Modeling and verifying So S performance requirements of C4ISR systems

System-of-systems （SOS） engineering involves a com- plex process of refining high-level SoS requirements into more detailed systems requirements and assessing the extent to which the performances of to-be systems may possibly satisfy SoS capa- bility objectives. The key issue is how to model such requirements to automate the process of analysis and assessment. This paper suggests a meta-model that defines both functional and non- functional features of SoS requirements for command and control, communication, computer, intelligence, surveillance reconnais- sance （C41SR） systems. A domain-specific modeling language is defined by extending unified modeling language （UML） con- structed of class and association with fuzzy theory in order to model the fuzzy concepts of performance requirements. An effi- ciency evaluation function is introduced, based on Bezier curves, to predict the effectiveness of systems. An algorithm is presented to transform domain models in fuzzy UML into a requirements ontology in description logic （DL） so that requirements verification can be automated with a popular DL reasoner such as Pellet.

Integrated Optimal Model of Structure and Control of the Single Arm Manipulator

The integrated optimal design of mechanical and control system is discussed in terms of the performance requirement and configuration for the single arm flexible manipulator. By combination of dynamics of flexible structure and control theory, a PD feedback control system, which minimizes the settling time, has been designed. Then, the viable region of poles of the PD dosed-loop control system is decided according to overshoot and the settling time, and an integrated optimal model of structure and control of single arm manipulator is presented. Finally, the parameters of structure and control system are simultaneously optimized with respect to objective function induding the moment of inertia and the control effort of system.

Real-time total system error estimation: Modeling and application in required navigation performance

In required navigation performance（RNP）, total system error（TSE） is estimated to provide a timely warning in the presence of an excessive error. In this paper, by analyzing the underlying formation mechanism, the TSE estimation is modeled as the estimation fusion of a fixed bias and a Gaussian random variable. To address the challenge of high computational load induced by the accurate numerical method, two efficient methods are proposed for real-time application, which are called the circle tangent ellipse method（CTEM） and the line tangent ellipse method（LTEM）,respectively. Compared with the accurate numerical method and the traditional scalar quantity summation method（SQSM）, the computational load and accuracy of these four methods are extensively analyzed. The theoretical and experimental results both show that the computing time of the LTEM is approximately equal to that of the SQSM, while it is only about 1/30 and 1/6 of that of the numerical method and the CTEM. Moreover, the estimation result of the LTEM is parallel with that of the numerical method, but is more accurate than those of the SQSM and the CTEM. It is illustrated that the LTEM is quite appropriate for real-time TSE estimation in RNP application.