Modular supervisory control for multi-floor manufacturing processes

Due to space availability limitations and high land costs, there is an increasing development of multi-floor manufacturing (MFM) systems in urban and industrial areas. The problem of coordination in a multi-floor manufacturing process, in the Ramadge Wonham framework, is introduced. The manufacturing chain of each floor and the elevator system are modeled in the form of finite deterministic automata. The models of the multi-floor manufacturing process are parametric with respect to the number of floors and the number of manufacturing machines on each floor. The coordination desired performance is formulated in the form of desired regular languages in analytic forms. The languages are realized by appropriate supervisors in the form of finite deterministic automata. The models of the supervisors are also parametric with respect to the number of floors and the number of manufacturing machines on each floor. The total control of the coordination of the multi-floor manufacturing process is accomplished via a modular supervisory control architecture. The complexity of the supervisors as well as the complexity of the total modular supervisory architecture are determined in analytic forms with respect to the number of floors and the number of manufacturing machines on each floor. The special case of a two floor manufacturing process is presented as an illustrative example.     

Observer-based robust stabilization for uncertain systems with unknown time-varying delay

This paper focuses on the problem of robust stabilization for a class of linear systems with uncertain parameters and time varying delays in states. The parameter uncertainty is continuous, time varying, and norm-bounded. The state delay is unknown and time varying. The states of the system are not all measurable and an observer is constructed to estimate the states. If a linear matrix inequality (LMI) is solvable, the gains of the controller and observer can be obtained from the solution of the LMI. The observer and controller are dependent on the size of time delay and on the size of delay derivative. Finally, an example is given to illustrate the effectiveness of the proposed control method.     

Regional gradient observability for semilinear hyperbolic systems: HUM approach

The paper aims to extend the notion of regional observability of the gradient to the semilinear hyperbolic case, in order to reconstruct the gradient of the initial conditions in a subregion $\omega$ of the domain evolution $\varOmega$. We start with an asymptotically linear system, the approach is based on an extension of the Hilbert uniqueness method (HUM) and Schauder''s fixed point theorem. The analysis leads to an algorithm which is successfully numerically implemented and illustrated with examples and simulations.     

A Heuristic Algorithm for Task Scheduling Based on Mean Load on Grid

Efficient task scheduling is critical to achieving high performance on grid computing environment. The task scheduling on grid is studied as optimization problem in this paper. A heuristic task scheduling algorithm satisfying resources load balancing on grid environment is presented. The algorithm schedules tasks by employing mean load based on task predictive execution time as heuristic information to obtain an initial scheduling strategy. Then an optimal scheduling strategy is achieved by selecting two machines satisfying condition to change their loads via reassigning their tasks under the heuristic of their mean load. Methods of selecting machines and tasks are given in this paper to increase the throughput of the system and reduce the total waiting time. The efficiency of the algorithm is analyzed and the performance of the proposed algorithm is evaluated via extensive simulation experiments. Experimental results show that the heuristic algorithm performs significantly to ensure high load balancing and achieve an optimal scheduling strategy almost all the time. Furthermore, results show that our algorithm is high efficient in terms of time complexity.     

Using a Student Model to Improve Explanation in an ITS

This paper presents the use of a student model to improve the explanations provided by an intelligent tutoring system,namely SimpleQuestl,in the domain of electronics.The method of overlay modelling is adopted to build the studdent model.The diagnosis is based on the comparison of the behaviours of the student and the expert.The student model is consulted by the “explainer”and “debugging”procedures in order to re-order the sequence of the explanation.     

Second Attribute Algorithm Based on Tree Expression

One view of finding a personalized solution of reduct in an information system is grounded on the viewpoint that attribute order can serve as a kind of semantic representation of user requirements. Thus the problem of finding personalized solutions can be transformed into computing the reduct on an attribute order. The second attribute theorem describes the relationship between the set of attribute orders and the set of reducts, and can be used to transform the problem of searching solutions to meet user requirements into the problem of modifying reduct based on a given attribute order. An algorithm is implied based on the second attribute theorem, with computation on the discernibility matrix. Its time complexity is O（n^2 × m） （n is the number of the objects and m the number of the attributes of an information system）. This paper presents another effective second attribute algorithm for facilitating the use of the second attribute theorem, with computation on the tree expression of an information system. The time complexity of the new algorithm is linear in n. This algorithm is proved to be equivalent to the algorithm on the discernibility matrix.     

Adaptive control of permanent magnet synchronous machines with disturbance estimation

In this paper,an adaptive control scheme is introduced for permanent magnet synchronous machines (PMSMs)as an alternative to classical control techniques.The adaptive control strategy capitalizes on the machine’s inverse dynamics to achieve accurate tracking by using an observer to approximate disturbance in the form of friction and load torque.The controller’s output is then fed to a space vector pulse width modulation(SVPWM)algorithm to produce duty cycles for the inverter.The control scheme is validated through a set of simulations on an experimentally validated PMSM model.Results for different situations highlight its high speed tracking accuracy and high performance in compensating for friction and load disturbances of various magnitudes.     

Design and implementation of the virtual machine constructing on register

The technology of virtual machines is widely applied in many fields, such as code transplanting, cross-platform computing, and hardware simulation. The main purpose is to simulate the environment of general hardware by means of software and realize the operation of byte codes in processor. Virtual machines are commonly used to distribute programs in an architecture-neutral format, which can easily be interpreted or compiled. A long-running question in the design of virtual machines is whether stack architecture or register architecture can be implemented more efficiently with an interpreter. After introducing the basic theory, a solution to designing and realizing virtual machine constructing on register processor proposed in this paper, which gives a preliminary study on simulating the process of instructions in Intel x86.     

An extended processing scheme for coherent integration and parameter estimation based on matched filtering in passive radar

In passive radars, coherent integration is an essential method to achieve processing gain for target detection. The cross ambiguity function （CAF） and the method based on matched filtering are the most common approaches. The method based on matched filtering is an approximation to CAF and the procedure is： （1） divide the signal into snapshots; （2） perform matched filtering on each snapshot; （3） perform fast Fourier transform （FFT） across the snapshots. The matched filtering method is com- putationally affordable and can offer savings of an order of 1000 times in execution speed over that of CAF. However, matched filtering suffers from severe energy loss for high speed targets. In this paper we concentrate mainly on the matched filtering method and we use keystone transform to rectify range migration. Several factors affecting the performance of coherent integration are discussed based on the matched filtering method and keystone transform. Modified methods are introduced to improve the performance by analyzing the impacts of mismatching, precision of the keystone transform, and discretization. The modified discrete chirp Fourier transform （MDCFT） is adopted to rectify the Doppler expansion in a multi-target scenario. A novel velocity estimation method is proposed, and an extended processing scheme presented. Simulations show that the proposed algorithms improve the performance of matched filtering for high speed targets.     

Online approach to feature interaction problems in middleware based system

As a popular infrastructure for distributed systems running on the Internet, middleware has to support much more diverse and complex interactions for coping with the drastically increasing demand on information technology and the extremely open and dynamic nature of the Internet. These supporting mechanisms facilitate the development, deployment, and integration of distributed systems, as well as increase the occasions for distributed systems to interact in an undesired way. The undesired interactions may cause serious problems, such as quality violation, function loss, and even system crash. In this paper, the problem is studied from the perspective of the feature interaction problem （FIP） in telecom, and an online approach to the detection and solution on runtime systems is proposed. Based on a classification of middleware enabled interactions, the existence of FIP in middleware based systems is illustrated by four real cases and a conceptual comparison between middleware based systems and telecom systems. After that, runtime software architecture is employed to facilitate the online detection and solution of FIP. The approach is demonstrated on J2EE （Java 2 Platform Enterprise Edition） and applied to detect and resolve all of the four real cases.     

A virtual network mapping algorithm based on integer programming

The virtual network （VN） embedding/mapping problem is recognized as an essential question of network virtualization. The VN embedding problem is a major challenge in this field. Its target is to efficiently map the virtual nodes and virtual links onto the substrate network resources. Previous research focused on designing heuristic-based algorithms or attempting two-stage solutions by solving node mapping in the first stage and link mapping in the second stage. In this study, we propose a new VN embedding algorithm based on integer programming. We build a model of an augmented substrate graph, and formulate the VN embedding problem as an integer program with an objective function and some constraints. A factor of topology-awareness is added to the objective function. The VN embedding problem is solved in one stage. Simulation results show that our algorithm greatly enhances the acceptance ratio, and increases the revenue/cost （R/C） ratio and the revenue while decreasing the cost of the VN embedding problem.     

Bitstream decoding and SEU-induced failure analysis in SRAM-based FPGAs

Reconfigurable SRAM-based FPGAs are highly susceptible to radiation induced single-event upsets (SEUs) in space applications.The bit flip in FPGAs configuration memory may alter user circuit permanently without proper bitstream reparation,which is a completely different phenomenon from upsets in traditional memory devices.It is important to find the relationship between a programmable resource and corresponding control bit in order to understand the impact of this effect.In this paper,a method is proposed to decode the bitstream of FPGAs from Xilinx Corporation,and then an analysis program is developed to parse the netlist of a specific design to get the configuration state of occupied programmable logic and routings.After that,an SEU propagation rule is established according to the resource type to identify critical logic nodes and paths,which could destroy the circuit topological structure.The decoded relationship is stored in a database.The database is queried to get the sensitive bits of a specific design.The result can be used to represent the vulnerability of the system and predict the on orbit system failure rate.The analysis tool was validated through fault injection and accelerator irradiation experiment.     

A loop-based apparatus for at-speed self-testing

At-speed testing using external tester requires an expensive equipment,thus built-in self-test(BIST) is an alternative technique due to its ability to perform on-chip at-speed self-testing.The main issue in BIST for at-speed testing is to obtain high delay fault coverage with a low hardware overhead.This paper presents an improved loop-based BIST scheme,in which a configurable MISR (multiple-input signature register)is used to generate test-pair sequences.The structure and operation modes of the BIST scheme are described.The topological properties of the state-transition-graph of the proposed BIST scheme are analyzed.Based on it ,an approach to design and efficiently implement the proposed BIST scheme is developed.Experimental results on academic benchmark circuits are presented to demonstrate the effectiveness of the proposed BIST scheme as well as the design approach.     

Ganglion-Based Balance Design of Multi-Layer Model and Its War chfulness-Keeping

An important problem of machine vision is the balance among the efficiency, accuracy and computation cost.The visual system of man can keep watchfulness to the perimeter of a visual field and subtly process information emerging in the center of the visual field at the same time. This kind of requirement assignment of computation can virtually ease the demand of hardware both in quantity and complexity. Therefore designing an artificial model based on biological mechanism is an effective approach. In this paper a multi-layer neural model is designed based on the multi-scale receptive fields of ganglions in retina. The model can keep watch on the periphery part of a scene while processing the center information of the scene. And why it can balance the hardware complexity, processing precision and computational intensity is analyzed.An experiment is done to test the model‘s sensitivity in watchfulness keeping and its efficiency and veracity in environment sampling. This model may provide valuable inspiration in the implementation of real-time processing and the avoidance of expensive computation cost in machine vision.     

Experimental evaluation of a real-time GPU-based pose estimation system for autonomous landing of rotary wings UAVs

This paper proposes a real-time system for pose estimation of an unmanned aerial vehicle (UAV) using parallel image processing and a fiducial marker. The system exploits the capabilities of a high-performance CPU/GPU embedded system in order to provide on-board high-frequency pose estimation enabling autonomous takeoff and landing. The system is evaluated extensively with lab and field tests using a custom quadrotor. The autonomous landing is successfully demonstrated, through experimental tests, using the proposed algorithm. The results show that the system is able to provide precise pose estimation with a framerate of at least 30\,fps and an image resolution of 640?480 pixels. The main advantage of the proposed approach is in the use of the GPU for image filtering and marker detection. The GPU provides an upper bound on the required computation time regardless of the complexity of the image thereby allowing for robust marker detection even in cluttered environments.     

Convergence analysis of an incremental approach to online inverse reinforcement learning

Interest in inverse reinforcement learning (IRL) has recently increased,that is,interest in the problem of recovering the reward function underlying a Markov decision process (MDP) given the dynamics of the system and the behavior of an expert.This paper deals with an incremental approach to online IRL.First,the convergence property of the incremental method for the IRL problem was investigated,and the bounds of both the mistake number during the learning process and regret were provided by using a detailed proof.Then an online algorithm based on incremental error correcting was derived to deal with the IRL problem.The key idea is to add an increment to the current reward estimate each time an action mismatch occurs.This leads to an estimate that approaches a target optimal value.The proposed method was tested in a driving simulation experiment and found to be able to efficiently recover an adequate reward function.     

AVS Intellectual Property Rights (IPR) Policy

The AVS Workgroup has developed an IPR Policy to facilitate the adoption of standards in the marketplace The policy is based on consideration of IPR issues in parallel with the technical work for drafting the standard. The paper describes the relationship between IPR and the standard, and how the goals for the standard must be complemented by goals for the IPR. The existing IPR policies of the ITU and ISO are outlined, and then the AVS IPR policy is described, organized by its three main components： commitment to license on declared basic terms, disclosure of intellectual property, and protection of IPR.     

Secure System Modeling: Integrating Security Attacks with Statecharts

Software security is becoming an important concern as software applications are increasingly depending on the Internet, an untrustworthy computing environment. Vulnerabilities due to design errors, inconsistencies, incompleteness, and missing constraints in software design can be wrongly exploited by security attacks. Software functionality and security, however, are often handled separately in the development process. Software is designed with the mindset of its functionalities and cost, where the focus is mainly on the operational behavior. Security concerns, on the other hand, are often described in an imprecise way and open to subjective interpretations. This paper presents a threat driven approach that improves on the quality of software through the realization of a more secure model. The approach introduces systematic transformation rules and integration steps for integrating attack tree representations into statechart-based functional models. Through the focus on the behavior of an attack from the perspective of the system behavior, software engineers can clearly define and understand security concerns as software is designed. Security analysis and threat identification are then applied to the integrated model in order to identify and mitigate vulnerabilities at the design level.     

Counterworking the Operation Disturbance of a Radiators Structure due to External Actions

The operation of a complicated radiators structure creating a required field in a given area is disturbed often due to different external actions. As an example, the impact of metallic objects approaching off to an antenna system with minimal irradiation on user＇s body is analyzed. In this case, the zone itself, where the area of a weak field （a dark spot） is created, is generally not approachable for sensors installation. In order to counteract the disturbance of the system operation due to presence of different metallic objects in close proximity to the radiators, two methods based on two information sources are studied. These information sources are antennas driving currents and fields at a predetermined point outside the given area. As an example, the antenna system used in the compensation method for reducing human＇s body irradiation, to which a metal object approaches, is analyzed. The conditions of severe external actions are considered： a great metal body and a small distance from this body to the dark spot. It is shown that under these conditions of severe external actions the second method based on the field values measuring demonstrates a higher efficiency. A block scheme for structure of an automatic adjustment is suggested. The considered problem is a common one, and developers of radio circuits are faced with them constantly.     

Ganglion-Based Balance Design of Multi-Layer Model and Its Watchfulness-Keeping

An important problem of machine vision is the balance among the efficiency, accuracy and computation cost. The visual system of man can keep watchfulness to the perimeter of a visual field and subtly process information emerging in the center of the visual field at the same time. This kind of requirement assignment of computation can virtually ease the demand of hardware both in quantity and complexity. Therefore designing an artificial model based on biological mechanism is an effective approach. In this paper a multi-layer neural model is designed based on the multi-scale receptive fields of ganglions in retina. The model can keep watch on the periphery part of a scene while processing the center information of the scene. And why it can balance the hardware complexity, processing precision and computational intensity is analyzed. An experiment is done to test the model's sensitivity in watchfulness keeping and its efficiency and veracity in environment sampling. This model may provide valuable inspiration in the implementation of real-time processing and the avoidance of expensive computation cost in machine vision.