Earticle

An integrated coupled control strategy for a servicing spacecraft autonomously approaching and docking with a freely tumbling target is studied. To implement capturing successfully, the docking port of the servicing spacecraft should be always pointing to the docking port of target during close rendezvous and docking, which involves proximity maneuvering of coupled position and attitude simultaneously. The integrated coupled control is accomplished through a robust sliding mode control for coupled relative position and attitude tracking. In order to design the integrated coupled control law, the integrated coupled dynamics of relative position and attitude is established through relative position vector and relative attitude quaternion. Then, based on the integrated coupled dynamics, an integrated coupled control law is designed through a robust sliding mode control technique which is constructed by two sliding surfaces. The convergence of sliding surfaces and tracking error are guaranteed in presence of unknown but bounded disturbances and model uncertainties. The robustness of the proposed control law to measurement noise is also analyzed. Finally, three numerical simulation scenarios are conducted and the results validate the effectiveness and robustness of the integrated coupled control law.

The class of Basis Function Piecewise-affine (BPWA) functions is an ideal model structure for nonlinear and hybrid system identification. This paper proposes a parameter space decomposition theorem for BPWA functions. It is proved that any BPWA function has a decomposed parametric representation, in which the algebraic and geometrical parameters can be identified separately. Under the assumption of invariant geometrical structure, a recursive algorithm is proposed to identify the BWPA AutoRegressive Exogenous models from the input-output data. Two benchmark examples are illustrated to show that the proposed algorithm has much higher computational efficiency compared with the competing algorithms with the same identification accuracy.

In this paper, we consider the problem of delay-dependent H1 control of a class of linear uncertain systems with interval time-varying delay and norm-bounded uncertainties using Lyapunov-Krasovskii approach. By exploiting a candidate Lyapunov-Krasovakii (LK) functional and using slack matrix variables in the delay-dependent stability analysis, a less conservative stability criterion is first derived in terms of linear matrix inequalities (LMIs). Subsequently, based on the criterion obtained, a delay-dependent condition for the existence of a static state feedback controller, which ensures asymptotic stability as well as a prescribed H1 performance of the closed loop system for all admissible uncertainties, is deduced. A numerical example is employed to demonstrate the effectiveness of the proposed controller.

Mobile IPv6 is a network-layer solution to node mobility for the IPv6 Internet. It allows a mobile node to maintain a continuous connection from one access point to another. MIPv6 introduces several security vulnerabilities such as the authentication and authorization of Binding Updates (BUs) during the home agent registration process. This paper deals with securing the standard mobile IPv6 handover scheme by adding a cryptography procedure for authenticating the binding updates sent by mobile nodes during the home agent registration process.

This paper explains about a neural network based control scheme to determine trajectory control parameters i.e. velocity, acceleration and jerk for a industrial robot performing a defined task. The proposed approach is the blend of quintic B-spline and neural network system for prediction of joint control parameters. The proposed approach is applied to a case of three robot trajectory control problem. The same problem is solved using a RobotiCad toolbox of matlab. The performance of the proposed approach is compared with the output of toolbox based on the total time and the torque consumed for the completion of the desired task.

This paper proposes a method of simulating the movements of the human body by automatically extracting the characteristics of an object from a camera and sending them to mobile devices. In this method, a RGB color video from a camera was converted into hue, saturation, and intensity images for extracting the silhouettes of the human body using digital subtraction of the images. Using the corner points and modeling information from the extracted silhouettes, joints are automatically detected and used as each connection points of the object. Also, block-matching algorithms were applied to extracted joints to track the characteristics, which are sent to mobile devices. On the mobile devices, body movements are simulated using the received joints. The results showed that the method automatically detects silhouettes and joints and effectively simulates the human body using the extracted joints. Also, the tracking of the joints were reflected in the mapped body, allowing for appropriate tracking the movements.

This paper examines single input single output (SISO) chattering free variable structure control (VSC) which controller coefficient is on-line tuned by fuzzy backstepping algorithm. VSC methodology is selected as a framework to construct the control law and address the stability and robustness of the close loop system based on Lyapunove formulation. The main goal is to guarantee acceptable trajectories tracking between the robot arm actual output and the desired input. The proposed approach effectively combines the design technique from variable structure controller is based on Lyapunov and fuzzy estimator to estimate the nonlinearity of undefined system dynamic in backstepping controller. The input represents the function between variable structure function, error and the rate of error. The outputs represent fuel ratio, respectively. The fuzzy backstepping methodology is on-line tune the variable structure function based on adaptive methodology. The performance of the SISO VSC which controller coefficient is on-line tuned by fuzzy backstepping algorithm (FBSAVSC) is validated through comparison with VSC and proposed method. Simulation results signify good performance of trajectory in presence of uncertainty and external disturbance.

Modeling has traditionally been an important part of the multimedia software development process as it allows developers to tackle complex problems by using abstraction and hiding technical details. A models goal is to predict problems early on in design phases to avoid problems during implementation. Since defects can be detected earlier on in the software development process, the use of models reduces maintenance costs. Model-based software development is used for more than just visualizing the code or design of the system; it is used to produce source code directly from the model. Traditional model management and service system which is the key component of DSS only supports the single format model in the special application field. Based on requirements of multi-model-aided decision, this paper designs the general model management and service system which provides the general management and service for different format models on network. The system proposes the solution to manage different format models by providing model frame generator which aims to analyze decision problem top-down and model application frame which aims to integrate model function bottom-up.

The walking beam furnace (WBF) plays a critical role in a steel production factory, and has complex nonlinear dynamic behaviour. Thus, using the conventional physical principles to build a model of the process leads to a time-consuming modeling procedure and when the number of operating set-points in walking beam furnace increases the conventional modeling problem difficultly will be solved, indeed analytical models cannot be applied or can not give satisfactory results. This paper proposes intelligent nonlinear simulator model for a real walking beam furnace in a steel production factory using nonlinear sub-system identification technique based on the recurrent local linear neuro-fuzzy (RLLNF) network. This model is trained using the local linear model tree (LOLIMOT) algorithm, which is a tree-structure divide-and-conquer algorithm. It is the first time that such nonlinear simulator (recurrent) model for a real WBF based on locally linear neuro-fuzzy modelling is developed. The recorded data of Iran Alloy Steel Company are used to identify and evaluate the RLLNF simulator model of walking beam furnace.

In aiming for service innovation, mobile operators are in the process of providing an environment that encourages third parties to create a wide variety of Web applications by making use of an application programming interface that the network offers. This paper presents an analysis method for dealing with API-oriented traffic, one of the major operational challenges in the coming IMS era which must be overcome in developing a highly stable and reliable communication system. We addressed this issue by extending traffic evaluation methods used for the commercial i-mode service in Japan. API traffic models are defined based on process sequences and the user packets invoked by an API request and these models are used in the performance evaluation of nodes in a system. We found that API traffic can have a large impact on the CPU use of the gateway modules. Thus, network capacity planning should take account of the impact of estimated API traffic on a mobile network. Our proposal allows mobile operators to construct a highly stable and reliable system which supports service innovation by providing APIs to application developers.

In this paper, the light pollution at night is about the urban landscape. Light pollution, improve the aesthetic, visual and so ensure the safety of existing lighting causes excessive light, visual interference means. In terms of new pollution, light pollution is one of the nightscape of the city is analyzed. In addition, part of astronomical observations are analyzed with respect to light. So the improvement of lighting in light pollution measures, lighting changes the wavelength of the light-sensitive compensation rate according to the method by considering the light distribution design is proposed.

As mobile technologies are getting smarter using various environmental awareness technologies, so too are the mobile learning environment harnesses of smart technologies. Instead of the learner and mobile device being at a fixed and predetermined location, a mobile learning environment fosters free movement while connected to a server with a wireless network. Therefore, in addition to traditional user information, the learning environment needs to provide adequate location based learning materials to the learner. In this paper, how such smart learning technologies can be integrated into a learning system to compose a smart educational agent that utilizes location awareness technology such as GPS and dialogue-based feedback systems in order to provide real-life situated learning environments to users will be introduced.

The 3 Degree-of-Freedom (DOF) crane represents one of the most widely deployed real-world platforms in the world today. It uses levers and pulleys for gripping, lifting and moving loads horizontally, as well as lowering and releasing the gripper to the original position. Hence the system produces swing angle which need to be controlled so that the payload could be transferred efficiently. The existing 3 DOF systems used conventional Linear Quadratic Regulator (LQR) controller to control the position and swing angle. This project report proposed the usage of Fuzzy Logic Controller (FLC) in place of LQR controller. FLC has a simpler and practical design approached. It avoids laborious mathematical formulation and computation thus reducing operating time. The FLC performance for position control and anti-swing control are compared with LQR controller using MATLAB simulation. The simulation results showed, under laboratory limitation, that FLC performed better compared to the conventional LQR controller.

IPv6 nodes use the Neighbor Discovery Protocol (NDP) to discover other nodes on the link, to determine their link-layer addresses to find routers, and to maintain reachability information about the paths to active neighbors. Secure Neighbor Discovery Protocol (SEND Protocol) is a security extension of Neighbor Discovery. The SEND protocol is designed to counter the threats to NDP. This paper presents the threats and security analysis for SEND and all the possible security options for more secure IPv6 Neighbor Discovery Protocol.