Commenting in the Online Arab Public Sphere: Debating the Swiss Minaret Ban and the “Ground Zero Mosque” Online

This article focuses on the emerging online Arab public sphere that the web has enabled. It explores how the “local” interacts with the “global,” critically examining their implications on global politics. Specifically looking at online readers' comments about the Swiss minaret ban the so‐called “Ground Zero Mosque,” how does the Arab online public sphere respond to and frame these issues? What implications do these reader frames portend locally and globally? The study analyzes online comments and responses that readers of Al Arabiya.net and Al Jazeera.net posted on related news articles. The article concludes that the new online public sphere does make it possible for Arab citizens to circumvent and challenge traditional authoritarian controls.     

A new model of job design: Initial evidence and implications for future research

Clegg and Spencer's (2007) model of job design synthesizes and extends recent conceptions of the job design process by incorporating variables such as knowledge, motivation, and trust into a cyclical and dynamic system. The objective of this study was to examine the sequential organization of variables that comprise the model, as a basis from which to justify further investigations of the model's dynamic properties. Data were collected via questionnaires from 432 participants in two work organizations. Results obtained from structural equation modeling are broadly supportive of the proposed relationships between the variables. Implications of this initial study for future research and practice are discussed. © 2011 Wiley Periodicals, Inc.     

MicroPort: A general simulation platform for seaport container terminals

Seaport container terminals are essential nodes in sea cargo transportation networks. As such, the operational efficiency of container terminals in handling containers passing through them plays a critical role in a globalized world economy. Many models and algorithms have been developed to address various decision problems in container terminals to help improve operational efficiency. These decision support tools are usually used separately for specific purposes. However, the problems they are trying to tackle are often interrelated. Therefore, in this regard, an evaluation tool which can capture as many operational conditions as possible for different decision problems is necessary. This paper introduces a general simulation platform, named MicroPort, which aims to provide an integrated and flexible modeling system for evaluating the operational capability and efficiency of different designs of seaport container terminals. The software structure of MicroPort comprises three programming layers: (1) the Functions layer; (2) the Applications layer; and (3) the Extensions layer. Different layers are bound by Application Programming Interfaces (APIs). Basic functions built in the Functions layer support the Applications layer in which major operation processes can be modeled by an agent-based method. External modules and decision support tools in the Extensions layer then use APIs to adjust the system to produce suitable simulation models for specific purposes.     

Semi‐Global Output Feedback Stabilization for a Class of Uncertain Nonlinear Systems

This paper addresses the problem of semi‐global stabilization by output feedback for a class of nonlinear systems whose output gains are unknown. For each subsystem, we first design a state compensator and use the compensator states to construct a control law to stabilize the nominal linear system without the perturbing nonlinearities. Then, combining the output feedback domination approach with block‐backstepping scheme, a series of homogeneous output feedback controllers are constructed recursively for each subsystem and the closed‐loop system is rendered semi‐globally asymptotically stable.     

Optimal Performance in Tracking Stochastic Signal Under Disturbance Rejection

The analysis method of optimal tracking performance is proposed for multiple‐input multiple‐output (MIMO) linear time‐invariant (LTI) systems under disturbance rejection. An H₂ criterion of the error signal between the output of the plant and the reference signal is used as a measure for the tracking performance. Spectral factorization is applied to obtain the optimal solution of the system tracking error. The explicit expressions are derived for this minimal tracking error with respect to random reference signals under disturbance rejection. It is shown that the nonminimum phase zeros, the zero direction, the unstable poles, the pole direction of a given plant, statistical characteristics of the reference input signal, and disturbance signal have a negative effect on a feedback system's ability to reduce the system error with disturbance rejection. The results show that the optimal tracking performance will further be damaged because of disturbance rejection. Some typical examples are given to illustrate the theoretical results.     

An Intelligent Robust Tracking Control for a Class of Electrically Driven Mobile Robots

This paper addresses the problem of designing robust tracking control for a class of uncertain wheeled mobile robots actuated by brushed direct current motors. This class of electrically‐driven mechanical systems consists of the robot kinematics, the robot dynamics, and the wheel actuator dynamics. Via the backstepping technique, an intelligent robust tracking control scheme that integrates a kinematic controller and an adaptive neural network‐based (or fuzzy‐based) controller is developed such that all of the states and signals of the closed‐loop system are bounded and the tracking error can be made as small as possible. Two adaptive approximation systems are constructed to learn the behaviors of unknown mechanical and electrical dynamics. The effects of both the approximation errors and the unmodeled time‐varying perturbations in the input and virtual‐input weighting matrices are counteracted by suitably tuning the control gains. Consequently, the robust control scheme developed here can be employed to handle a broader class of electrically‐driven wheeled mobile robots in the presence of high‐degree time‐varying uncertainties. Finally, a simulation example is given to demonstrate the effectiveness of the developed control scheme.     

Memoryless SMC Design Methods for Stochastic Delay Systems

Recently, the sliding mode control (SMC) method has been extended to accommodate stochastic systems. Particularly, restrictive assumption on the structure of the control systems have been removed and a practical SMC design method for stochastic systems has been presented. This paper continues this line of research and studies the SMC methods for stochastic systems with state delay in diffusion. Both delay‐independent and delay‐dependent approaches are investigated. Essentially, this paper studies SMC design methods with memoryless controllers for time delay systems, which has been a problem in the past decades.     

Fuzzy Identification of Nonlinear Systems via Orthogonal Transform

This paper is concerned with the application of orthogonal transforms and fuzzy competitive learning to extract fuzzy rules from data. The least square algorithm with orthogonal transforms is proposed to supervise the progress of fuzzy competitive learning. First of all, competitive learning takes place in the product space of system inputs and outputs and each cluster corresponds to a fuzzy IF–THEN rule. The fuzzy relation matrix, confirmed by fuzzy competitive learning, is studied by the orthogonal least square algorithm. The validity of fuzzy rules is obtained by analyzing the effect of orthogonal vectors in the fuzzy model, and subsequently removing less important ones. The structure identification and parameter identification of the fuzzy model are simultaneously confirmed in the proposed algorithm. Using simulation results as an example, the fuzzy model of non‐linear systems can be built by using the proposed algorithm. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Delay‐dependent stability for Markovian genetic regulatory networks with time‐varying delays

This paper is concerned with the problem of stochastic stability analysis for a class of genetic regulatory networks with Markovian jump parameters and time‐varying delays. A delay‐dependent stability criterion is derived by using a novel mode‐dependent Lyapunov functional. The derived stability criterion is expressed in terms of linear matrix inequalities and is less conservative than the existing ones in the literature. A numerical example is provided to demonstrate the effectiveness of the proposed stability criterion. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Stabilization of impulsive hybrid systems using quantized input and output feedback

In this paper, we consider the feedback stabilization of impulsive control systems with quantized input and output signals. To study the problem, the notions of quasi‐invariant sets and attracting sets for impulsive systems with quantization are introduced first, and then applied to the control design. Hybrid quantized control schemes are proposed to stabilize the considered impulsive linear or nonlinear systems via either input or output feedback. Mathematical analysis and numerical simulations are given to show the principle and effectiveness of the proposed designs. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society