This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

A networked control system (NCS) is a control system which involves a communication network. In NCSs, the continuous-time measurement is usually sampled and quantized before transmission. Then, the measurement is transmitted to the remote controller via the communication channel, during which the signal may be delayed, lost or even sometimes not allowed for transmission due to the communication or energy constraints. In recent years, the modeling, analysis and synthesis of networked control systems (NCSs) have received great attention, which leads to a large number of publications. This paper attempts to present an overview of recent advances and unify them in a framework of network-induced issues such as signal sampling, data quantization, communication delay, packet dropouts, medium access constraints, channel fading and power constraint, and present respective solution approaches to each of these issues. We draw some conclusions and highlight future research directions in end.

Analysis and synthesis of networked control systems: A survey of recent advances and challenges.

Network-based modelling and dynamic output feedback control for unmanned marine vehicles in network environments

This paper presents a novel method to address a Proportional Integral observer design for the actuator and sensor faults estimation based on Takagi–Sugeno fuzzy model with unmeasurable premise variables. The faults are assumed as time-varying signals whose kth time derivatives are bounded. Using Lyapunov stability theory and L2 performance analysis, sufficient design conditions are developed for simultaneous estimation of states and time-varying actuator and sensor faults. The Proportional Integral observer gains are computed by solving the proposed conditions under Linear Matrix Inequalities constraints. A simulation example is provided to illustrate the effectiveness of the proposed approach.

Actuator and sensor faults estimation based on proportional integral observer for TS fuzzy model

This paper is concerned with the guaranteed cost control problem for a class of Markov jump discrete-time neural networks (NNs) with event-triggered mechanism, asynchronous jumping, and fading channels. The Markov jump NNs are introduced to be close to reality, where the modes of the NNs and guaranteed cost controller are determined by two mutually independent Markov chains. The asynchronous phenomenon is considered, which increases the difficulty of designing required mode-dependent controller. The event-triggered mechanism is designed by comparing the relative measurement error with the last triggered state at the process of data transmission, which is used to eliminate dispensable transmission and reduce the networked energy consumption. In addition, the signal fading is considered for the effect of signal reflection and shadow in wireless networks, which is modeled by the novel Rice fading models. Some novel sufficient conditions are obtained to guarantee that the closed-loop system reaches a specified cost value under the designed jumping state feedback control law in terms of linear matrix inequalities. Finally, some simulation results are provided to illustrate the effectiveness of the proposed method.

Event-Triggered Asynchronous Guaranteed Cost Control for Markov Jump Discrete-Time Neural Networks With Distributed Delay and Channel Fading

This paper focuses on the $H_{\infty }$ fault detection (FD) problem for spring-mass systems (SMSs) over networks with distributed state delays, random packet losses, sensor saturation as well as multiplicative noises via unreliable communication channels. The output measurements are affected by sensor saturation which is described by sector-nonlinearities. The multiplicative noises are described as a form of Gaussian white noises multiplied by the states. A series of stochastic variables are introduced to describe the randomly occurring distributed state delays. Random packet losses are also introduced in unreliable communications. The purpose of this paper is to design an FD filter such that: 1) The FD dynamic system is exponentially stable in the mean square. 2) The error between the fault signal and the residual signal is controlled to the minimum. 3) The optimal $H_{\infty }$ filtering performance index is achieved. A sufficient condition for the FD filter design is derived in terms of the solution to a linear matrix inequality (LMI). When the LMI has a feasible solution, the explicit parameters of the desired FD filter can be obtained. Finally, a simulation experiment is illustrated to show the effectiveness and application of the designed method.

$H_{\infty }$ Fault Detection for Networked Mechanical Spring-Mass Systems With Incomplete Information

H∞ filtering for nonlinear networked systems with randomly occurring distributed delays, missing measurements and sensor saturation

H∞ fault detection filtering for mechanical spring-mass systems over networked systems with incomplete information

This paper is concerned with the H∞ fault detection (FD) for a class of networked systems with random packet losses, sensor saturation and multiplicative noises. The network with both output measurement and control packet losses is modeled with two independent Bernouli distributed white sequences. H∞ filtering theory is adapted to formulate the problem of fault detection for networked systems. The output measurement is affected by sensor saturation which is described by sector-nonlinearities, and the multiplicative noises are modeled as a form of Gaussian white noise. The purpose of the addressed problem is to design a fault detection filter such that, the fault detection dynamic system is exponentially stable in the mean square, and the error between the residual value and fault value is made as small as possible. A sufficient condition for FD filter is derived by solving the linear matrix inequality (LMI). Finally, a numerical example is illustrated to show the effectiveness of the designed method.

http://ieeexplore.ieee.org/iel7/7267673/7279248/07279480.pdf

Fault detection for networked systems with random packet losses, sensor saturation and multiplicative noises

The paper focuses on a stabilizing controller design problem for networked systems with quantization, mixed delays, and a series of packet losses due to the signal transmission through the unreliable communication channel. Quantization of both sensor-to-controller and controller-to-actuator are taken into account for the networked systems, and the distributed time delay is also considered in the network channel. Sufficient conditions for designing the controller as well as the system parameters can be obtained by solving certain linear matrix inequalities. Finally, the effectiveness of the designed method is proved by a numerical example.

Fengfeng Qian

Papers

$H_{\infty }$ Fault Detection for Networked Mechanical Spring-Mass Systems With Incomplete Information

H∞ filtering for nonlinear networked systems with randomly occurring distributed delays, missing measurements and sensor saturation

H∞ fault detection filtering for mechanical spring-mass systems over networked systems with incomplete information

Fault detection for networked systems with random packet losses, sensor saturation and multiplicative noises

Observer-based controller design for networked systems with multiple packet losses and mixed delay