scholarly journals A Review on Analysis and Synthesis of Nonlinear Stochastic Systems with Randomly Occurring Incomplete Information

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Hongli Dong ◽  
Zidong Wang ◽  
Xuemin Chen ◽  
Huijun Gao
Keyword(s):  
Incomplete Information ◽  
Stochastic Systems ◽  
Future Research ◽  
Missing Measurements ◽  
Parameter Uncertainties ◽  
Nonlinear Stochastic Systems ◽  
Randomly Occurring Uncertainties ◽  
Analysis And Synthesis ◽  
System States ◽  
And Control

In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modeling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent. Such a phenomenon typically appears in a networked environment. Examples include, but are not limited to, randomly occurring uncertainties, randomly occurring nonlinearities, randomly occurring saturation, randomly missing measurements and randomly occurring quantization. Randomly occurring incomplete information, if not properly handled, would seriously deteriorate the performance of a control system. In this paper, we aim to survey some recent advances on the analysis and synthesis problems for nonlinear stochastic systems with randomly occurring incomplete information. The developments of the filtering, control and fault detection problems are systematically reviewed. Latest results on analysis and synthesis of nonlinear stochastic systems are discussed in great detail. In addition, various distributed filtering technologies over sensor networks are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out.

scholarly journals Recent Advances on Recursive Filtering and Sliding Mode Design for Networked Nonlinear Stochastic Systems: A Survey

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Jun Hu ◽  
Zidong Wang ◽  
Hongli Dong ◽  
Huijun Gao
Keyword(s):  
Stochastic Systems ◽  
Sliding Mode ◽  
Future Research ◽  
Missing Measurements ◽  
Nonlinear Stochastic Systems ◽  
Design Problems ◽  
Recursive Filtering ◽  
Mode Design ◽  
Recent Advances ◽  
Randomly Occurring Uncertainties

Some recent advances on the recursive filtering and sliding mode design problems for nonlinear stochastic systems with network-induced phenomena are surveyed. The network-induced phenomena under consideration mainly include missing measurements, fading measurements, signal quantization, probabilistic sensor delays, sensor saturations, randomly occurring nonlinearities, and randomly occurring uncertainties. With respect to these network-induced phenomena, the developments on filtering and sliding mode design problems are systematically reviewed. In particular, concerning the network-induced phenomena, some recent results on the recursive filtering for time-varying nonlinear stochastic systems and sliding mode design for time-invariant nonlinear stochastic systems are given, respectively. Finally, conclusions are proposed and some potential future research works are pointed out.

scholarly journals Recent Advances on Filtering and Control for Nonlinear Stochastic Complex Systems with Incomplete Information: A Survey

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Bo Shen ◽  
Zidong Wang ◽  
Jinling Liang ◽  
Yurong Liu
Keyword(s):  
Complex Systems ◽  
Incomplete Information ◽  
Stochastic Systems ◽  
Future Research ◽  
Control Problems ◽  
Missing Measurements ◽  
Recent Advances ◽  
Future Research Directions ◽  
Control Technologies ◽  
And Control

Some recent advances on the filtering and control problems for nonlinear stochastic complex systems with incomplete information are surveyed. The incomplete information under consideration mainly includes missing measurements, randomly varying sensor delays, signal quantization, sensor saturations, and signal sampling. With such incomplete information, the developments on various filtering and control issues are reviewed in great detail. In particular, the addressed nonlinear stochastic complex systems are so comprehensive that they include conventional nonlinear stochastic systems, different kinds of complex networks, and a large class of sensor networks. The corresponding filtering and control technologies for such nonlinear stochastic complex systems are then discussed. Subsequently, some latest results on the filtering and control problems for the complex systems with incomplete information are given. Finally, conclusions are drawn and several possible future research directions are pointed out.

scholarly journals Feedback Stabilization for a Class of Nonlinear Stochastic Systems with State- and Control-Dependent Noise

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Yu-Hong Wang ◽  
Tianliang Zhang ◽  
Weihai Zhang
Keyword(s):  
State Feedback ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Feedback Stabilization ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Global State ◽  
Nonlinear Stochastic Systems ◽  
Feedback Stabilizability ◽  
And Control

This paper mainly studies the state feedback stabilizability of a class of nonlinear stochastic systems with state- and control-dependent noise. Some sufficient conditions on local and global state feedback stabilizations are given in linear matrix inequalities (LMIs) and generalized algebraic Riccati equations (GAREs). Some obtained results improve the previous work.

scholarly journals Performance Analysis with Network-Enhanced Complexities: On Fading Measurements, Event-Triggered Mechanisms, and Cyber Attacks

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Derui Ding ◽  
Zidong Wang ◽  
Hongli Dong ◽  
Yurong Liu ◽  
Bashir Ahmad
Keyword(s):  
Performance Analysis ◽  
Large Scale ◽  
Filter Design ◽  
Cyber Attacks ◽  
Networked Systems ◽  
Future Research ◽  
Dynamical Characteristic ◽  
Parameter Uncertainties ◽  
Analysis And Synthesis ◽  
Event Triggered

Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.

Robust H∞ Control for Uncertain Nonlinear Stochastic Systems with Delayed State and Control

2011 ◽  
Vol 58-60 ◽  
pp. 685-690
Author(s):  
Cheng Wang ◽  
Yun Xu
Keyword(s):  
Linear Matrix Inequalities ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Nonlinear Stochastic Systems ◽  
Stochastically Stable ◽  
Nonlinear Uncertain Systems ◽  
And Control

This paper considers the issue of robust H∞ control for a class of nonlinear uncertain systems with delayed states and control, and the feedback controller is designed. By constructing proper Lyapunov-krasovskii function, the resulting closed-loop system is stochastically stable for all admissible uncertainties, time-delays and nonlinearities, and satisfies a prescribed H∞ performance. Sufficient conditions for the system to be robustly stochastically asymptotically stable are derived, by using linear matrix inequalities and Lyapunov-krasovskii stability theory. The feedback controller is obtained by solving the linear matrix inequalities. Numerical example is provided to show the validity of the proposed approaches.

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