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This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Modeling and control of bead geometry in wire and arc additive manufacturing is significant as it affects the whole manufacturing process. The purpose of this paper is to establish an efficient model to control the bead geometry with fewer experiments in wire and arc additive manufacturing (WAAM).

A multi-sensor system is established to monitor the process parameters and measure the bead geometry information. A dynamic parameters experimental method is proposed for rapid modeling without dozens of experiments. A deep learning method is used for bead modeling and control. To adaptively control the bead geometry in real-time, a closed-loop control system was developed based on the bead model and in situ monitoring.

A series of experiments were conducted to train, test and verify the feasibility of the method and system, and the results showed that the proposed method can build the bead model rapidly with high precision, and the closed-loop system can control the forming geometry adaptively.

The proposed modeling method is novel as the experiment number is reduced. The dynamic parameters experimental method is effective with high precision. The closed-loop control system can control the bead geometry in real-time. The forming accuracy is elevated.

The present study is intended to develop an effective approach to the real-time modeling of general dynamic nonlinear systems based on the multidimensional Taylor network (MTN).

The authors present a detailed explanation for modeling the general discrete nonlinear dynamic system by the MTN. The weight coefficients of the network can be obtained by sampling data learning. Specifically, the least square (LS) method is adopted herein due to its desirable real-time performance and robustness.

Compared with the existing mainstream nonlinear time series analysis methods, the least square method-based multidimensional Taylor network (LSMTN) features its more desirable prediction accuracy and real-time performance. Model metric results confirm the satisfaction of modeling and identification for the generalized nonlinear system. In addition, the MTN is of simpler structure and lower computational complexity than neural networks.

Once models of general nonlinear dynamical systems are formulated based on MTNs and their weight coefficients are identified using the data from the systems of ecosystems, society, organizations, businesses or human behavior, the forecasting, optimizing and controlling of the systems can be further studied by means of the MTN analytical models.

MTNs can be used as controllers, identifiers, filters, predictors, compensators and equation solvers (solving nonlinear differential equations or approximating nonlinear functions) of the systems of ecosystems, society, organizations, businesses or human behavior.

The operating efficiency and benefits of social systems can be prominently enhanced, and their operating costs can be significantly reduced.

Nonlinear systems are typically impacted by a variety of factors, which makes it a challenge to build correct mathematical models for various tasks. As a result, existing modeling approaches necessitate a large number of limitations as preconditions, severely limiting their applicability. The proposed MTN methodology is believed to contribute much to the data-based modeling and identification of the general nonlinear dynamical system with no need for its prior knowledge.

This article deals with how to test for and evaluate interdependence among control practices in a management control system using structural equation modeling. Empirical research on the levers of control (LOC) framework is used as an example. In LOC research, a path model approach to interdependence has been developed. The appropriateness of this approach is evaluated, developed, and compared with the correlation of residuals approach (seemingly unrelated regression) implemented in the wider complementarity literature. Empirical examples of the different models are shown and compared by using a data set on LOC of 120 SBUs in Sweden. The empirical results show that modeling interdependence among control practices in a management control system as non-recursive (bi-directional) paths or as residual correlations evidently affects the conclusions drawn about interdependence in terms of both presence and magnitude. The two models imply different views on how to conceptualize interdependence and are not statistically and empirically comparable. If using non-recursive path models, several model specification issues appear. To be able to identify such models, this needs to be carefully considered in the theory and research design prior to data collection.

The purpose of this paper is to give reviews on the platform modeling and design of a controller for autonomous vertical take-off and landing (VTOL) tilt rotor hybrid unmanned aerial vehicles (UAVs). Nowadays, UAVs have experienced remarkable progress and can be classified into two main types, i.e. fixed-wing UAVs and VTOL UAVs. The mathematical model of tilt rotor UAV is time variant, multivariable and non-linear in nature. Solving and understanding these plant models is very complex. Developing a control algorithm to improve the performance and stability of a UAV is a challenging task.

This paper gives a thorough description on modeling of VTOL tilt rotor UAV from first principle theory. The review of the design of both linear and non-linear control algorithms are explained in detail. The robust flight controller for the six degrees of freedom UAV has been designed using H-infinity optimization with loop shaping under external wind and aerodynamic disturbances.

This review will act as a basis for the future work on modeling and control of VTOL tilt rotor UAV by the researchers. The development of self-guided and fully autonomous UAVs would result in reducing the risk to human life. Civil applications include inspection of rescue teams, terrain, coasts, border patrol buildings, police and pipelines. The simulation results show that the controller achieves robust stability, good adaptability and robust performance.

The review articles on quadrotors/quadcopters, hybrid UAVs can be found in many literature, but there are comparatively a lesser amount of review articles on the detailed description of VTOL Tilt rotor UAV. In this paper modeling, platform design and control algorithms for the tilt rotor are presented. A robust H-infinity loop shaping controller in the presence of disturbances is designed for VTOL UAV.

Traditionally, progress in detail engineering in construction projects is reported based on estimates and manual input from the disciplines in the engineering team. Reporting progress on activities in an engineering schedule manually, based on subjective evaluations, is time consuming and can reduce accuracy, especially in larger and multi-disciplinary projects. How can progress in detail engineering be reported using BIM and connected to activities in an engineering schedule? The purpose of this paper is to introduce a three-step process for reporting progress in detail engineering using building information modeling (BIM) to minimize manual reporting and increase quality and accuracy.

The findings of this paper are based on the studies of experiences from the execution of projects in the oil and gas industry. Data are collected from an engineering, procurement and construction (EPC) contractor and two engineering contractors using case study research.

In the first step, control objects in building information models are introduced. Statuses are added to control objects to fulfill defined quality levels related to milestones. In the second step, the control objects with statuses are used to report visual progress and aggregated in an overall progress report. In the third step, overall progress from building information models are connected to activities in an engineering schedule.

Existing research works related to monitoring and reporting progress using a BIM focus on construction and not on detail engineering. The research demonstrates that actual progress in detail engineering can be visualized and reported through the use of BIM and extracted to activities in an engineering schedule through a three-step process.

Business process models, while primarily intended for process documentation, communication, and improvement, are often also used as input for developing process-oriented software systems (Ouyang et al., 2009). Ensuring correctness, handling complexity, and improving reusability and maintainability of business process models are important for all these goals. The purpose of this paper is to propose an aspect-oriented business process modeling and correctness controlling method based on Petri nets to satisfy these goals.

The aspect-oriented paradigm provides a proper mechanism to modularization, and thus reduces the complexity of models, and also improves reusability and maintainability. However, weaving aspects into base processes may bring in mistakes or errors. To ensure correctness of modeling, this paper presents a formal approach to modeling aspect-oriented business processes and a method to ensure modeling correctness. Petri net is used as the process modeling language and its analysis techniques are applied to analyze the correctness of modeling. Two types of correctness, specifically, aspect-aspect correctness and base-aspect correctness are analyzed. A real banking process model is studied systematically in the case study to evaluate the approach and the performance assessments are conducted to show the cost and effect of the approach.

Designing aspect-oriented business process models help organizations reusing the model elements to reduce redundancy of their model repository, improving their maintainability, and supporting them to adapt to the changes of business requirements with flexible modeling. It is important to stress that the correctness of business process modeling is important in ensuring the quality of the models, especially in the safety-critical business domains, such as financial business domain.

In this paper, separation of concerns is used to separate the cross-cutting activities and core activities in accordance with the different functions of these activities, and an approach to modeling aspect-oriented business processes is proposed. First, the cross-cutting activities are encapsulated as aspects, while core business activities are modeled as base processes. Then, according to the correctness requirements of business process models, based on the weaving mechanisms of aspect-oriented approach, weaving correctness is defined. Weaving correctness controlling methods between multi-aspects and between aspects and base processes are designed. Errors or mistakes of aspect-oriented business process modeling are prevented during the procedure of modeling to ensure error-free business process modeling.

This paper aims to provide a mathematical modeling and design of H-infinity controller for an autonomous vertical take-off and landing (VTOL) Quad Tiltrotor hybrid unmanned aerial vehicles (UAVs). The variation in the aerodynamics and model dynamics of these aerial vehicles due to its tilting rotors are the key issues and challenges, which attracts the attention of many researchers. They carry parametric uncertainties (such as non-linear friction force, backlash, etc.), which drives the designed controller based on the nominal model to instability or performance degradation. The controller needs to take these factors into consideration and still give good stability and performance. Hence, a robust H-infinity controller is proposed that can handle these uncertainties.

A unique VTOL Quad Tiltrotor hybrid UAV, which operates in three flight modes, is mathematically modeled using Newton–Euler equations of motion. The contribution of the model is its ability to combine high-speed level flight, VTOL and transition between these two phases. The transition involves the tilting of the proprotors from 90° to 0° and vice-versa in 15° intervals. A robust H-infinity control strategy is proposed, evaluated and analyzed through simulation to control the flight dynamics for different modes of operation.

The main contribution of this research is the mathematical modeling of three flight modes (vertical takeoff–forward, transition–cruise-back, transition-vertical landing) of operation by controlling the revolutions per minute and tilt angles, which are independent of each other. An autonomous flight control system using a robust H-infinity controller to stabilize the mode of transition is designed for the Quad Tiltrotor UAV in the presence of uncertainties, noise and disturbances using MATLAB/SIMULINK. This paper focused on improving the disturbance rejection properties of the proposed UAV by designing a robust H-infinity controller for position and orientation trajectory regulation in the presence of uncertainty. The simulation results show that the Tiltrotor achieves transition successfully with disturbances, noise and uncertainties being present.

A novel VTOL Quad Tiltrotor UAV mathematical model is developed with a special tilting rotor mechanism, which combines both aircraft and helicopter flight modes with the transition taking place in between phases using robust H-infinity controller for attitude, altitude and trajectory regulation in the presence of uncertainty.

This paper aims to propose a new linear parameter varying (LPV) controller for the robot tracking control problem. Using the identification of the robot dynamics in different work space points about modeling trajectory based on the least square of error algorithm, an LPV model for the robotic arm is extracted.

Parameter set mapping based on parameter component analysis results in a reduced polytopic LPV model that reduces the complexity of the implementation. An approximation of the required torque is computed based on the reduced LPV models. The state-feedback gain of each zone is computed by solving some linear matrix inequalities (LMIs) to sufficiently decrease the time derivative of a Lyapunov function. A novel smoothing method is used for the proposed controller to switch properly in the borders of the zones.

The polytopic set of the resulting gains creates the smooth switching polytopic LPV (SS-LPV) controller which is applied to the trajectory tracking problem of the six-degree-of-freedom PUMA 560 robotic arm. A sufficient condition ensures that the proposed controller stabilizes the polytopic LPV system against the torque estimation error.

Smoothing of the switching LPV controller is performed by defining some tolerances and creating some quasi-zones in the borders of the main zones leading to the compressed main zones. The proposed torque estimation is not a model-based technique; so the model variation and other disturbances cannot destroy the performance of the suggested controller. The proposed control scheme does not have any considerable computational load, because the control gains are obtained offline by solving some LMIs, and the torque computation is done online by a simple polytopic-based equation.

In this paper, a new SS-LPV controller is addressed for the trajectory tracking problem of robotic arms. Robot workspace is zoned into some main zones in such a way that the number of models in each zone is almost equal. Data obtained from the modeling trajectory is used to design the state-feedback control gain.