multirate singularly perturbed complex networks under bit rate constraints, where sensor sampling period allowed to differ from updating networks. The facilitation communication between sensors and remote estimator through wireless networks, which are subject involves use a coding-decoding mechanism. For efficient in presence periodic measurements, specialized impulsive method developed,...