On Chaotic and Hyperchaotic Complex Nonlinear Dynamical Systems

NASA Astrophysics Data System (ADS)

Mahmoud, Gamal M.

Dynamical systems described by real and complex variables are currently one of the most popular areas of scientific research. These systems play an important role in several fields of physics, engineering, and computer sciences, for example, laser systems, control (or chaos suppression), secure communications, and information science. Dynamical basic properties, chaos (hyperchaos) synchronization, chaos control, and generating hyperchaotic behavior of these systems are briefly summarized. The main advantage of introducing complex variables is the reduction of phase space dimensions by a half. They are also used to describe and simulate the physics of detuned laser and thermal convection of liquid flows, where the electric field and the atomic polarization amplitudes are both complex. Clearly, if the variables of the system are complex the equations involve twice as many variables and control parameters, thus making it that much harder for a hostile agent to intercept and decipher the coded message. Chaotic and hyperchaotic complex systems are stated as examples. Finally there are many open problems in the study of chaotic and hyperchaotic complex nonlinear dynamical systems, which need further investigations. Some of these open problems are given.

Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

ERIC Educational Resources Information Center

Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

2013-01-01

This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

Flight control with adaptive critic neural network

NASA Astrophysics Data System (ADS)

Han, Dongchen

2001-10-01

In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

Precedent approach to the formation of programs for cyclic objects control

NASA Astrophysics Data System (ADS)

Kulakov, S. M.; Trofimov, V. B.; Dobrynin, A. S.; Taraborina, E. N.

2018-05-01

The idea and procedure for formalizing the precedent method of formation of complex control solutions (complex control programs) is discussed with respect to technological or organizational objects, the operation of which is organized cyclically. A typical functional structure of the system of precedent control by complex technological unit is developed, including a subsystem of retrospective optimization of actually implemented control programs. As an example, the problem of constructing replaceable planograms for the operation of the link of a heading-and-winning machine on the basis of precedents is considered.

Symmetry, Contingency, Complexity: Accommodating Uncertainty in Public Relations Theory.

ERIC Educational Resources Information Center

Murphy, Priscilla

2000-01-01

Explores the potential of complexity theory as a unifying theory in public relations, where scholars have recently raised problems involving flux, uncertainty, adaptiveness, and loss of control. Describes specific complexity-based methodologies and their potential for public relations studies. Offers an account of complexity theory, its…

Positive deviance: an elegant solution to a complex problem.

PubMed

Lindberg, Curt; Clancy, Thomas R

2010-04-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 13th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. This article provides one example of how concepts taken from complex systems theory can be applied to real-world problems facing nurses today.

Planning Following Stroke: A Relational Complexity Approach Using the Tower of London

PubMed Central

Andrews, Glenda; Halford, Graeme S.; Chappell, Mark; Maujean, Annick; Shum, David H. K.

2014-01-01

Planning on the 4-disk version of the Tower of London (TOL4) was examined in stroke patients and unimpaired controls. Overall TOL4 solution scores indicated impaired planning in the frontal stroke but not non-frontal stroke patients. Consistent with the claim that processing the relations between current states, intermediate states, and goal states is a key process in planning, the domain-general relational complexity metric was a good indicator of the experienced difficulty of TOL4 problems. The relational complexity metric shared variance with task-specific metrics of moves to solution and search depth. Frontal stroke patients showed impaired planning compared to controls on problems at all three complexity levels, but at only two of the three levels of moves to solution, search depth and goal ambiguity. Non-frontal stroke patients showed impaired planning only on the most difficult quaternary-relational and high search depth problems. An independent measure of relational processing (viz., Latin square task) predicted TOL4 solution scores after controlling for stroke status and location, and executive processing (Trail Making Test). The findings suggest that planning involves a domain-general capacity for relational processing that depends on the frontal brain regions. PMID:25566042

Arithmetic Word-Problem-Solving in Huntington's Disease

ERIC Educational Resources Information Center

Allain, P.; Verny, C.; Aubin, G.; Pinon, K.; Bonneau, D.; Dubas, F.; Gall, D.L.

2005-01-01

The purpose of this study was to examine executive functioning in patients with Huntington's disease using an arithmetic word-problem-solving task including eight solvable problems of increasing complexity and four aberrant problems. Ten patients with Huntington's disease and 12 normal control subjects matched by age and education were tested.…

Min-Max Spaces and Complexity Reduction in Min-Max Expansions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaubert, Stephane, E-mail: Stephane.Gaubert@inria.fr; McEneaney, William M., E-mail: wmceneaney@ucsd.edu

2012-06-15

Idempotent methods have been found to be extremely helpful in the numerical solution of certain classes of nonlinear control problems. In those methods, one uses the fact that the value function lies in the space of semiconvex functions (in the case of maximizing controllers), and approximates this value using a truncated max-plus basis expansion. In some classes, the value function is actually convex, and then one specifically approximates with suprema (i.e., max-plus sums) of affine functions. Note that the space of convex functions is a max-plus linear space, or moduloid. In extending those concepts to game problems, one finds amore » different function space, and different algebra, to be appropriate. Here we consider functions which may be represented using infima (i.e., min-max sums) of max-plus affine functions. It is natural to refer to the class of functions so represented as the min-max linear space (or moduloid) of max-plus hypo-convex functions. We examine this space, the associated notion of duality and min-max basis expansions. In using these methods for solution of control problems, and now games, a critical step is complexity-reduction. In particular, one needs to find reduced-complexity expansions which approximate the function as well as possible. We obtain a solution to this complexity-reduction problem in the case of min-max expansions.« less

Geometry of Quantum Computation with Qudits

PubMed Central

Luo, Ming-Xing; Chen, Xiu-Bo; Yang, Yi-Xian; Wang, Xiaojun

2014-01-01

The circuit complexity of quantum qubit system evolution as a primitive problem in quantum computation has been discussed widely. We investigate this problem in terms of qudit system. Using the Riemannian geometry the optimal quantum circuits are equivalent to the geodetic evolutions in specially curved parametrization of SU(dn). And the quantum circuit complexity is explicitly dependent of controllable approximation error bound. PMID:24509710

Command and Control in a Complex World

DTIC Science & Technology

2012-05-22

definition of command and control does not adequately address changes introduced through technology trends, our understanding of the global operating...processes. The current joint definition of command and control does not adequately address changes introduced through technology trends, our...the problem is actually solved.  There are no  definitive ,  objective solutions to wicked problems.  For a complete  definition  of wicked problems, see

Recent experience in simultaneous control-structure optimization

NASA Technical Reports Server (NTRS)

Salama, M.; Ramaker, R.; Milman, M.

1989-01-01

To show the feasibility of simultaneous optimization as design procedure, low order problems were used in conjunction with simple control formulations. The numerical results indicate that simultaneous optimization is not only feasible, but also advantageous. Such advantages come at the expense of introducing complexities beyond those encountered in structure optimization alone, or control optimization alone. Examples include: larger design parameter space, optimization may combine continuous and combinatoric variables, and the combined objective function may be nonconvex. Future extensions to include large order problems, more complex objective functions and constraints, and more sophisticated control formulations will require further research to ensure that the additional complexities do not outweigh the advantages of simultaneous optimization. Some areas requiring more efficient tools than currently available include: multiobjective criteria and nonconvex optimization. Efficient techniques to deal with optimization over combinatoric and continuous variables, and with truncation issues for structure and control parameters of both the model space as well as the design space need to be developed.

Adaptive fixed-time control for cluster synchronisation of coupled complex networks with uncertain disturbances

NASA Astrophysics Data System (ADS)

Jiang, Shengqin; Lu, Xiaobo; Cai, Guoliang; Cai, Shuiming

2017-12-01

This paper focuses on the cluster synchronisation problem of coupled complex networks with uncertain disturbances under an adaptive fixed-time control strategy. To begin with, complex dynamical networks with community structure which are subject to uncertain disturbances are taken into account. Then, a novel adaptive control strategy combined with fixed-time techniques is proposed to guarantee the nodes in the communities to desired states in a settling time. In addition, the stability of complex error systems is theoretically proved based on Lyapunov stability theorem. At last, two examples are presented to verify the effectiveness of the proposed adaptive fixed-time control.

Master-slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control.

PubMed

Li, Xiaofan; Fang, Jian-An; Li, Huiyuan

2017-09-01

This paper investigates master-slave exponential synchronization for a class of complex-valued memristor-based neural networks with time-varying delays via discontinuous impulsive control. Firstly, the master and slave complex-valued memristor-based neural networks with time-varying delays are translated to two real-valued memristor-based neural networks. Secondly, an impulsive control law is constructed and utilized to guarantee master-slave exponential synchronization of the neural networks. Thirdly, the master-slave synchronization problems are transformed into the stability problems of the master-slave error system. By employing linear matrix inequality (LMI) technique and constructing an appropriate Lyapunov-Krasovskii functional, some sufficient synchronization criteria are derived. Finally, a numerical simulation is provided to illustrate the effectiveness of the obtained theoretical results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Numerical Leak Detection in a Pipeline Network of Complex Structure with Unsteady Flow

NASA Astrophysics Data System (ADS)

Aida-zade, K. R.; Ashrafova, E. R.

2017-12-01

An inverse problem for a pipeline network of complex loopback structure is solved numerically. The problem is to determine the locations and amounts of leaks from unsteady flow characteristics measured at some pipeline points. The features of the problem include impulse functions involved in a system of hyperbolic differential equations, the absence of classical initial conditions, and boundary conditions specified as nonseparated relations between the states at the endpoints of adjacent pipeline segments. The problem is reduced to a parametric optimal control problem without initial conditions, but with nonseparated boundary conditions. The latter problem is solved by applying first-order optimization methods. Results of numerical experiments are presented.

Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

NASA Astrophysics Data System (ADS)

Williams, Rube B.

2004-02-01

Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving

PubMed Central

Maisto, Domenico; Donnarumma, Francesco; Pezzulo, Giovanni

2015-01-01

It has long been recognized that humans (and possibly other animals) usually break problems down into smaller and more manageable problems using subgoals. Despite a general consensus that subgoaling helps problem solving, it is still unclear what the mechanisms guiding online subgoal selection are during the solution of novel problems for which predefined solutions are not available. Under which conditions does subgoaling lead to optimal behaviour? When is subgoaling better than solving a problem from start to finish? Which is the best number and sequence of subgoals to solve a given problem? How are these subgoals selected during online inference? Here, we present a computational account of subgoaling in problem solving. Following Occam's razor, we propose that good subgoals are those that permit planning solutions and controlling behaviour using less information resources, thus yielding parsimony in inference and control. We implement this principle using approximate probabilistic inference: subgoals are selected using a sampling method that considers the descriptive complexity of the resulting sub-problems. We validate the proposed method using a standard reinforcement learning benchmark (four-rooms scenario) and show that the proposed method requires less inferential steps and permits selecting more compact control programs compared to an equivalent procedure without subgoaling. Furthermore, we show that the proposed method offers a mechanistic explanation of the neuronal dynamics found in the prefrontal cortex of monkeys that solve planning problems. Our computational framework provides a novel integrative perspective on subgoaling and its adaptive advantages for planning, control and learning, such as for example lowering cognitive effort and working memory load. PMID:25652466

A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.

PubMed

Hajri, S; Liouane, N; Hammadi, S; Borne, P

2000-01-01

Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.

Class II malocclusion with complex problems treated with a novel combination of lingual orthodontic appliances and lingual arches.

PubMed

Yanagita, Takeshi; Nakamura, Masahiro; Kawanabe, Noriaki; Yamashiro, Takashi

2014-07-01

This case report describes a novel method of combining lingual appliances and lingual arches to control horizontal problems. The patient, who was 25 years of age at her first visit to our hospital with a chief complaint of crooked anterior teeth, was diagnosed with skeletal Class II and Angle Class II malocclusion with anterior deep bite, lateral open bite, premolar crossbite, and severe crowding in both arches. She was treated with premolar extractions and temporary anchorage devices. Conventionally, it is ideal to use labial brackets simultaneously with appliances, such as a lingual arch, a quad-helix, or a rapid expansion appliance, in patients with complex problems requiring horizontal, anteroposterior, and vertical control; however, this patient strongly requested orthodontic treatment with lingual appliances. A limitation of lingual appliances is that they cannot be used with other conventional appliances. In this report, we present the successful orthodontic treatment of a complex problem using modified lingual appliances that enabled combined use of a conventional lingual arch. Copyright © 2014 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Studies on hepatic lipidosis and coinciding health and fertility problems of high-producing dairy cows using the "Utrecht fatty liver model of dairy cows". A review.

PubMed

Geelen, M J H; Wensing, T

2006-09-01

Fatty liver or hepatic lipidosis is a major metabolic disorder of high-producing dairy cows that occurs rather frequently in early lactation and is associated with decreased health, production and fertility. A background section of the review explores reasons why high-producing dairy cows are prone to develop fatty liver post partum. Hepatic lipidosis and coinciding health and fertility problems seriously endanger profitability and longevity of the dairy cow. Results from a great number of earlier epidemiological and clinical studies made it clear that a different approach was needed for elucidation of pathogenesis and etiology of this complex of health problems. There was a need for an adequate animal model in which hepatic lipidosis and production, health and fertility problems could be provoked under controlled conditions. It was hypothesized that overconditioning ante partum and feed restriction post partum might induce lipolysis in adipose tissue and triacylglycerol accumulation in the liver following calving. This consideration formed the basis for the experiments, which resulted in the "Utrecht fatty liver model of dairy cows". In this model, post partum triacylglycerol-lipidosis as well as the whole complex of health and fertility problems are induced under well-controlled conditions. The experimental protocol based on this hypothesis produced in all cases (10 feeding trials with over 150 dairy cattle) the intended result, i.e. all experimental cows developed post partum higher hepatic triacylglycerol concentrations than did control cows. The model was evaluated in biochemical, clinical pathology, immunological, clinical and fertility terms. It turned out that in this model, post partum triacylglycerol-lipidosis as well as the whole complex of health and fertility problems were induced under well-controlled conditions.

A Study on the Control of Third Generation Spacecraft

NASA Technical Reports Server (NTRS)

Davison, E. J.; Gesing, W.

1985-01-01

An overview of some studies which have recently been carried out on the control of third generation spcecraft, as modelled by the MSAT space vehicle configuration, is made. This spacecraft is highly nonsymmetrical and has appendages which cannot in general be assumed to be rigid. In particular, it is desired to design a controller for MSAT which stabilizes the system and satisfies certain attitude control, shape control, and possibly stationkeeping requirements; in addition, it is desired that the resultant controller should be robust and avoid any undesirable spill over effects. In addition, the controller obtained should have minimum complexity. The method of solution adopted to solve this class of problems is to formulate the problem as a robust servomechanism problem, and thence to obtain existence conditions and a controller characterization to solve the problem. The final controller obtained for MSAT has a distributed control configuration and appears to be quite satisfactory.

Approximation algorithms for planning and control

NASA Technical Reports Server (NTRS)

Boddy, Mark; Dean, Thomas

1989-01-01

A control system operating in a complex environment will encounter a variety of different situations, with varying amounts of time available to respond to critical events. Ideally, such a control system will do the best possible with the time available. In other words, its responses should approximate those that would result from having unlimited time for computation, where the degree of the approximation depends on the amount of time it actually has. There exist approximation algorithms for a wide variety of problems. Unfortunately, the solution to any reasonably complex control problem will require solving several computationally intensive problems. Algorithms for successive approximation are a subclass of the class of anytime algorithms, algorithms that return answers for any amount of computation time, where the answers improve as more time is allotted. An architecture is described for allocating computation time to a set of anytime algorithms, based on expectations regarding the value of the answers they return. The architecture described is quite general, producing optimal schedules for a set of algorithms under widely varying conditions.

Computational complexities and storage requirements of some Riccati equation solvers

NASA Technical Reports Server (NTRS)

Utku, Senol; Garba, John A.; Ramesh, A. V.

1989-01-01

The linear optimal control problem of an nth-order time-invariant dynamic system with a quadratic performance functional is usually solved by the Hamilton-Jacobi approach. This leads to the solution of the differential matrix Riccati equation with a terminal condition. The bulk of the computation for the optimal control problem is related to the solution of this equation. There are various algorithms in the literature for solving the matrix Riccati equation. However, computational complexities and storage requirements as a function of numbers of state variables, control variables, and sensors are not available for all these algorithms. In this work, the computational complexities and storage requirements for some of these algorithms are given. These expressions show the immensity of the computational requirements of the algorithms in solving the Riccati equation for large-order systems such as the control of highly flexible space structures. The expressions are also needed to compute the speedup and efficiency of any implementation of these algorithms on concurrent machines.

Dynamic programming methods for concurrent design and dynamic allocation of vehicles embedded in a system-of-systems

NASA Astrophysics Data System (ADS)

Nusawardhana

2007-12-01

Recent developments indicate a changing perspective on how systems or vehicles should be designed. Such transition comes from the way decision makers in defense related agencies address complex problems. Complex problems are now often posed in terms of the capabilities desired, rather than in terms of requirements for a single systems. As a result, the way to provide a set of capabilities is through a collection of several individual, independent systems. This collection of individual independent systems is often referred to as a "System of Systems'' (SoS). Because of the independent nature of the constituent systems in an SoS, approaches to design an SoS, and more specifically, approaches to design a new system as a member of an SoS, will likely be different than the traditional design approaches for complex, monolithic (meaning the constituent parts have no ability for independent operation) systems. Because a system of system evolves over time, this simultaneous system design and resource allocation problem should be investigated in a dynamic context. Such dynamic optimization problems are similar to conventional control problems. However, this research considers problems which not only seek optimizing policies but also seek the proper system or vehicle to operate under these policies. This thesis presents a framework and a set of analytical tools to solve a class of SoS problems that involves the simultaneous design of a new system and allocation of the new system along with existing systems. Such a class of problems belongs to the problems of concurrent design and control of a new systems with solutions consisting of both optimal system design and optimal control strategy. Rigorous mathematical arguments show that the proposed framework solves the concurrent design and control problems. Many results exist for dynamic optimization problems of linear systems. In contrary, results on optimal nonlinear dynamic optimization problems are rare. The proposed framework is equipped with the set of analytical tools to solve several cases of nonlinear optimal control problems: continuous- and discrete-time nonlinear problems with applications on both optimal regulation and tracking. These tools are useful when mathematical descriptions of dynamic systems are available. In the absence of such a mathematical model, it is often necessary to derive a solution based on computer simulation. For this case, a set of parameterized decision may constitute a solution. This thesis presents a method to adjust these parameters based on the principle of stochastic approximation simultaneous perturbation using continuous measurements. The set of tools developed here mostly employs the methods of exact dynamic programming. However, due to the complexity of SoS problems, this research also develops suboptimal solution approaches, collectively recognized as approximate dynamic programming solutions, for large scale problems. The thesis presents, explores, and solves problems from an airline industry, in which a new aircraft is to be designed and allocated along with an existing fleet of aircraft. Because the life cycle of an aircraft is on the order of 10 to 20 years, this problem is to be addressed dynamically so that the new aircraft design is the best design for the fleet over a given time horizon.

Modular thought in the circuit analysis

NASA Astrophysics Data System (ADS)

Wang, Feng

2018-04-01

Applied to solve the problem of modular thought, provides a whole for simplification's method, the complex problems have become of, and the study of circuit is similar to the above problems: the complex connection between components, make the whole circuit topic solution seems to be more complex, and actually components the connection between the have rules to follow, this article mainly tells the story of study on the application of the circuit modular thought. First of all, this paper introduces the definition of two-terminal network and the concept of two-terminal network equivalent conversion, then summarizes the common source resistance hybrid network modular approach, containing controlled source network modular processing method, lists the common module, typical examples analysis.

Numerical Modeling of Pulsed Electrical Discharges for High-Speed Flow Control

DTIC Science & Technology

2012-02-01

dimensions , and later on more complex problems. Subsequent work compared different physical models for pulsed discharges: one-moment (drift-diffusion with...two dimensions , and later on more complex problems. Subsequent work compared different physical models for pulsed discharges: one-moment (drift...The state of a particle can be specified by its position and velocity. In principal, the motion of a large group of particles can be predicted from

Controlling uncertainty: a review of human behavior in complex dynamic environments.

PubMed

Osman, Magda

2010-01-01

Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research (economics, engineering, ergonomics, human-computer interaction, management, psychology), but they remain largely disconnected from each other. The objective of this article is to review theoretical developments and empirical work on CDC tasks, and to introduce a novel framework (monitoring and control framework) as a tool for integrating theory and findings. The main thesis of the monitoring and control framework is that CDC tasks are characteristically uncertain environments, and subjective judgments of uncertainty guide the way in which monitoring and control behaviors attempt to reduce it. The article concludes by discussing new insights into continuing debates and future directions for research on CDC tasks.

Closed-Loop Control of Complex Networks: A Trade-Off between Time and Energy

NASA Astrophysics Data System (ADS)

Sun, Yong-Zheng; Leng, Si-Yang; Lai, Ying-Cheng; Grebogi, Celso; Lin, Wei

2017-11-01

Controlling complex nonlinear networks is largely an unsolved problem at the present. Existing works focus either on open-loop control strategies and their energy consumptions or on closed-loop control schemes with an infinite-time duration. We articulate a finite-time, closed-loop controller with an eye toward the physical and mathematical underpinnings of the trade-off between the control time and energy as well as their dependence on the network parameters and structure. The closed-loop controller is tested on a large number of real systems including stem cell differentiation, food webs, random ecosystems, and spiking neuronal networks. Our results represent a step forward in developing a rigorous and general framework to control nonlinear dynamical networks with a complex topology.

Fusing terrain and goals: agent control in urban environments

NASA Astrophysics Data System (ADS)

Kaptan, Varol; Gelenbe, Erol

2006-04-01

The changing face of contemporary military conflicts has forced a major shift of focus in tactical planning and evaluation from the classical Cold War battlefield to an asymmetric guerrilla-type warfare in densely populated urban areas. The new arena of conflict presents unique operational difficulties due to factors like complex mobility restrictions and the necessity to preserve civilian lives and infrastructure. In this paper we present a novel method for autonomous agent control in an urban environment. Our approach is based on fusing terrain information and agent goals for the purpose of transforming the problem of navigation in a complex environment with many obstacles into the easier problem of navigation in a virtual obstacle-free space. The main advantage of our approach is its ability to act as an adapter layer for a number of efficient agent control techniques which normally show poor performance when applied to an environment with many complex obstacles. Because of the very low computational and space complexity at runtime, our method is also particularly well suited for simulation or control of a huge number of agents (military as well as civilian) in a complex urban environment where traditional path-planning may be too expensive or where a just-in-time decision with hard real-time constraints is required.

Learning Search Control Knowledge for Deep Space Network Scheduling

NASA Technical Reports Server (NTRS)

Gratch, Jonathan; Chien, Steve; DeJong, Gerald

1993-01-01

While the general class of most scheduling problems is NP-hard in worst-case complexity, in practice, for specific distributions of problems and constraints, domain-specific solutions have been shown to perform in much better than exponential time.

Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving.

PubMed

Maisto, Domenico; Donnarumma, Francesco; Pezzulo, Giovanni

2015-03-06

It has long been recognized that humans (and possibly other animals) usually break problems down into smaller and more manageable problems using subgoals. Despite a general consensus that subgoaling helps problem solving, it is still unclear what the mechanisms guiding online subgoal selection are during the solution of novel problems for which predefined solutions are not available. Under which conditions does subgoaling lead to optimal behaviour? When is subgoaling better than solving a problem from start to finish? Which is the best number and sequence of subgoals to solve a given problem? How are these subgoals selected during online inference? Here, we present a computational account of subgoaling in problem solving. Following Occam's razor, we propose that good subgoals are those that permit planning solutions and controlling behaviour using less information resources, thus yielding parsimony in inference and control. We implement this principle using approximate probabilistic inference: subgoals are selected using a sampling method that considers the descriptive complexity of the resulting sub-problems. We validate the proposed method using a standard reinforcement learning benchmark (four-rooms scenario) and show that the proposed method requires less inferential steps and permits selecting more compact control programs compared to an equivalent procedure without subgoaling. Furthermore, we show that the proposed method offers a mechanistic explanation of the neuronal dynamics found in the prefrontal cortex of monkeys that solve planning problems. Our computational framework provides a novel integrative perspective on subgoaling and its adaptive advantages for planning, control and learning, such as for example lowering cognitive effort and working memory load. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Amnestic mild cognitive impairment: functional MR imaging study of response in posterior cingulate cortex and adjacent precuneus during problem-solving tasks.

PubMed

Jin, Guangwei; Li, Kuncheng; Hu, Yingying; Qin, Yulin; Wang, Xiangqing; Xiang, Jie; Yang, Yanhui; Lu, Jie; Zhong, Ning

2011-11-01

To compare the blood oxygen level-dependent (BOLD) response, measured with functional magnetic resonance (MR) imaging, in the posterior cingulate cortex (PCC) and adjacent precuneus regions between healthy control subjects and patients with amnestic mild cognitive impairment (MCI) during problem-solving tasks. This study was approved by the institutional review board. Each subject provided written informed consent. Thirteen patients with amnestic MCI and 13 age- and sex-matched healthy control subjects participated in the study. The functional magnetic resonance (MR) imaging tasks were simplified 4 × 4-grid number placement puzzles that were divided into a simple task (using the row rule or the column rule to solve the puzzle) and a complex task (using both the row and column rules to solve the puzzle). Behavioral results and functional imaging results between the healthy control group and the amnestic MCI group were analyzed. The accuracy for the complex task in the healthy control group was significantly higher than that in the amnestic MCI group (P < .05). The healthy control group exhibited a deactivated BOLD signal intensity (SI) change in the bilateral PCC and adjacent precuneus regions during the complex task, whereas the amnestic MCI group showed activation. The positive linear correlations between the BOLD SI change in bilateral PCC and adjacent precuneus regions and in bilateral hippocampi in the amnestic MCI group were significant (P < .001), while in the healthy control group, they were not (P ≥ .23). These findings suggest that an altered BOLD response in amnestic MCI patients during complex tasks might be related to a decline in problem-solving ability and to memory impairment and, thus, may indicate a compensatory response to memory impairment. RSNA, 2011

Novel Image Quality Control Systems(Add-On). Innovative Computational Methods for Inverse Problems in Optical and SAR Imaging

DTIC Science & Technology

2007-02-28

Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex Medium Response, International Journal of Imaging Systems and...1767-1782, 2006. 31. Z. Mu, R. Plemmons, and P. Santago. Iterative Ultrasonic Signal and Image Deconvolution for Estimation of the Complex...rigorous mathematical and computational research on inverse problems in optical imaging of direct interest to the Army and also the intelligence agencies

Electromagnetic interference-aware transmission scheduling and power control for dynamic wireless access in hospital environments.

PubMed

Phunchongharn, Phond; Hossain, Ekram; Camorlinga, Sergio

2011-11-01

We study the multiple access problem for e-Health applications (referred to as secondary users) coexisting with medical devices (referred to as primary or protected users) in a hospital environment. In particular, we focus on transmission scheduling and power control of secondary users in multiple spatial reuse time-division multiple access (STDMA) networks. The objective is to maximize the spectrum utilization of secondary users and minimize their power consumption subject to the electromagnetic interference (EMI) constraints for active and passive medical devices and minimum throughput guarantee for secondary users. The multiple access problem is formulated as a dual objective optimization problem which is shown to be NP-complete. We propose a joint scheduling and power control algorithm based on a greedy approach to solve the problem with much lower computational complexity. To this end, an enhanced greedy algorithm is proposed to improve the performance of the greedy algorithm by finding the optimal sequence of secondary users for scheduling. Using extensive simulations, the tradeoff in performance in terms of spectrum utilization, energy consumption, and computational complexity is evaluated for both the algorithms.

Research on the man in the loop control system of the robot arm based on gesture control

NASA Astrophysics Data System (ADS)

Xiao, Lifeng; Peng, Jinbao

2017-03-01

The Man in the loop control system of the robot arm based on gesture control research complex real-world environment, which requires the operator to continuously control and adjust the remote manipulator, as the background, completes the specific mission human in the loop entire system as the research object. This paper puts forward a kind of robot arm control system of Man in the loop based on gesture control, by robot arm control system based on gesture control and Virtual reality scene feedback to enhance immersion and integration of operator, to make operator really become a part of the whole control loop. This paper expounds how to construct a man in the loop control system of the robot arm based on gesture control. The system is a complex system of human computer cooperative control, but also people in the loop control problem areas. The new system solves the problems that the traditional method has no immersion feeling and the operation lever is unnatural, the adjustment time is long, and the data glove mode wears uncomfortable and the price is expensive.

Jacobi bundles and the BFV-complex

NASA Astrophysics Data System (ADS)

Lê, Hông Vân; Tortorella, Alfonso G.; Vitagliano, Luca

2017-11-01

We extend the construction of the BFV-complex of a coisotropic submanifold from the Poisson setting to the Jacobi setting. In particular, our construction applies in the contact and l.c.s. settings. The BFV-complex of a coisotropic submanifold S controls the coisotropic deformation problem of S under both Hamiltonian and Jacobi equivalence.

Fuzzy Adaptive Output Feedback Control of Uncertain Nonlinear Systems With Prescribed Performance.

PubMed

Zhang, Jin-Xi; Yang, Guang-Hong

2018-05-01

This paper investigates the tracking control problem for a family of strict-feedback systems in the presence of unknown nonlinearities and immeasurable system states. A low-complexity adaptive fuzzy output feedback control scheme is proposed, based on a backstepping method. In the control design, a fuzzy adaptive state observer is first employed to estimate the unmeasured states. Then, a novel error transformation approach together with a new modification mechanism is introduced to guarantee the finite-time convergence of the output error to a predefined region and ensure the closed-loop stability. Compared with the existing methods, the main advantages of our approach are that: 1) without using extra command filters or auxiliary dynamic surface control techniques, the problem of explosion of complexity can still be addressed and 2) the design procedures are independent of the initial conditions. Finally, two practical examples are performed to further illustrate the above theoretic findings.

Connecting Core Percolation and Controllability of Complex Networks

PubMed Central

Jia, Tao; Pósfai, Márton

2014-01-01

Core percolation is a fundamental structural transition in complex networks related to a wide range of important problems. Recent advances have provided us an analytical framework of core percolation in uncorrelated random networks with arbitrary degree distributions. Here we apply the tools in analysis of network controllability. We confirm analytically that the emergence of the bifurcation in control coincides with the formation of the core and the structure of the core determines the control mode of the network. We also derive the analytical expression related to the controllability robustness by extending the deduction in core percolation. These findings help us better understand the interesting interplay between the structural and dynamical properties of complex networks. PMID:24946797

Mode Transitions in Glass Cockpit Aircraft: Results of a Field Study

NASA Technical Reports Server (NTRS)

Degani, Asaf; Kirlik, Alex; Shafto, Michael (Technical Monitor)

1995-01-01

One consequence of increased levels of automation in complex control systems is the presence of modes. A mode is a particular configuration of a control system that defines how human command inputs are interpreted. In complex systems, modes also often determine a specific allocation of control authority between the human and automated systems. Even in simple static devices (e.g., electronic watches, word processors), the presence of modes has been found to cause problems in either-the acquisition or production of skilled performance. Many of these problems arise due to the fact that the selection of a mode causes device behavior to be mediated by hidden internal state information. For these simple systems, many of these interaction problems can be solved by the design of appropriate feedback to communicate internal state information to the human operator. In complex dynamic systems, however, the design issues associated with modes seem to trancend the problem of merely communicating internal state information via displayed feedback. In complex supervisory control systems (e.g., aircraft, spacecraft, military command and control), a key function of modes is the selection of a particular configuration of control authority between the human operator and automated control systems. One mode may result in full manual control, another may result in a mix of manual and automatic control, while a third may result in full automatic control over the entire system. The human operator selects an appropriate mode as a function of current goals, operating conditions, and operating procedures. Thus, the operator is put in a position of essentially trying to control two coupled dynamic systems: the target system itself, and also a highly complex suite of automation controlling the target system. From a historical perspective, it should probably not come as a surprise that very little information is available to guide the design of mode-oriented control systems. The topic of function allocation (i.e., the proper division of control authority among human and computer) has a long history in human-machine systems research. Although this research has produced some relevant guidelines, a design approach capable of defining appropriate allocations of control function between the human and automation is not yet available. As a result, the function allocation decision itself has been allocated to the operator, to be performed in real-time, in the operation of mode-oriented control systems. A variety of documented aircraft accidents and incidents suggest that the real-time selection and monitoring of control modes is a weak link in the effective operation of complex supervisory control systems. Research in human-machine systems and human-computer interaction has barely scraped the surface of the problem of understanding how operators manage this task.The purpose of this paper is to present the results of a field study which examined how operators manage mode selection in a complex supervisory control system. Data on mode engagements using the Boeing B757/767 auto-flight system were collected during approach and descent into four major airports in the East Coast of the United States. Protocols documenting mode selection, automatic mode changes, pilot actions, quantitative records of flight-path variables, and verbal reports during and after mode engagements were collected by an observer from the jumpseat. Observations were conducted on two typical trips between three airports. Each trip was be replicated 11 times, which yielded a total of 22 trips and 66 legs on which data were collected. All data collected concerned the same flight numbers, and therefore, the same time of day, same type of aircraft, and identical operational environments (e.g., ATC facilities, weather patterns, traffic flow etc.)

A problem of optimal control and observation for distributed homogeneous multi-agent system

NASA Astrophysics Data System (ADS)

Kruglikov, Sergey V.

2017-12-01

The paper considers the implementation of a algorithm for controlling a distributed complex of several mobile multi-robots. The concept of a unified information space of the controlling system is applied. The presented information and mathematical models of participants and obstacles, as real agents, and goals and scenarios, as virtual agents, create the base forming the algorithmic and software background for computer decision support system. The controlling scheme assumes the indirect management of the robotic team on the basis of optimal control and observation problem predicting intellectual behavior in a dynamic, hostile environment. A basic content problem is a compound cargo transportation by a group of participants in the case of a distributed control scheme in the terrain with multiple obstacles.

DUII control system performance measures for Oregon counties 1991-2001

DOT National Transportation Integrated Search

2002-06-01

Driving Under the Influence of Intoxicants (DUII) is a complex social problem that has origins in both internal and external system factors. Due to its complexity, Oregon communities and involved agencies must concentrate on addressing the negative r...

Cognitive process modelling of controllers in en route air traffic control.

PubMed

Inoue, Satoru; Furuta, Kazuo; Nakata, Keiichi; Kanno, Taro; Aoyama, Hisae; Brown, Mark

2012-01-01

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes. This research focuses on an experimental study to gain a better understanding of controllers' cognitive processes in air traffic control. We conducted ethnographic observations and then analysed the data to develop a model of controllers' cognitive process. This analysis revealed that strategic routines are applicable to decision making.

Ergatic dynamic control systems

NASA Technical Reports Server (NTRS)

Pavlov, V. V. (Editor); Drozdova, T. I. (Editor); Antomonov, Y. G. (Editor); Golego, V. N. (Editor); Ivakhnenko, A. G. (Editor); Meleshev, A. M. (Editor)

1977-01-01

Synthesis and analysis of systems containing a man in their control circuits are considered. The concepts of ergonomics and ergatic systems are defined, and tasks and problems of ergonomics are outlined. The synthesis of the structure of an astronautic ergatic organism is presented, as well as the synthesis of nonstationary ergatic systems. Problems of selecting the criteria for complex systems are considered, and the results are presented from a study of ergatic control systems with any degree of human participation.

Chaotification of complex networks with impulsive control.

PubMed

Guan, Zhi-Hong; Liu, Feng; Li, Juan; Wang, Yan-Wu

2012-06-01

This paper investigates the chaotification problem of complex dynamical networks (CDN) with impulsive control. Both the discrete and continuous cases are studied. The method is presented to drive all states of every node in CDN to chaos. The proposed impulsive control strategy is effective for both the originally stable and unstable CDN. The upper bound of the impulse intervals for originally stable networks is derived. Finally, the effectiveness of the theoretical results is verified by numerical examples.

Active Control of Generalized Complex Modal Structures in a Stochastic Environment

DTIC Science & Technology

1992-05-15

began with the design of a baseline controller. The system of interest was a MIMO, heavily damped structure with complex modes, and the control objective...feed-through term in our system that was due to the use of accelerometers as sensors. This provided an acceptable baseline solution to our I problem...to which we could compare our ideas for improvement. One area in which the baseline design was deficient was robust stability to unstructured

Strategic control in decision-making under uncertainty.

PubMed

Venkatraman, Vinod; Huettel, Scott A

2012-04-01

Complex economic decisions - whether investing money for retirement or purchasing some new electronic gadget - often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, evaluate outcomes against a variety of contexts, and flexibly match behavior to changes in the environment. In recent years, substantial research has implicated the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision-making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision-making. This region contains a functional topography such that the posterior dmPFC supports response-related control, whereas the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue for both generalized contributions of the dmPFC to cognitive control, and specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are likely to be critical for decision-making in other domains, including interpersonal interactions in social settings. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Strategic Control in Decision Making under Uncertainty

PubMed Central

Venkatraman, Vinod; Huettel, Scott

2012-01-01

Complex economic decisions – whether investing money for retirement or purchasing some new electronic gadget – often involve uncertainty about the likely consequences of our choices. Critical for resolving that uncertainty are strategic meta-decision processes, which allow people to simplify complex decision problems, to evaluate outcomes against a variety of contexts, and to flexibly match behavior to changes in the environment. In recent years, substantial research implicates the dorsomedial prefrontal cortex (dmPFC) in the flexible control of behavior. However, nearly all such evidence comes from paradigms involving executive function or response selection, not complex decision making. Here, we review evidence that demonstrates that the dmPFC contributes to strategic control in complex decision making. This region contains a functional topography such that the posterior dmPFC supports response-related control while the anterior dmPFC supports strategic control. Activation in the anterior dmPFC signals changes in how a decision problem is represented, which in turn can shape computational processes elsewhere in the brain. Based on these findings, we argue both for generalized contributions of the dmPFC to cognitive control, and for specific computational roles for its subregions depending upon the task demands and context. We also contend that these strategic considerations are also likely to be critical for decision making in other domains, including interpersonal interactions in social settings. PMID:22487037

Fortuitous phenomena: on complexity, pragmatic randomised controlled trials, and knowledge for evidence-based practice.

PubMed

Thompson, Carl

2004-01-01

Many of the interventions that nurses develop and implement are in themselves complex and have to operate in situations of irreducible complexity and uncertainty. This article argues that the primary means of generating knowledge for the evidence-based deployment of complex interventions should be the pragmatic randomised controlled trial. Randomised controlled trials represent the only research design to adequately deal with that which we know and (far more importantly) that which we do not. Using the example of practice development as an exemplar for complexity, and drawing on the objections often voiced as a response to calls to make use of randomised controlled trials in nursing and nursing research, the article presents a developmental framework and some methodological solutions to problems often encountered. Randomised controlled trials, whilst undoubtedly methodologically and strategically challenging, offer the most robust basis for developing primary research knowledge on the effects of complex interventions in nursing and their active components.

Parametric optimal control of uncertain systems under an optimistic value criterion

NASA Astrophysics Data System (ADS)

Li, Bo; Zhu, Yuanguo

2018-01-01

It is well known that the optimal control of a linear quadratic model is characterized by the solution of a Riccati differential equation. In many cases, the corresponding Riccati differential equation cannot be solved exactly such that the optimal feedback control may be a complex time-oriented function. In this article, a parametric optimal control problem of an uncertain linear quadratic model under an optimistic value criterion is considered for simplifying the expression of optimal control. Based on the equation of optimality for the uncertain optimal control problem, an approximation method is presented to solve it. As an application, a two-spool turbofan engine optimal control problem is given to show the utility of the proposed model and the efficiency of the presented approximation method.

Effective algorithm for solving complex problems of production control and of material flows control of industrial enterprise

NASA Astrophysics Data System (ADS)

Mezentsev, Yu A.; Baranova, N. V.

2018-05-01

A universal economical and mathematical model designed for determination of optimal strategies for managing subsystems (components of subsystems) of production and logistics of enterprises is considered. Declared universality allows taking into account on the system level both production components, including limitations on the ways of converting raw materials and components into sold goods, as well as resource and logical restrictions on input and output material flows. The presented model and generated control problems are developed within the framework of the unified approach that allows one to implement logical conditions of any complexity and to define corresponding formal optimization tasks. Conceptual meaning of used criteria and limitations are explained. The belonging of the generated tasks of the mixed programming with the class of NP is shown. An approximate polynomial algorithm for solving the posed optimization tasks for mixed programming of real dimension with high computational complexity is proposed. Results of testing the algorithm on the tasks in a wide range of dimensions are presented.

Minimal complexity control law synthesis

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Haddad, Wassim M.; Nett, Carl N.

1989-01-01

A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.

Human factors in air traffic control: problems at the interfaces.

PubMed

Shouksmith, George

2003-10-01

The triangular ISIS model for describing the operation of human factors in complex sociotechnical organisations or systems is applied in this research to a large international air traffic control system. A large sample of senior Air Traffic Controllers were randomly assigned to small focus discussion groups, whose task was to identify problems occurring at the interfaces of the three major human factor components: individual, system impacts, and social. From these discussions, a number of significant interface problems, which could adversely affect the functioning of the Air Traffic Control System, emerged. The majority of these occurred at the Individual-System Impact and Individual-Social interfaces and involved a perceived need for further interface centered training.

The algorithmic details of polynomials application in the problems of heat and mass transfer control on the hypersonic aircraft permeable surfaces

NASA Astrophysics Data System (ADS)

Bilchenko, G. G.; Bilchenko, N. G.

2018-03-01

The hypersonic aircraft permeable surfaces heat and mass transfer effective control mathematical modeling problems are considered. The analysis of the control (the blowing) constructive and gasdynamical restrictions is carried out for the porous and perforated surfaces. The functions classes allowing realize the controls taking into account the arising types of restrictions are suggested. Estimates of the computational complexity of the W. G. Horner scheme application in the case of using the C. Hermite interpolation polynomial are given.

The Application of Science and Technology to Public Programs.

ERIC Educational Resources Information Center

Feller, Irwin

Conference papers, recommendations, and discussion are compiled, focusing on the complex of problems associated with rapidly expanding urbanization and consequent rural dislocation. Topics exploring the problems included: air and water pollution; program planning and management; solid waste disposal; transportation; housing; crime control; health…

Alternative Architectures for Distributed Cooperative Problem-Solving in the National Airspace System

NASA Technical Reports Server (NTRS)

Smith, Phillip J.; Billings, Charles; McCoy, C. Elaine; Orasanu, Judith

1999-01-01

The air traffic management system in the United States is an example of a distributed problem solving system. It has elements of both cooperative and competitive problem-solving. This system includes complex organizations such as Airline Operations Centers (AOCs), the FAA Air Traffic Control Systems Command Center (ATCSCC), and traffic management units (TMUs) at enroute centers and TRACONs, all of which have a major focus on strategic decision-making. It also includes individuals concerned more with tactical decisions (such as air traffic controllers and pilots). The architecture for this system has evolved over time to rely heavily on the distribution of tasks and control authority in order to keep cognitive complexity manageable for any one individual operator, and to provide redundancy (both human and technological) to serve as a safety net to catch the slips or mistakes that any one person or entity might make. Currently, major changes are being considered for this architecture, especially with respect to the locus of control, in an effort to improve efficiency and safety. This paper uses a series of case studies to help evaluate some of these changes from the perspective of system complexity, and to point out possible alternative approaches that might be taken to improve system performance. The paper illustrates the need to maintain a clear understanding of what is required to assure a high level of performance when alternative system architectures and decompositions are developed.

Initial flight qualification and operational maintenance of X-29A flight software

NASA Technical Reports Server (NTRS)

Earls, Michael R.; Sitz, Joel R.

1989-01-01

A discussion is presented of some significant aspects of the initial flight qualification and operational maintenance of the flight control system softward for the X-29A technology demonstrator. Flight qualification and maintenance of complex, embedded flight control system software poses unique problems. The X-29A technology demonstrator aircraft has a digital flight control system which incorporates functions generally considered too complex for analog systems. Organizational responsibilities, software assurance issues, tools, and facilities are discussed.

Control of Multilayer Networks

PubMed Central

Menichetti, Giulia; Dall’Asta, Luca; Bianconi, Ginestra

2016-01-01

The controllability of a network is a theoretical problem of relevance in a variety of contexts ranging from financial markets to the brain. Until now, network controllability has been characterized only on isolated networks, while the vast majority of complex systems are formed by multilayer networks. Here we build a theoretical framework for the linear controllability of multilayer networks by mapping the problem into a combinatorial matching problem. We found that correlating the external signals in the different layers can significantly reduce the multiplex network robustness to node removal, as it can be seen in conjunction with a hybrid phase transition occurring in interacting Poisson networks. Moreover we observe that multilayer networks can stabilize the fully controllable multiplex network configuration that can be stable also when the full controllability of the single network is not stable. PMID:26869210

Optimization of controllability and robustness of complex networks by edge directionality

NASA Astrophysics Data System (ADS)

Liang, Man; Jin, Suoqin; Wang, Dingjie; Zou, Xiufen

2016-09-01

Recently, controllability of complex networks has attracted enormous attention in various fields of science and engineering. How to optimize structural controllability has also become a significant issue. Previous studies have shown that an appropriate directional assignment can improve structural controllability; however, the evolution of the structural controllability of complex networks under attacks and cascading has always been ignored. To address this problem, this study proposes a new edge orientation method (NEOM) based on residual degree that changes the link direction while conserving topology and directionality. By comparing the results with those of previous methods in two random graph models and several realistic networks, our proposed approach is demonstrated to be an effective and competitive method for improving the structural controllability of complex networks. Moreover, numerical simulations show that our method is near-optimal in optimizing structural controllability. Strikingly, compared to the original network, our method maintains the structural controllability of the network under attacks and cascading, indicating that the NEOM can also enhance the robustness of controllability of networks. These results alter the view of the nature of controllability in complex networks, change the understanding of structural controllability and affect the design of network models to control such networks.

Measuring Complexity and Predictability of Time Series with Flexible Multiscale Entropy for Sensor Networks

PubMed Central

Zhou, Renjie; Yang, Chen; Wan, Jian; Zhang, Wei; Guan, Bo; Xiong, Naixue

2017-01-01

Measurement of time series complexity and predictability is sometimes the cornerstone for proposing solutions to topology and congestion control problems in sensor networks. As a method of measuring time series complexity and predictability, multiscale entropy (MSE) has been widely applied in many fields. However, sample entropy, which is the fundamental component of MSE, measures the similarity of two subsequences of a time series with either zero or one, but without in-between values, which causes sudden changes of entropy values even if the time series embraces small changes. This problem becomes especially severe when the length of time series is getting short. For solving such the problem, we propose flexible multiscale entropy (FMSE), which introduces a novel similarity function measuring the similarity of two subsequences with full-range values from zero to one, and thus increases the reliability and stability of measuring time series complexity. The proposed method is evaluated on both synthetic and real time series, including white noise, 1/f noise and real vibration signals. The evaluation results demonstrate that FMSE has a significant improvement in reliability and stability of measuring complexity of time series, especially when the length of time series is short, compared to MSE and composite multiscale entropy (CMSE). The proposed method FMSE is capable of improving the performance of time series analysis based topology and traffic congestion control techniques. PMID:28383496

Measuring Complexity and Predictability of Time Series with Flexible Multiscale Entropy for Sensor Networks.

PubMed

Zhou, Renjie; Yang, Chen; Wan, Jian; Zhang, Wei; Guan, Bo; Xiong, Naixue

2017-04-06

Measurement of time series complexity and predictability is sometimes the cornerstone for proposing solutions to topology and congestion control problems in sensor networks. As a method of measuring time series complexity and predictability, multiscale entropy (MSE) has been widely applied in many fields. However, sample entropy, which is the fundamental component of MSE, measures the similarity of two subsequences of a time series with either zero or one, but without in-between values, which causes sudden changes of entropy values even if the time series embraces small changes. This problem becomes especially severe when the length of time series is getting short. For solving such the problem, we propose flexible multiscale entropy (FMSE), which introduces a novel similarity function measuring the similarity of two subsequences with full-range values from zero to one, and thus increases the reliability and stability of measuring time series complexity. The proposed method is evaluated on both synthetic and real time series, including white noise, 1/f noise and real vibration signals. The evaluation results demonstrate that FMSE has a significant improvement in reliability and stability of measuring complexity of time series, especially when the length of time series is short, compared to MSE and composite multiscale entropy (CMSE). The proposed method FMSE is capable of improving the performance of time series analysis based topology and traffic congestion control techniques.

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

NASA Astrophysics Data System (ADS)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

Antecedents and behavior-problem outcomes of parental monitoring and psychological control in early adolescence.

PubMed

Pettit, G S; Laird, R D; Dodge, K A; Bates, J E; Criss, M M

2001-01-01

The early childhood antecedents and behavior-problem correlates of monitoring and psychological control were examined in this prospective, longitudinal, multi-informant study. Parenting data were collected during home visit interviews with 440 mothers and their 13-year-old children. Behavior problems (anxiety/depression and delinquent behavior) were assessed via mother, teacher, and/or adolescent reports at ages 8 through 10 years and again at ages 13 through 14. Home-interview data collected at age 5 years were used to measure antecedent parenting (harsh/reactive, positive/proactive), family background (e.g., socioeconomic status), and mother-rated child behavior problems. Consistent with expectation, monitoring was anteceded by a proactive parenting style and by advantageous family-ecological characteristics, and psychological control was anteceded by harsh parenting and by mothers' earlier reports of child externalizing problems. Consistent with prior research, monitoring was associated with fewer delinquent behavior problems. Links between psychological control and adjustment were more complex: High levels of psychological control were associated with more delinquent problems for girls and for teens who were low in preadolescent delinquent problems, and with more anxiety/depression for girls and for teens who were high in preadolescent anxiety/depression.

Data Synchronization Discrepancies in a Formation Flight Control System

NASA Technical Reports Server (NTRS)

Ryan, Jack; Hanson, Curtis E.; Norlin, Ken A.; Allen, Michael J.; Schkolnik, Gerard (Technical Monitor)

2001-01-01

Aircraft hardware-in-the-loop simulation is an invaluable tool to flight test engineers; it reveals design and implementation flaws while operating in a controlled environment. Engineers, however, must always be skeptical of the results and analyze them within their proper context. Engineers must carefully ascertain whether an anomaly that occurs in the simulation will also occur in flight. This report presents a chronology illustrating how misleading simulation timing problems led to the implementation of an overly complex position data synchronization guidance algorithm in place of a simpler one. The report illustrates problems caused by the complex algorithm and how the simpler algorithm was chosen in the end. Brief descriptions of the project objectives, approach, and simulation are presented. The misleading simulation results and the conclusions then drawn are presented. The complex and simple guidance algorithms are presented with flight data illustrating their relative success.

Algorithms for sum-of-squares-based stability analysis and control design of uncertain nonlinear systems

NASA Astrophysics Data System (ADS)

Ataei-Esfahani, Armin

In this dissertation, we present algorithmic procedures for sum-of-squares based stability analysis and control design for uncertain nonlinear systems. In particular, we consider the case of robust aircraft control design for a hypersonic aircraft model subject to parametric uncertainties in its aerodynamic coefficients. In recent years, Sum-of-Squares (SOS) method has attracted increasing interest as a new approach for stability analysis and controller design of nonlinear dynamic systems. Through the application of SOS method, one can describe a stability analysis or control design problem as a convex optimization problem, which can efficiently be solved using Semidefinite Programming (SDP) solvers. For nominal systems, the SOS method can provide a reliable and fast approach for stability analysis and control design for low-order systems defined over the space of relatively low-degree polynomials. However, The SOS method is not well-suited for control problems relating to uncertain systems, specially those with relatively high number of uncertainties or those with non-affine uncertainty structure. In order to avoid issues relating to the increased complexity of the SOS problems for uncertain system, we present an algorithm that can be used to transform an SOS problem with uncertainties into a LMI problem with uncertainties. A new Probabilistic Ellipsoid Algorithm (PEA) is given to solve the robust LMI problem, which can guarantee the feasibility of a given solution candidate with an a-priori fixed probability of violation and with a fixed confidence level. We also introduce two approaches to approximate the robust region of attraction (RROA) for uncertain nonlinear systems with non-affine dependence on uncertainties. The first approach is based on a combination of PEA and SOS method and searches for a common Lyapunov function, while the second approach is based on the generalized Polynomial Chaos (gPC) expansion theorem combined with the SOS method and searches for parameter-dependent Lyapunov functions. The control design problem is investigated through a case study of a hypersonic aircraft model with parametric uncertainties. Through time-scale decomposition and a series of function approximations, the complexity of the aircraft model is reduced to fall within the capability of SDP solvers. The control design problem is then formulated as a convex problem using the dual of the Lyapunov theorem. A nonlinear robust controller is searched using the combined PEA/SOS method. The response of the uncertain aircraft model is evaluated for two sets of pilot commands. As the simulation results show, the aircraft remains stable under up to 50% uncertainty in aerodynamic coefficients and can follow the pilot commands.

Complexity Science and the Dynamics of Climate and Communication: Reducing Nursing Home Turnover

ERIC Educational Resources Information Center

Anderson, Ruth A.; Corazzini, Kirsten N.; McDaniel, Reuben R., Jr.

2004-01-01

Purpose: Turnover in nursing homes is a widespread problem adversely affecting care quality. Using complexity theory, we tested the effect of administrative climate, communication patterns, and the interaction between the two on turnover, controlling for facility context. Design and Methods: Perceptions of administrative climate and communication…

Stock management in hospital pharmacy using chance-constrained model predictive control.

PubMed

Jurado, I; Maestre, J M; Velarde, P; Ocampo-Martinez, C; Fernández, I; Tejera, B Isla; Prado, J R Del

2016-05-01

One of the most important problems in the pharmacy department of a hospital is stock management. The clinical need for drugs must be satisfied with limited work labor while minimizing the use of economic resources. The complexity of the problem resides in the random nature of the drug demand and the multiple constraints that must be taken into account in every decision. In this article, chance-constrained model predictive control is proposed to deal with this problem. The flexibility of model predictive control allows taking into account explicitly the different objectives and constraints involved in the problem while the use of chance constraints provides a trade-off between conservativeness and efficiency. The solution proposed is assessed to study its implementation in two Spanish hospitals. Copyright © 2015 Elsevier Ltd. All rights reserved.

The design of nonlinear observers for wind turbine dynamic state and parameter estimation

NASA Astrophysics Data System (ADS)

Ritter, B.; Schild, A.; Feldt, M.; Konigorski, U.

2016-09-01

This contribution addresses the dynamic state and parameter estimation problem which arises with more advanced wind turbine controllers. These control devices need precise information about the system's current state to outperform conventional industrial controllers effectively. First, the necessity of a profound scientific treatment on nonlinear observers for wind turbine application is highlighted. Secondly, the full estimation problem is introduced and the variety of nonlinear filters is discussed. Finally, a tailored observer architecture is proposed and estimation results of an illustrative application example from a complex simulation set-up are presented.

Visual control of prey-capture flight in dragonflies.

PubMed

Olberg, Robert M

2012-04-01

Interacting with a moving object poses a computational problem for an animal's nervous system. This problem has been elegantly solved by the dragonfly, a formidable visual predator on flying insects. The dragonfly computes an interception flight trajectory and steers to maintain it during its prey-pursuit flight. This review summarizes current knowledge about pursuit behavior and neurons thought to control interception in the dragonfly. When understood, this system has the potential for explaining how a small group of neurons can control complex interactions with moving objects. Copyright © 2011 Elsevier Ltd. All rights reserved.

Interior sound field control using generalized singular value decomposition in the frequency domain.

PubMed

Pasco, Yann; Gauthier, Philippe-Aubert; Berry, Alain; Moreau, Stéphane

2017-01-01

The problem of controlling a sound field inside a region surrounded by acoustic control sources is considered. Inspired by the Kirchhoff-Helmholtz integral, the use of double-layer source arrays allows such a control and avoids the modification of the external sound field by the control sources by the approximation of the sources as monopole and radial dipole transducers. However, the practical implementation of the Kirchhoff-Helmholtz integral in physical space leads to large numbers of control sources and error sensors along with excessive controller complexity in three dimensions. The present study investigates the potential of the Generalized Singular Value Decomposition (GSVD) to reduce the controller complexity and separate the effect of control sources on the interior and exterior sound fields, respectively. A proper truncation of the singular basis provided by the GSVD factorization is shown to lead to effective cancellation of the interior sound field at frequencies below the spatial Nyquist frequency of the control sources array while leaving the exterior sound field almost unchanged. Proofs of concept are provided through simulations achieved for interior problems by simulations in a free field scenario with circular arrays and in a reflective environment with square arrays.

Microgravity isolation system design: A modern control synthesis framework

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Knospe, C. R.; Allaire, P. E.; Grodsinsky, C. M.

1994-01-01

Manned orbiters will require active vibration isolation for acceleration-sensitive microgravity science experiments. Since umbilicals are highly desirable or even indispensable for many experiments, and since their presence greatly affects the complexity of the isolation problem, they should be considered in control synthesis. In this paper a general framework is presented for applying extended H2 synthesis methods to the three-dimensional microgravity isolation problem. The methodology integrates control and state frequency weighting and input and output disturbance accommodation techniques into the basic H2 synthesis approach. The various system models needed for design and analysis are also presented. The paper concludes with a discussion of a general design philosophy for the microgravity vibration isolation problem.

Microgravity isolation system design: A modern control synthesis framework

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Knospe, C. R.; Allaire, P. E.; Grodsinsky, C. M.

1994-01-01

Manned orbiters will require active vibration isolation for acceleration-sensitive microgravity science experiments. Since umbilicals are highly desirable or even indispensable for many experiments, and since their presence greatly affects the complexity of the isolation problem, they should be considered in control synthesis. A general framework is presented for applying extended H2 synthesis methods to the three-dimensional microgravity isolation problem. The methodology integrates control and state frequency weighting and input and output disturbance accommodation techniques into the basic H2 synthesis approach. The various system models needed for design and analysis are also presented. The paper concludes with a discussion of a general design philosophy for the microgravity vibration isolation problem.

On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

NASA Technical Reports Server (NTRS)

Tunstel, Edward; Jamshidi, Mo

1997-01-01

Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

Direct heuristic dynamic programming for damping oscillations in a large power system.

PubMed

Lu, Chao; Si, Jennie; Xie, Xiaorong

2008-08-01

This paper applies a neural-network-based approximate dynamic programming method, namely, the direct heuristic dynamic programming (direct HDP), to a large power system stability control problem. The direct HDP is a learning- and approximation-based approach to addressing nonlinear coordinated control under uncertainty. One of the major design parameters, the controller learning objective function, is formulated to directly account for network-wide low-frequency oscillation with the presence of nonlinearity, uncertainty, and coupling effect among system components. Results include a novel learning control structure based on the direct HDP with applications to two power system problems. The first case involves static var compensator supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a difficult complex system challenge by providing a new solution to a large interconnected power network oscillation damping control problem that frequently occurs in the China Southern Power Grid.

Network Access Control List Situation Awareness

ERIC Educational Resources Information Center

Reifers, Andrew

2010-01-01

Network security is a large and complex problem being addressed by multiple communities. Nevertheless, current theories in networking security appear to overestimate network administrators' ability to understand network access control lists (NACLs), providing few context specific user analyses. Consequently, the current research generally seems to…

An analysis of relational complexity in an air traffic control conflict detection task.

PubMed

Boag, Christine; Neal, Andrew; Loft, Shayne; Halford, Graeme S

2006-11-15

Theoretical analyses of air traffic complexity were carried out using the Method for the Analysis of Relational Complexity. Twenty-two air traffic controllers examined static air traffic displays and were required to detect and resolve conflicts. Objective measures of performance included conflict detection time and accuracy. Subjective perceptions of mental workload were assessed by a complexity-sorting task and subjective ratings of the difficulty of different aspects of the task. A metric quantifying the complexity of pair-wise relations among aircraft was able to account for a substantial portion of the variance in the perceived complexity and difficulty of conflict detection problems, as well as reaction time. Other variables that influenced performance included the mean minimum separation between aircraft pairs and the amount of time that aircraft spent in conflict.

Optimal Periodic Control Theory.

DTIC Science & Technology

1980-08-01

single pair of complex eigenvalues are restricted to the unit circle in the complex plane . This is shown by first applying the reciprocity property to a...figure 6.2a and for H in figure 6.2b. Traversing the right half plot of figure 6.1a in a counter-clockwise direction, beginning at the origin...respectively. Only the lower half of the plots are shown because this region provides the solutions of most interest to the optimal periodic control problem

QUALITY ASSURANCE AND QUALITY CONTROL IN THE DEVELOPMENT AND APPLICATION OF THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA) TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving from simple, local-scale problems toward complex, spatially explicit regional ones. Such problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and t...

The Quiet Revolution in Land Use Control.

ERIC Educational Resources Information Center

Bosselman, Fred; Callies, David

The Council on Environmental Quality commissioned this report on the innovative land use laws of several states to learn how some of the most complex land use issues and problems of re-allocating responsibilities between state and local governments are being addressed. Many of the laws analyzed are designed to deal with problems that are treated…

Water Pollution (Causes, Mechanisms, Solution).

ERIC Educational Resources Information Center

Strandberg, Carl

Written for the general public, this book illustrates the causes, status, problem areas, and prediction and control of water pollution. Water pollution is one of the most pressing issues of our time and the author communicates the complexities of this problem to the reader in common language. The purpose of the introductory chapter is to show what…

Fast and stable algorithms for computing the principal square root of a complex matrix

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Lian, Sui R.; Mcinnis, Bayliss C.

1987-01-01

This note presents recursive algorithms that are rapidly convergent and more stable for finding the principal square root of a complex matrix. Also, the developed algorithms are utilized to derive the fast and stable matrix sign algorithms which are useful in developing applications to control system problems.

Prevention and treatment of long-term social disability amongst young people with emerging severe mental illness with social recovery therapy (The PRODIGY Trial): study protocol for a randomised controlled trial.

PubMed

Fowler, David; French, Paul; Banerjee, Robin; Barton, Garry; Berry, Clio; Byrne, Rory; Clarke, Timothy; Fraser, Rick; Gee, Brioney; Greenwood, Kathryn; Notley, Caitlin; Parker, Sophie; Shepstone, Lee; Wilson, Jon; Yung, Alison R; Hodgekins, Joanne

2017-07-11

Young people who have social disability associated with severe and complex mental health problems are an important group in need of early intervention. Their problems often date back to childhood and become chronic at an early age. Without intervention, the long-term prognosis is often poor and the economic costs very large. There is a major gap in the provision of evidence-based interventions for this group, and therefore new approaches to detection and intervention are needed. This trial provides a definitive evaluation of a new approach to early intervention with young people with social disability and severe and complex mental health problems using social recovery therapy (SRT) over a period of 9 months to improve mental health and social recovery outcomes. This is a pragmatic, multi-centre, single blind, superiority randomised controlled trial. It is conducted in three sites in the UK: Sussex, Manchester and East Anglia. Participants are aged 16 to 25 and have both persistent and severe social disability (defined as engaged in less than 30 hours per week of structured activity) and severe and complex mental health problems. The target sample size is 270 participants, providing 135 participants in each trial arm. Participants are randomised 1:1 using a web-based randomisation system and allocated to either SRT plus optimised treatment as usual (enhanced standard care) or enhanced standard care alone. The primary outcome is time use, namely hours spent in structured activity per week at 15 months post-randomisation. Secondary outcomes assess typical mental health problems of the group, including subthreshold psychotic symptoms, negative symptoms, depression and anxiety. Time use, secondary outcomes and health economic measures are assessed at 9, 15 and 24 months post-randomisation. This definitive trial will be the first to evaluate a novel psychological treatment for social disability and mental health problems in young people presenting with social disability and severe and complex non-psychotic mental health problems. The results will have important implications for policy and practice in the detection and early intervention for this group in mental health services. Trial Registry: International Standard Randomised Controlled Trial Number (ISRCTN) Registry. ISRCTN47998710 (registered 29/11/2012).

Optical techniques to feed and control GaAs MMIC modules for phased array antenna applications

NASA Astrophysics Data System (ADS)

Bhasin, K. B.; Anzic, G.; Kunath, R. R.; Connolly, D. J.

A complex signal distribution system is required to feed and control GaAs monolithic microwave integrated circuits (MMICs) for phased array antenna applications above 20 GHz. Each MMIC module will require one or more RF lines, one or more bias voltage lines, and digital lines to provide a minimum of 10 bits of combined phase and gain control information. In a closely spaced array, the routing of these multiple lines presents difficult topology problems as well as a high probability of signal interference. To overcome GaAs MMIC phased array signal distribution problems optical fibers interconnected to monolithically integrated optical components with GaAs MMIC array elements are proposed as a solution. System architecture considerations using optical fibers are described. The analog and digital optical links to respectively feed and control MMIC elements are analyzed. It is concluded that a fiber optic network will reduce weight and complexity, and increase reliability and performance, but higher power will be required.

Optical techniques to feed and control GaAs MMIC modules for phased array antenna applications

NASA Technical Reports Server (NTRS)

Bhasin, K. B.; Anzic, G.; Kunath, R. R.; Connolly, D. J.

1986-01-01

A complex signal distribution system is required to feed and control GaAs monolithic microwave integrated circuits (MMICs) for phased array antenna applications above 20 GHz. Each MMIC module will require one or more RF lines, one or more bias voltage lines, and digital lines to provide a minimum of 10 bits of combined phase and gain control information. In a closely spaced array, the routing of these multiple lines presents difficult topology problems as well as a high probability of signal interference. To overcome GaAs MMIC phased array signal distribution problems optical fibers interconnected to monolithically integrated optical components with GaAs MMIC array elements are proposed as a solution. System architecture considerations using optical fibers are described. The analog and digital optical links to respectively feed and control MMIC elements are analyzed. It is concluded that a fiber optic network will reduce weight and complexity, and increase reliability and performance, but higher power will be required.

Characterizing Protein Complexes with UV absorption, Light Scattering, and Refractive Index Detection.

NASA Astrophysics Data System (ADS)

Trainoff, Steven

2009-03-01

Many modern pharmaceuticals and naturally occurring biomolecules consist of complexes of proteins and polyethylene glycol or carbohydrates. In the case of vaccine development, these complexes are often used to induce or amplify immune responses. For protein therapeutics they are used to modify solubility and function, or to control the rate of degradation and elimination of a drug from the body. Characterizing the stoichiometry of these complexes is an important industrial problem that presents a formidable challenge to analytical instrument designers. Traditional analytical methods, such as using florescent tagging, chemical assays, and mass spectrometry perturb the system so dramatically that the complexes are often destroyed or uncontrollably modified by the measurement. A solution to this problem consists of fractionating the samples and then measuring the fractions using sequential non-invasive detectors that are sensitive to different components of the complex. We present results using UV absorption, which is primarily sensitive to the protein fraction, Light Scattering, which measures the total weight average molar mass, and Refractive Index detection, which measures the net concentration. We also present a solution of the problem inter-detector band-broadening problem that has heretofore made this approach impractical. Presented will be instrumentation and an analysis method that overcome these obstacles and make this technique a reliable and robust way of non-invasively characterizing these industrially important compounds.

The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems.

PubMed

Baars, Martine; Wijnia, Lisette; Paas, Fred

2017-01-01

Self-regulated learning (SRL) skills are essential for learning during school years, particularly in complex problem-solving domains, such as biology and math. Although a lot of studies have focused on the cognitive resources that are needed for learning to solve problems in a self-regulated way, affective and motivational resources have received much less research attention. The current study investigated the relation between affect (i.e., Positive Affect and Negative Affect Scale), motivation (i.e., autonomous and controlled motivation), mental effort, SRL skills, and problem-solving performance when learning to solve biology problems in a self-regulated online learning environment. In the learning phase, secondary education students studied video-modeling examples of how to solve hereditary problems, solved hereditary problems which they chose themselves from a set of problems with different complexity levels (i.e., five levels). In the posttest, students solved hereditary problems, self-assessed their performance, and chose a next problem from the set of problems but did not solve these problems. The results from this study showed that negative affect, inaccurate self-assessments during the posttest, and higher perceptions of mental effort during the posttest were negatively associated with problem-solving performance after learning in a self-regulated way.

Research directions in large scale systems and decentralized control

NASA Technical Reports Server (NTRS)

Tenney, R. R.

1980-01-01

Control theory provides a well established framework for dealing with automatic decision problems and a set of techniques for automatic decision making which exploit special structure, but it does not deal well with complexity. The potential exists for combining control theoretic and knowledge based concepts into a unified approach. The elements of control theory are diagrammed, including modern control and large scale systems.

Making the EZ Choice

NASA Technical Reports Server (NTRS)

2001-01-01

Analytical Mechanics Associates, Inc. (AMA), of Hampton, Virginia, created the EZopt software application through Small Business Innovation Research (SBIR) funding from NASA's Langley Research Center. The new software is a user-friendly tool kit that provides quick and logical solutions to complex optimal control problems. In its most basic form, EZopt converts process data into math equations and then proceeds to utilize those equations to solve problems within control systems. EZopt successfully proved its advantage when applied to short-term mission planning and onboard flight computer implementation. The technology has also solved multiple real-life engineering problems faced in numerous commercial operations. For instance, mechanical engineers use EZopt to solve control problems with robots, while chemical plants implement the application to overcome situations with batch reactors and temperature control. In the emerging field of commercial aerospace, EZopt is able to optimize trajectories for launch vehicles and perform potential space station- keeping tasks. Furthermore, the software also helps control electromagnetic devices in the automotive industry.

Perceived control moderates the relationship between social capital and binge drinking: longitudinal findings from the Montreal Neighborhood Networks and Health Aging (MoNNET-HA) panel.

PubMed

Child, Stephanie; Stewart, Steven; Moore, Spencer

2017-02-01

Cross-sectional research suggests social capital has negative consequences for problem drinking behaviors. Previous studies have suggested psychosocial resources, including perceived control, may buffer this association. Little research has examined whether such relationships persist longitudinally. Random effects models examined between-person relationships among problem drinking, social capital, and perceived control, and whether perceived control moderated the relationship between social capital and drinking. Fixed effects models assessed whether social capital and perceived control were related to changes in problem drinking. Greater network capital and generalized trust predicted higher odds of binge drinking (RR = 1.08; 95% CI = 1.03-1.12 and RR = 1.23; 95% CI = 1.03-1.48, respectively). Perceived control moderated the positive association of network capital with binge drinking (RR = 0.91; 95% CI = 0.87-0.96). The present findings support previous notions about the complex role of social capital on health, and offer new insights on the role of perceived control on problem drinking. Copyright © 2016 Elsevier Inc. All rights reserved.

Multi-agent based control of large-scale complex systems employing distributed dynamic inference engine

NASA Astrophysics Data System (ADS)

Zhang, Daili

Increasing societal demand for automation has led to considerable efforts to control large-scale complex systems, especially in the area of autonomous intelligent control methods. The control system of a large-scale complex system needs to satisfy four system level requirements: robustness, flexibility, reusability, and scalability. Corresponding to the four system level requirements, there arise four major challenges. First, it is difficult to get accurate and complete information. Second, the system may be physically highly distributed. Third, the system evolves very quickly. Fourth, emergent global behaviors of the system can be caused by small disturbances at the component level. The Multi-Agent Based Control (MABC) method as an implementation of distributed intelligent control has been the focus of research since the 1970s, in an effort to solve the above-mentioned problems in controlling large-scale complex systems. However, to the author's best knowledge, all MABC systems for large-scale complex systems with significant uncertainties are problem-specific and thus difficult to extend to other domains or larger systems. This situation is partly due to the control architecture of multiple agents being determined by agent to agent coupling and interaction mechanisms. Therefore, the research objective of this dissertation is to develop a comprehensive, generalized framework for the control system design of general large-scale complex systems with significant uncertainties, with the focus on distributed control architecture design and distributed inference engine design. A Hybrid Multi-Agent Based Control (HyMABC) architecture is proposed by combining hierarchical control architecture and module control architecture with logical replication rings. First, it decomposes a complex system hierarchically; second, it combines the components in the same level as a module, and then designs common interfaces for all of the components in the same module; third, replications are made for critical agents and are organized into logical rings. This architecture maintains clear guidelines for complexity decomposition and also increases the robustness of the whole system. Multiple Sectioned Dynamic Bayesian Networks (MSDBNs) as a distributed dynamic probabilistic inference engine, can be embedded into the control architecture to handle uncertainties of general large-scale complex systems. MSDBNs decomposes a large knowledge-based system into many agents. Each agent holds its partial perspective of a large problem domain by representing its knowledge as a Dynamic Bayesian Network (DBN). Each agent accesses local evidence from its corresponding local sensors and communicates with other agents through finite message passing. If the distributed agents can be organized into a tree structure, satisfying the running intersection property and d-sep set requirements, globally consistent inferences are achievable in a distributed way. By using different frequencies for local DBN agent belief updating and global system belief updating, it balances the communication cost with the global consistency of inferences. In this dissertation, a fully factorized Boyen-Koller (BK) approximation algorithm is used for local DBN agent belief updating, and the static Junction Forest Linkage Tree (JFLT) algorithm is used for global system belief updating. MSDBNs assume a static structure and a stable communication network for the whole system. However, for a real system, sub-Bayesian networks as nodes could be lost, and the communication network could be shut down due to partial damage in the system. Therefore, on-line and automatic MSDBNs structure formation is necessary for making robust state estimations and increasing survivability of the whole system. A Distributed Spanning Tree Optimization (DSTO) algorithm, a Distributed D-Sep Set Satisfaction (DDSSS) algorithm, and a Distributed Running Intersection Satisfaction (DRIS) algorithm are proposed in this dissertation. Combining these three distributed algorithms and a Distributed Belief Propagation (DBP) algorithm in MSDBNs makes state estimations robust to partial damage in the whole system. Combining the distributed control architecture design and the distributed inference engine design leads to a process of control system design for a general large-scale complex system. As applications of the proposed methodology, the control system design of a simplified ship chilled water system and a notional ship chilled water system have been demonstrated step by step. Simulation results not only show that the proposed methodology gives a clear guideline for control system design for general large-scale complex systems with dynamic and uncertain environment, but also indicate that the combination of MSDBNs and HyMABC can provide excellent performance for controlling general large-scale complex systems.

Interdisciplinary optimum design. [of aerospace structures

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw; Haftka, Raphael T.

1986-01-01

Problems related to interdisciplinary interactions in the design of a complex engineering systems are examined with reference to aerospace applications. The interdisciplinary optimization problems examined include those dealing with controls and structures, materials and structures, control and stability, structure and aerodynamics, and structure and thermodynamics. The discussion is illustrated by the following specific applications: integrated aerodynamic/structural optimization of glider wing; optimization of an antenna parabolic dish structure for minimum weight and prescribed emitted signal gain; and a multilevel optimization study of a transport aircraft.

Algorithm For Optimal Control Of Large Structures

NASA Technical Reports Server (NTRS)

Salama, Moktar A.; Garba, John A..; Utku, Senol

1989-01-01

Cost of computation appears competitive with other methods. Problem to compute optimal control of forced response of structure with n degrees of freedom identified in terms of smaller number, r, of vibrational modes. Article begins with Hamilton-Jacobi formulation of mechanics and use of quadratic cost functional. Complexity reduced by alternative approach in which quadratic cost functional expressed in terms of control variables only. Leads to iterative solution of second-order time-integral matrix Volterra equation of second kind containing optimal control vector. Cost of algorithm, measured in terms of number of computations required, is of order of, or less than, cost of prior algoritms applied to similar problems.

Synchronization of coupled stochastic complex-valued dynamical networks with time-varying delays via aperiodically intermittent adaptive control

NASA Astrophysics Data System (ADS)

Wang, Pengfei; Jin, Wei; Su, Huan

2018-04-01

This paper deals with the synchronization problem of a class of coupled stochastic complex-valued drive-response networks with time-varying delays via aperiodically intermittent adaptive control. Different from the previous works, the intermittent control is aperiodic and adaptive, and the restrictions on the control width and time delay are removed, which lead to a larger application scope for this control strategy. Then, based on the Lyapunov method and Kirchhoff's Matrix Tree Theorem as well as differential inequality techniques, several novel synchronization conditions are derived for the considered model. Specially, impulsive control is also considered, which can be seen as a special case of the aperiodically intermittent control when the control width tends to zero. And the corresponding synchronization criteria are given as well. As an application of the theoretical results, a class of stochastic complex-valued coupled oscillators with time-varying delays is studied, and the numerical simulations are also given to demonstrate the effectiveness of the control strategies.

Fluid Intelligence Predicts Novel Rule Implementation in a Distributed Frontoparietal Control Network.

PubMed

Tschentscher, Nadja; Mitchell, Daniel; Duncan, John

2017-05-03

Fluid intelligence has been associated with a distributed cognitive control or multiple-demand (MD) network, comprising regions of lateral frontal, insular, dorsomedial frontal, and parietal cortex. Human fluid intelligence is also intimately linked to task complexity, and the process of solving complex problems in a sequence of simpler, more focused parts. Here, a complex target detection task included multiple independent rules, applied one at a time in successive task epochs. Although only one rule was applied at a time, increasing task complexity (i.e., the number of rules) impaired performance in participants of lower fluid intelligence. Accompanying this loss of performance was reduced response to rule-critical events across the distributed MD network. The results link fluid intelligence and MD function to a process of attentional focus on the successive parts of complex behavior. SIGNIFICANCE STATEMENT Fluid intelligence is intimately linked to the ability to structure complex problems in a sequence of simpler, more focused parts. We examine the basis for this link in the functions of a distributed frontoparietal or multiple-demand (MD) network. With increased task complexity, participants of lower fluid intelligence showed reduced responses to task-critical events. Reduced responses in the MD system were accompanied by impaired behavioral performance. Low fluid intelligence is linked to poor foregrounding of task-critical information across a distributed MD system. Copyright © 2017 Tschentscher et al.

Physical insight into the simultaneous optimization of structure and control

NASA Technical Reports Server (NTRS)

Jacques, Robert N.; Miller, David W.

1993-01-01

Recent trends in spacecraft design which yield larger structures with more stringent performance requirements place many flexible modes of the structure within the bandwidth of active controllers. The resulting complications to the spacecraft design make it highly desirable to understand the impact of structural changes on an optimally controlled structure. This work uses low structural models with optimal H(sub 2) and H(sub infinity) controllers to develop some basic insight into this problem. This insight concentrates on several basic approaches to improving controlled performance and how these approaches interact in determining the optimal designs. A numerical example is presented to demonstrate how this insight can be generalized to more complex problems.

Some problems with the design of self-learning management systems

NASA Technical Reports Server (NTRS)

Flikop, Ziny

1992-01-01

In this paper some problems in the design of management systems for complex objects are discussed. Considering the absence of adequate models and the fact that human expertise in the management of non-stationary objects becomes obsolete quickly, the use of self-learning together with a two-step optimization of on-line control rules is suggested. To prepare for the object analysis, a set of definitions has been proposed. Traditional and fuzzy sets approaches are used in the analysis. To decrease the reaction time of the control system, we propose the development of control rules without feedback.

Emotion Regulation Enhancement of Cognitive Behavior Therapy for College Student Problem Drinkers: A Pilot Randomized Controlled Trial

ERIC Educational Resources Information Center

Ford, Julian D.; Grasso, Damion J.; Levine, Joan; Tennen, Howard

2018-01-01

This pilot randomized clinical trial tested an emotion regulation enhancement to cognitive behavior therapy (CBT) with 29 college student problem drinkers with histories of complex trauma and current clinically significant traumatic stress symptoms. Participants received eight face-to-face sessions of manualized Internet-supported CBT for problem…

Piloted simulation study of the effects of an automated trim system on flight characteristics of a light twin-engine airplane with one engine inoperative

NASA Technical Reports Server (NTRS)

Stewart, E. C.; Brown, P. W.; Yenni, K. R.

1986-01-01

A simulation study was conducted to investigate the piloting problems associated with failure of an engine on a generic light twin-engine airplane. A primary piloting problem for a light twin-engine airplane after an engine failure is maintaining precise control of the airplane in the presence of large steady control forces. To address this problem, a simulated automatic trim system which drives the trim tabs as an open-loop function of propeller slipstream measurements was developed. The simulated automatic trim system was found to greatly increase the controllability in asymmetric powered flight without having to resort to complex control laws or an irreversible control system. However, the trim-tab control rates needed to produce the dramatic increase in controllability may require special design consideration for automatic trim system failures. Limited measurements obtained in full-scale flight tests confirmed the fundamental validity of the proposed control law.

A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification.

PubMed

Guo, Wei-Feng; Zhang, Shao-Wu; Shi, Qian-Qian; Zhang, Cheng-Ming; Zeng, Tao; Chen, Luonan

2018-01-19

The advances in target control of complex networks not only can offer new insights into the general control dynamics of complex systems, but also be useful for the practical application in systems biology, such as discovering new therapeutic targets for disease intervention. In many cases, e.g. drug target identification in biological networks, we usually require a target control on a subset of nodes (i.e., disease-associated genes) with minimum cost, and we further expect that more driver nodes consistent with a certain well-selected network nodes (i.e., prior-known drug-target genes). Therefore, motivated by this fact, we pose and address a new and practical problem called as target control problem with objectives-guided optimization (TCO): how could we control the interested variables (or targets) of a system with the optional driver nodes by minimizing the total quantity of drivers and meantime maximizing the quantity of constrained nodes among those drivers. Here, we design an efficient algorithm (TCOA) to find the optional driver nodes for controlling targets in complex networks. We apply our TCOA to several real-world networks, and the results support that our TCOA can identify more precise driver nodes than the existing control-fucus approaches. Furthermore, we have applied TCOA to two bimolecular expert-curate networks. Source code for our TCOA is freely available from http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm or https://github.com/WilfongGuo/guoweifeng . In the previous theoretical research for the full control, there exists an observation and conclusion that the driver nodes tend to be low-degree nodes. However, for target control the biological networks, we find interestingly that the driver nodes tend to be high-degree nodes, which is more consistent with the biological experimental observations. Furthermore, our results supply the novel insights into how we can efficiently target control a complex system, and especially many evidences on the practical strategic utility of TCOA to incorporate prior drug information into potential drug-target forecasts. Thus applicably, our method paves a novel and efficient way to identify the drug targets for leading the phenotype transitions of underlying biological networks.

The exclusion problem in seasonally forced epidemiological systems.

PubMed

Greenman, J V; Adams, B

2015-02-21

The pathogen exclusion problem is the problem of finding control measures that will exclude a pathogen from an ecological system or, if the system is already disease-free, maintain it in that state. To solve this problem we work within a holistic control theory framework which is consistent with conventional theory for simple systems (where there is no external forcing and constant controls) and seamlessly generalises to complex systems that are subject to multiple component seasonal forcing and targeted variable controls. We develop, customise and integrate a range of numerical and algebraic procedures that provide a coherent methodology powerful enough to solve the exclusion problem in the general case. An important aspect of our solution procedure is its two-stage structure which reveals the epidemiological consequences of the controls used for exclusion. This information augments technical and economic considerations in the design of an acceptable exclusion strategy. Our methodology is used in two examples to show how time-varying controls can exploit the interference and reinforcement created by the external and internal lag structure and encourage the system to 'take over' some of the exclusion effort. On-off control switching, resonant amplification, optimality and controllability are important issues that emerge in the discussion. Copyright © 2014 Elsevier Ltd. All rights reserved.

Complex Problem Solving in Teams: The Impact of Collective Orientation on Team Process Demands.

PubMed

Hagemann, Vera; Kluge, Annette

2017-01-01

Complex problem solving is challenging and a high-level cognitive process for individuals. When analyzing complex problem solving in teams, an additional, new dimension has to be considered, as teamwork processes increase the requirements already put on individual team members. After introducing an idealized teamwork process model, that complex problem solving teams pass through, and integrating the relevant teamwork skills for interdependently working teams into the model and combining it with the four kinds of team processes (transition, action, interpersonal, and learning processes), the paper demonstrates the importance of fulfilling team process demands for successful complex problem solving within teams. Therefore, results from a controlled team study within complex situations are presented. The study focused on factors that influence action processes, like coordination, such as emergent states like collective orientation, cohesion, and trust and that dynamically enable effective teamwork in complex situations. Before conducting the experiments, participants were divided by median split into two-person teams with either high ( n = 58) or low ( n = 58) collective orientation values. The study was conducted with the microworld C3Fire, simulating dynamic decision making, and acting in complex situations within a teamwork context. The microworld includes interdependent tasks such as extinguishing forest fires or protecting houses. Two firefighting scenarios had been developed, which takes a maximum of 15 min each. All teams worked on these two scenarios. Coordination within the team and the resulting team performance were calculated based on a log-file analysis. The results show that no relationships between trust and action processes and team performance exist. Likewise, no relationships were found for cohesion. Only collective orientation of team members positively influences team performance in complex environments mediated by action processes such as coordination within the team. The results are discussed in relation to previous empirical findings and to learning processes within the team with a focus on feedback strategies.

Complex Problem Solving in Teams: The Impact of Collective Orientation on Team Process Demands

PubMed Central

Hagemann, Vera; Kluge, Annette

2017-01-01

Complex problem solving is challenging and a high-level cognitive process for individuals. When analyzing complex problem solving in teams, an additional, new dimension has to be considered, as teamwork processes increase the requirements already put on individual team members. After introducing an idealized teamwork process model, that complex problem solving teams pass through, and integrating the relevant teamwork skills for interdependently working teams into the model and combining it with the four kinds of team processes (transition, action, interpersonal, and learning processes), the paper demonstrates the importance of fulfilling team process demands for successful complex problem solving within teams. Therefore, results from a controlled team study within complex situations are presented. The study focused on factors that influence action processes, like coordination, such as emergent states like collective orientation, cohesion, and trust and that dynamically enable effective teamwork in complex situations. Before conducting the experiments, participants were divided by median split into two-person teams with either high (n = 58) or low (n = 58) collective orientation values. The study was conducted with the microworld C3Fire, simulating dynamic decision making, and acting in complex situations within a teamwork context. The microworld includes interdependent tasks such as extinguishing forest fires or protecting houses. Two firefighting scenarios had been developed, which takes a maximum of 15 min each. All teams worked on these two scenarios. Coordination within the team and the resulting team performance were calculated based on a log-file analysis. The results show that no relationships between trust and action processes and team performance exist. Likewise, no relationships were found for cohesion. Only collective orientation of team members positively influences team performance in complex environments mediated by action processes such as coordination within the team. The results are discussed in relation to previous empirical findings and to learning processes within the team with a focus on feedback strategies. PMID:29033886

Complex regional pain syndrome

MedlinePlus

... to properly control blood flow, feeling (sensation), and temperature to the affected area. This leads to problems ... lasts 1 to 3 months): Changes in skin temperature, switching between warm or cold Faster growth of ...

An Actor-Network Theory Analysis of Policy Innovation for Smoke-Free Places: Understanding Change in Complex Systems

PubMed Central

Borland, Ron; Coghill, Ken

2010-01-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems. PMID:20466949

An actor-network theory analysis of policy innovation for smoke-free places: understanding change in complex systems.

PubMed

Young, David; Borland, Ron; Coghill, Ken

2010-07-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems.

Development of a Comprehensive Digital Avionics Curriculum for the Aeronautical Engineer

DTIC Science & Technology

2006-03-01

able to analyze and design aircraft and missile guidance and control systems, including feedback stabilization schemes and stochastic processes, using ...Uncertainty modeling for robust control; Robust closed-loop stability and performance; Robust H- infinity control; Robustness check using mu-analysis...Controlled feedback (reduces noise) 3. Statistical group response (reduce pressure toward conformity) When used as a tool to study a complex problem

Coordinating complex problem-solving among distributed intelligent agents

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1992-01-01

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.

Multiplexed Predictive Control of a Large Commercial Turbofan Engine

NASA Technical Reports Server (NTRS)

Richter, hanz; Singaraju, Anil; Litt, Jonathan S.

2008-01-01

Model predictive control is a strategy well-suited to handle the highly complex, nonlinear, uncertain, and constrained dynamics involved in aircraft engine control problems. However, it has thus far been infeasible to implement model predictive control in engine control applications, because of the combination of model complexity and the time allotted for the control update calculation. In this paper, a multiplexed implementation is proposed that dramatically reduces the computational burden of the quadratic programming optimization that must be solved online as part of the model-predictive-control algorithm. Actuator updates are calculated sequentially and cyclically in a multiplexed implementation, as opposed to the simultaneous optimization taking place in conventional model predictive control. Theoretical aspects are discussed based on a nominal model, and actual computational savings are demonstrated using a realistic commercial engine model.

Outer synchronization of complex networks with internal delay and coupling delay via aperiodically intermittent pinning control

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Wang, Chunpeng; Xia, Zhiqiu

This paper concerns the outer synchronization problem between two complex delayed networks via the method of aperiodically intermittent pinning control. Apart from previous works, internal delay and coupling delay are both involved in this model, and the designed intermittent controllers can be aperiodic. The main work in this paper can be summarized as follows: First, two cases of aperiodically intermittent control with constant gain and adaptive gain are implemented, respectively. The intermittent control and pinning control are combined to reduce consumptions further. Then, based on the Lyapunov stability theory, synchronization protocols are given by strict derivation. Especially, the designed controllers are indeed simple and valid in application of theory to practice. Finally, numerical examples put the proposed control methods to the test.

Information needs related to extension service and community outreach.

PubMed

Bottcher, Robert W

2003-06-01

Air quality affects everyone. Some people are affected by air quality impacts, regulations, and technological developments in several ways. Stakeholders include the medical community, ecologists, government regulators, industries, technology providers, academic professionals, concerned citizens, the news media, and elected officials. Each of these groups may perceive problems and opportunities differently, but all need access to information as it is developed. The diversity and complexity of air quality problems contribute to the challenges faced by extension and outreach professionals who must communicate with stakeholders having diverse backgrounds. Gases, particulates, biological aerosols, pathogens, and odors all require expensive and relatively complex technology to measure and control. Economic constraints affect the ability of regulators and others to measure air quality, and industry and others to control it. To address these challenges, while communicating air quality research results and concepts to stakeholders, three areas of information needs are evident. (1) A basic understanding of the fundamental concepts regarding air pollutants and their measurement and control is needed by all stakeholders; the Extension Specialist, to be effective, must help people move some distance up the learning curve. (2) Each problem or set of problems must be reasonably well defined since comprehensive solution of all problems simultaneously may not be feasible; for instance, the solution of an odor problem associated with animal production may not address atmospheric effects due to ammonia emissions. (3) The integrity of the communication process must be preserved by avoiding prejudice and protectionism; although stakeholders may seek to modify information to enhance their interests, extension and outreach professionals must be willing to present unwelcome information or admit to a lack of information. A solid grounding in fundamental concepts, careful and fair problem definition, and a resolute commitment to integrity and credibility will enable effective communication of air quality information to and among diverse stakeholders.

Periodic reference tracking control approach for smart material actuators with complex hysteretic characteristics

NASA Astrophysics Data System (ADS)

Sun, Zhiyong; Hao, Lina; Song, Bo; Yang, Ruiguo; Cao, Ruimin; Cheng, Yu

2016-10-01

Micro/nano positioning technologies have been attractive for decades for their various applications in both industrial and scientific fields. The actuators employed in these technologies are typically smart material actuators, which possess inherent hysteresis that may cause systems behave unexpectedly. Periodic reference tracking capability is fundamental for apparatuses such as scanning probe microscope, which employs smart material actuators to generate periodic scanning motion. However, traditional controller such as PID method cannot guarantee accurate fast periodic scanning motion. To tackle this problem and to conduct practical implementation in digital devices, this paper proposes a novel control method named discrete extended unparallel Prandtl-Ishlinskii model based internal model (d-EUPI-IM) control approach. To tackle modeling uncertainties, the robust d-EUPI-IM control approach is investigated, and the associated sufficient stabilizing conditions are derived. The advantages of the proposed controller are: it is designed and represented in discrete form, thus practical for digital devices implementation; the extended unparallel Prandtl-Ishlinskii model can precisely represent forward/inverse complex hysteretic characteristics, thus can reduce modeling uncertainties and benefits controllers design; in addition, the internal model principle based control module can be utilized as a natural oscillator for tackling periodic references tracking problem. The proposed controller was verified through comparative experiments on a piezoelectric actuator platform, and convincing results have been achieved.

Solution of an optimal control lifting body entry problem by an improved method of perturbation functions

NASA Technical Reports Server (NTRS)

Garcia, F., Jr.

1975-01-01

This paper presents a solution to a complex lifting reentry three-degree-of-freedom problem by using the calculus of variations to minimize the integral of the sum of the aerodynamics loads and heat rate input to the vehicle. The entry problem considered does not have state and/or control constraints along the trajectory. The calculus of variations method applied to this problem gives rise to a set of necessary conditions which are used to formulate a two point boundary value (TPBV) problem. This TPBV problem is then numerically solved by an improved method of perturbation functions (IMPF) using several starting co-state vectors. These vectors were chosen so that each one had a larger norm with respect to show how the envelope of convergence is significantly increased using this method and cases are presented to point this out.

Environmental/Biomedical Terminology Index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huffstetler, J.K.; Dailey, N.S.; Rickert, L.W.

1976-12-01

The Information Center Complex (ICC), a centrally administered group of information centers, provides information support to environmental and biomedical research groups and others within and outside Oak Ridge National Laboratory. In-house data base building and development of specialized document collections are important elements of the ongoing activities of these centers. ICC groups must be concerned with language which will adequately classify and insure retrievability of document records. Language control problems are compounded when the complexity of modern scientific problem solving demands an interdisciplinary approach. Although there are several word lists, indexes, and thesauri specific to various scientific disciplines usually groupedmore » as Environmental Sciences, no single generally recognized authority can be used as a guide to the terminology of all environmental science. If biomedical terminology for the description of research on environmental effects is also needed, the problem becomes even more complex. The building of a word list which can be used as a general guide to the environmental/biomedical sciences has been a continuing activity of the Information Center Complex. This activity resulted in the publication of the Environmental Biomedical Terminology Index (EBTI).« less

Finite-time mixed outer synchronization of complex networks with coupling time-varying delay.

PubMed

He, Ping; Ma, Shu-Hua; Fan, Tao

2012-12-01

This article is concerned with the problem of finite-time mixed outer synchronization (FMOS) of complex networks with coupling time-varying delay. FMOS is a recently developed generalized synchronization concept, i.e., in which different state variables of the corresponding nodes can evolve into finite-time complete synchronization, finite-time anti-synchronization, and even amplitude finite-time death simultaneously for an appropriate choice of the controller gain matrix. Some novel stability criteria for the synchronization between drive and response complex networks with coupling time-varying delay are derived using the Lyapunov stability theory and linear matrix inequalities. And a simple linear state feedback synchronization controller is designed as a result. Numerical simulations for two coupled networks of modified Chua's circuits are then provided to demonstrate the effectiveness and feasibility of the proposed complex networks control and synchronization schemes and then compared with the proposed results and the previous schemes for accuracy.

Individual strategy ratings improve the control for task difficulty effects in arithmetic problem solving paradigms.

PubMed

Tschentscher, Nadja; Hauk, Olaf

2015-01-01

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports control better for task complexity across arithmetic conditions than objective features (Tschentscher and Hauk, 2014). Here, we analyzed the relative predictive value of self-reported strategies and objective features for performance in addition and multiplication tasks, by using a paradigm designed for neuroimaging research. We found a superiority of strategy ratings as predictor of performance above objective features. In a Principal Component Analysis on reaction times, the first component explained over 90 percent of variance and factor loadings reflected percentages of self-reported strategies well. In multiple regression analyses on reaction times, self-reported strategies performed equally well or better than objective features, depending on the operation type. A Receiver Operating Characteristic (ROC) analysis confirmed this result. Reaction times classified task complexity better when defined by individual ratings. This suggests that participants' strategy ratings are reliable predictors of arithmetic complexity and should be taken into account in neuroimaging research.

Individual strategy ratings improve the control for task difficulty effects in arithmetic problem solving paradigms

PubMed Central

Tschentscher, Nadja; Hauk, Olaf

2015-01-01

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports control better for task complexity across arithmetic conditions than objective features (Tschentscher and Hauk, 2014). Here, we analyzed the relative predictive value of self-reported strategies and objective features for performance in addition and multiplication tasks, by using a paradigm designed for neuroimaging research. We found a superiority of strategy ratings as predictor of performance above objective features. In a Principal Component Analysis on reaction times, the first component explained over 90 percent of variance and factor loadings reflected percentages of self-reported strategies well. In multiple regression analyses on reaction times, self-reported strategies performed equally well or better than objective features, depending on the operation type. A Receiver Operating Characteristic (ROC) analysis confirmed this result. Reaction times classified task complexity better when defined by individual ratings. This suggests that participants’ strategy ratings are reliable predictors of arithmetic complexity and should be taken into account in neuroimaging research. PMID:26321997

Controlling herding in minority game systems

NASA Astrophysics Data System (ADS)

Zhang, Ji-Qiang; Huang, Zi-Gang; Wu, Zhi-Xi; Su, Riqi; Lai, Ying-Cheng

2016-02-01

Resource allocation takes place in various types of real-world complex systems such as urban traffic, social services institutions, economical and ecosystems. Mathematically, the dynamical process of resource allocation can be modeled as minority games. Spontaneous evolution of the resource allocation dynamics, however, often leads to a harmful herding behavior accompanied by strong fluctuations in which a large majority of agents crowd temporarily for a few resources, leaving many others unused. Developing effective control methods to suppress and eliminate herding is an important but open problem. Here we develop a pinning control method, that the fluctuations of the system consist of intrinsic and systematic components allows us to design a control scheme with separated control variables. A striking finding is the universal existence of an optimal pinning fraction to minimize the variance of the system, regardless of the pinning patterns and the network topology. We carry out a generally applicable theory to explain the emergence of optimal pinning and to predict the dependence of the optimal pinning fraction on the network topology. Our work represents a general framework to deal with the broader problem of controlling collective dynamics in complex systems with potential applications in social, economical and political systems.

An Optimization of Manufacturing Systems using a Feedback Control Scheduling Model

NASA Astrophysics Data System (ADS)

Ikome, John M.; Kanakana, Grace M.

2018-03-01

In complex production system that involves multiple process, unplanned disruption often turn to make the entire production system vulnerable to a number of problems which leads to customer’s dissatisfaction. However, this problem has been an ongoing problem that requires a research and methods to streamline the entire process or develop a model that will address it, in contrast to this, we have developed a feedback scheduling model that can minimize some of this problem and after a number of experiment, it shows that some of this problems can be eliminated if the correct remedial actions are implemented on time.

Restart Operator Meta-heuristics for a Problem-Oriented Evolutionary Strategies Algorithm in Inverse Mathematical MISO Modelling Problem Solving

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.

2017-02-01

This study is focused on solving an inverse mathematical modelling problem for dynamical systems based on observation data and control inputs. The mathematical model is being searched in the form of a linear differential equation, which determines the system with multiple inputs and a single output, and a vector of the initial point coordinates. The described problem is complex and multimodal and for this reason the proposed evolutionary-based optimization technique, which is oriented on a dynamical system identification problem, was applied. To improve its performance an algorithm restart operator was implemented.

The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems

PubMed Central

Baars, Martine; Wijnia, Lisette; Paas, Fred

2017-01-01

Self-regulated learning (SRL) skills are essential for learning during school years, particularly in complex problem-solving domains, such as biology and math. Although a lot of studies have focused on the cognitive resources that are needed for learning to solve problems in a self-regulated way, affective and motivational resources have received much less research attention. The current study investigated the relation between affect (i.e., Positive Affect and Negative Affect Scale), motivation (i.e., autonomous and controlled motivation), mental effort, SRL skills, and problem-solving performance when learning to solve biology problems in a self-regulated online learning environment. In the learning phase, secondary education students studied video-modeling examples of how to solve hereditary problems, solved hereditary problems which they chose themselves from a set of problems with different complexity levels (i.e., five levels). In the posttest, students solved hereditary problems, self-assessed their performance, and chose a next problem from the set of problems but did not solve these problems. The results from this study showed that negative affect, inaccurate self-assessments during the posttest, and higher perceptions of mental effort during the posttest were negatively associated with problem-solving performance after learning in a self-regulated way. PMID:28848467

An Improved Memetic Algorithm for Break Scheduling

NASA Astrophysics Data System (ADS)

Widl, Magdalena; Musliu, Nysret

In this paper we consider solving a complex real life break scheduling problem. This problem of high practical relevance arises in many working areas, e.g. in air traffic control and other fields where supervision personnel is working. The objective is to assign breaks to employees such that various constraints reflecting legal demands or ergonomic criteria are satisfied and staffing requirement violations are minimised.

ESP Teaching at the Institutions of Higher Education in Modern Russia: Problems and Perspectives

ERIC Educational Resources Information Center

Prudnikova, Nadezhda

2013-01-01

The author analyses ESP teaching at the institutions of higher education in modern Russia, explains the main problems and suggests the ways of their solving, details the quality control system of the students' progress improvement, presents the complex approach to interactive ESP teaching and views it as an integral part of up-to-date…

Theoretical Foundations of Software Technology.

DTIC Science & Technology

1983-02-14

major research interests are software testing, aritificial intelligence , pattern recogu- tion, and computer graphics. Dr. Chandranekaran is currently...produce PASCAL language code for the problems. Because of its relationship to many issues in Artificial Intelligence , we also investigated problems of...analysis to concurmt-prmcess software re- are not " intelligent " enough to discover these by themselves, ouirl more complex control flow models. The PAF

The effects of maternal working conditions and mastery on child behavior problems: studying the intergenerational transmission of social control.

PubMed

Rogers, S J; Parcel, T L; Menaghan, E G

1991-06-01

We assess the impact of maternal sense of mastery and maternal working conditions on maternal perceptions of children's behavior problems as a means to study the transmission of social control across generations. We use a sample of 521 employed mothers and their four-to six-year-old children from the National Longitudinal Survey's Youth Cohort in 1986. Regarding working conditions, we consider mother's hourly wage, work hours, and job content including involvement with things (vs. people), the requisite level of physical activity, and occupational complexity. We also consider maternal and child background and current family characteristics, including marital status, family size, and home environment. Maternal mastery was related to fewer reported behavior problems among children. Lower involvement with people and higher involvement with things, as well as low physical activity, were related significantly to higher levels of perceived problems. In addition, recent changes in maternal marital status, including maternal marriage or remarriage, increased reports of problems; stronger home environments had the opposite effect. We interpret these findings as suggesting how maternal experiences of control in the workplace and personal resources of control can influence the internalization of control in children.

Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft

NASA Astrophysics Data System (ADS)

Wu, Chao; Yang, Jun; Li, Shihua; Li, Qi; Guo, Lei

2018-05-01

Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8 km parachute deployment point distribution error) than the baseline control scheme (8.4 km) and integral control scheme (5.8 km).

Controllability of Deterministic Networks with the Identical Degree Sequence

PubMed Central

Ma, Xiujuan; Zhao, Haixing; Wang, Binghong

2015-01-01

Controlling complex network is an essential problem in network science and engineering. Recent advances indicate that the controllability of complex network is dependent on the network's topology. Liu and Barabási, et.al speculated that the degree distribution was one of the most important factors affecting controllability for arbitrary complex directed network with random link weights. In this paper, we analysed the effect of degree distribution to the controllability for the deterministic networks with unweighted and undirected. We introduce a class of deterministic networks with identical degree sequence, called (x,y)-flower. We analysed controllability of the two deterministic networks ((1, 3)-flower and (2, 2)-flower) by exact controllability theory in detail and give accurate results of the minimum number of driver nodes for the two networks. In simulation, we compare the controllability of (x,y)-flower networks. Our results show that the family of (x,y)-flower networks have the same degree sequence, but their controllability is totally different. So the degree distribution itself is not sufficient to characterize the controllability of deterministic networks with unweighted and undirected. PMID:26020920

Living with faecal incontinence: trying to control the daily life that is out of control.

PubMed

Olsson, Frida; Berterö, Carina

2015-01-01

To identify and describe the lived experience of persons living with faecal incontinence and show how it affects daily life. Faecal incontinence is a relatively common condition, with a prevalence ranging from 3-24%, not differing between men and women. There is an under-reporting due to patients' reluctance to talk about their symptoms and consult healthcare professionals about their problems, which means that problems related to faecal incontinence are often underestimated. Living with faecal incontinence affects the quality of life negatively and has a negative impact on family situations, social interaction, etc. A qualitative interpretative study based on interviews. In-depth interviews were conducted with five informants, all women, living with faecal incontinence. The interviews were transcribed verbatim and analysed using interpretive phenomenological analysis. The analysis identified four themes: self-affirmation, guilt and shame, limitations in life and personal approach. The themes differ from each other, but are related and have similarities. The results show different aspects of living with faecal incontinence and how they affected daily life. Living with faecal incontinence is a complex problem affecting everyday life in a number of different ways. It is a highly distressing and socially incapacitating problem. Living with faecal incontinence is about trying to control the daily life which is out of control. Living with faecal incontinence cannot be generalised as individuals experience the situation in unique ways. By gaining insight into the experience of living with faecal incontinence, healthcare professionals can deepen their understanding of this complex problem and thereby better address it and provide more individually based care. © 2014 John Wiley & Sons Ltd.

Dynamic analysis of space structures including elastic, multibody, and control behavior

NASA Technical Reports Server (NTRS)

Pinson, Larry; Soosaar, Keto

1989-01-01

The problem is to develop analysis methods, modeling stategies, and simulation tools to predict with assurance the on-orbit performance and integrity of large complex space structures that cannot be verified on the ground. The problem must incorporate large reliable structural models, multi-body flexible dynamics, multi-tier controller interaction, environmental models including 1g and atmosphere, various on-board disturbances, and linkage to mission-level performance codes. All areas are in serious need of work, but the weakest link is multi-body flexible dynamics.

A Framework for Optimal Control Allocation with Structural Load Constraints

NASA Technical Reports Server (NTRS)

Frost, Susan A.; Taylor, Brian R.; Jutte, Christine V.; Burken, John J.; Trinh, Khanh V.; Bodson, Marc

2010-01-01

Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.

Mental Health Problems in Children with Prader-Willi Syndrome

PubMed Central

Skokauskas, Norbert; Sweeny, Eileen; Meehan, Judith; Gallagher, Louise

2012-01-01

Background: Prader-Willi Syndrome (PWS) is a genetically determined neurodevelopmental disorder, which occurs in approximately one in 22000 births. Aims: This study aimed to investigate psychiatric characteristics of children diagnosed with PWS compared with an age-, gender- and IQ-matched control group. The parents of children with PWS were assessed for psychological distress in comparison to the parents of the control group. Methodological limitations identified in previous studies were addressed in the present study. Methods: Psychiatric problems were evaluated in a sample of children with genetically confirmed PWS and an age- and IQ-matched control group using the Child Behaviour Checklist 6–18. Parental psychological distress for both groups was evaluated with the Brief Symptom Inventory. Results: Children with PWS had more severe somatic, social, and thought problems, and were more withdrawn-depressed in comparison to controls. Borderline difficulties were detected for the affective, somatic, and attention deficit-hyperactivity CBCL DSM-orientated subscales in the PWS group. Parents of PWS children, in comparison to controls, had more somatization, phobic anxiety, obsessive-compulsive, and anxiety problems. Conclusions: PWS represents a complex psychological disorder with multiple areas of disturbances. PMID:22876265

Control and instanton trajectories for random transitions in turbulent flows

NASA Astrophysics Data System (ADS)

Bouchet, Freddy; Laurie, Jason; Zaboronski, Oleg

2011-12-01

Many turbulent systems exhibit random switches between qualitatively different attractors. The transition between these bistable states is often an extremely rare event, that can not be computed through DNS, due to complexity limitations. We present results for the calculation of instanton trajectories (a control problem) between non-equilibrium stationary states (attractors) in the 2D stochastic Navier-Stokes equations. By representing the transition probability between two states using a path integral formulation, we can compute the most probable trajectory (instanton) joining two non-equilibrium stationary states. Technically, this is equivalent to the minimization of an action, which can be related to a fluid mechanics control problem.

Chemistry, manufacturing and controls in passive transdermal drug delivery systems.

PubMed

Goswami, Tarun; Audett, Jay

2015-01-01

Transdermal drug delivery systems (TDDS) are used for the delivery of the drugs through the skin into the systemic circulation by applying them to the intact skin. The development of TDDS is a complex and multidisciplinary affair which involves identification of suitable drug, excipients and various other components. There have been numerous problems reported with respect to TDDS quality and performance. These problems can be reduced by appropriately addressing chemistry, manufacturing and controls requirements, which would thereby result in development of robust TDDS product and processes. This article provides recommendations on the chemistry, manufacturing and controls focusing on the unique technical aspects of TDDS.

Self-organized adaptation of a simple neural circuit enables complex robot behaviour

NASA Astrophysics Data System (ADS)

Steingrube, Silke; Timme, Marc; Wörgötter, Florentin; Manoonpong, Poramate

2010-03-01

Controlling sensori-motor systems in higher animals or complex robots is a challenging combinatorial problem, because many sensory signals need to be simultaneously coordinated into a broad behavioural spectrum. To rapidly interact with the environment, this control needs to be fast and adaptive. Present robotic solutions operate with limited autonomy and are mostly restricted to few behavioural patterns. Here we introduce chaos control as a new strategy to generate complex behaviour of an autonomous robot. In the presented system, 18 sensors drive 18 motors by means of a simple neural control circuit, thereby generating 11 basic behavioural patterns (for example, orienting, taxis, self-protection and various gaits) and their combinations. The control signal quickly and reversibly adapts to new situations and also enables learning and synaptic long-term storage of behaviourally useful motor responses. Thus, such neural control provides a powerful yet simple way to self-organize versatile behaviours in autonomous agents with many degrees of freedom.

A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems

NASA Astrophysics Data System (ADS)

Chen, Jung-Chieh

This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i. e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.

Autonomous control systems: applications to remote sensing and image processing

NASA Astrophysics Data System (ADS)

Jamshidi, Mohammad

2001-11-01

One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.

Cybersecurity vulnerabilities in medical devices: a complex environment and multifaceted problem

PubMed Central

Williams, Patricia AH; Woodward, Andrew J

2015-01-01

The increased connectivity to existing computer networks has exposed medical devices to cybersecurity vulnerabilities from which they were previously shielded. For the prevention of cybersecurity incidents, it is important to recognize the complexity of the operational environment as well as to catalog the technical vulnerabilities. Cybersecurity protection is not just a technical issue; it is a richer and more intricate problem to solve. A review of the factors that contribute to such a potentially insecure environment, together with the identification of the vulnerabilities, is important for understanding why these vulnerabilities persist and what the solution space should look like. This multifaceted problem must be viewed from a systemic perspective if adequate protection is to be put in place and patient safety concerns addressed. This requires technical controls, governance, resilience measures, consolidated reporting, context expertise, regulation, and standards. It is evident that a coordinated, proactive approach to address this complex challenge is essential. In the interim, patient safety is under threat. PMID:26229513

Cybersecurity vulnerabilities in medical devices: a complex environment and multifaceted problem.

PubMed

Williams, Patricia Ah; Woodward, Andrew J

2015-01-01

The increased connectivity to existing computer networks has exposed medical devices to cybersecurity vulnerabilities from which they were previously shielded. For the prevention of cybersecurity incidents, it is important to recognize the complexity of the operational environment as well as to catalog the technical vulnerabilities. Cybersecurity protection is not just a technical issue; it is a richer and more intricate problem to solve. A review of the factors that contribute to such a potentially insecure environment, together with the identification of the vulnerabilities, is important for understanding why these vulnerabilities persist and what the solution space should look like. This multifaceted problem must be viewed from a systemic perspective if adequate protection is to be put in place and patient safety concerns addressed. This requires technical controls, governance, resilience measures, consolidated reporting, context expertise, regulation, and standards. It is evident that a coordinated, proactive approach to address this complex challenge is essential. In the interim, patient safety is under threat.

Creativity: Creativity in Complex Military Systems

DTIC Science & Technology

2017-05-25

generation later in the problem-solving process. The design process is an alternative problem-solving framework individuals or groups use to orient...no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control ...the potential of their formations. 15. SUBJECT TERMS Creativity, Divergent Thinking, Design , Systems Thinking, Operational Art 16. SECURITY

Improving multi-objective reservoir operation optimization with sensitivity-informed problem decomposition

NASA Astrophysics Data System (ADS)

Chu, J. G.; Zhang, C.; Fu, G. T.; Li, Y.; Zhou, H. C.

2015-04-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce the computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed problem decomposition dramatically reduces the computational demands required for attaining high quality approximations of optimal tradeoff relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed problem decomposition and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform problem decomposition when solving the complex multi-objective reservoir operation problems.

Synchronization of fractional-order complex-valued neural networks with time delay.

PubMed

Bao, Haibo; Park, Ju H; Cao, Jinde

2016-09-01

This paper deals with the problem of synchronization of fractional-order complex-valued neural networks with time delays. By means of linear delay feedback control and a fractional-order inequality, sufficient conditions are obtained to guarantee the synchronization of the drive-response systems. Numerical simulations are provided to show the effectiveness of the obtained results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Looking at Leadership: Some Neglected Issues

DTIC Science & Technology

1977-10-01

problems. (3) Use of power Using social skills, rewards and punishments to control organizational events. A way to study leaders is to simulate the...conditions managers face. Simulation paradigms allow detailed ex- amination of the complex forces impacting on organizations from without and within...modifying the impacts of other variables. Given this horrendous complexity, it is no surprise that Vaill (in press) has questioned whether it makes much

A computer program to trace seismic ray distribution in complex two-dimensional geological models

USGS Publications Warehouse

Yacoub, Nazieh K.; Scott, James H.

1970-01-01

A computer program has been developed to trace seismic rays and their amplitudes and energies through complex two-dimensional geological models, for which boundaries between elastic units are defined by a series of digitized X-, Y-coordinate values. Input data for the program includes problem identification, control parameters, model coordinates and elastic parameter for the elastic units. The program evaluates the partitioning of ray amplitude and energy at elastic boundaries, computes the total travel time, total travel distance and other parameters for rays arising at the earth's surface. Instructions are given for punching program control cards and data cards, and for arranging input card decks. An example of printer output for a simple problem is presented. The program is written in FORTRAN IV language. The listing of the program is shown in the Appendix, with an example output from a CDC-6600 computer.

Method for Evaluating Information to Solve Problems of Control, Monitoring and Diagnostics

NASA Astrophysics Data System (ADS)

Vasil'ev, V. A.; Dobrynina, N. V.

2017-06-01

The article describes a method for evaluating information to solve problems of control, monitoring and diagnostics. It is necessary for reducing the dimensionality of informational indicators of situations, bringing them to relative units, for calculating generalized information indicators on their basis, ranking them by characteristic levels, for calculating the efficiency criterion of a system functioning in real time. The design of information evaluation system has been developed on its basis that allows analyzing, processing and assessing information about the object. Such object can be a complex technical, economic and social system. The method and the based system thereof can find a wide application in the field of analysis, processing and evaluation of information on the functioning of the systems, regardless of their purpose, goals, tasks and complexity. For example, they can be used to assess the innovation capacities of industrial enterprises and management decisions.

Robustness of linear quadratic state feedback designs in the presence of system uncertainty. [application to Augmentor Wing Jet STOL Research Aircraft flare control autopilot design

NASA Technical Reports Server (NTRS)

Patel, R. V.; Toda, M.; Sridhar, B.

1977-01-01

The paper deals with the problem of expressing the robustness (stability) property of a linear quadratic state feedback (LQSF) design quantitatively in terms of bounds on the perturbations (modeling errors or parameter variations) in the system matrices so that the closed-loop system remains stable. Nonlinear time-varying and linear time-invariant perturbations are considered. The only computation required in obtaining a measure of the robustness of an LQSF design is to determine the eigenvalues of two symmetric matrices determined when solving the algebraic Riccati equation corresponding to the LQSF design problem. Results are applied to a complex dynamic system consisting of the flare control of a STOL aircraft. The design of the flare control is formulated as an LQSF tracking problem.

Hybrid near-optimal aeroassisted orbit transfer plane change trajectories

NASA Technical Reports Server (NTRS)

Calise, Anthony J.; Duckeman, Gregory A.

1994-01-01

In this paper, a hybrid methodology is used to determine optimal open loop controls for the atmospheric portion of the aeroassisted plane change problem. The method is hybrid in the sense that it combines the features of numerical collocation with the analytically tractable portions of the problem which result when the two-point boundary value problem is cast in the form of a regular perturbation problem. Various levels of approximation are introduced by eliminating particular collocation parameters and their effect upon problem complexity and required number of nodes is discussed. The results include plane changes of 10, 20, and 30 degrees for a given vehicle.

Control optimization of a lifting body entry problem by an improved and a modified method of perturbation function. Ph.D. Thesis - Houston Univ.

NASA Technical Reports Server (NTRS)

Garcia, F., Jr.

1974-01-01

A study of the solution problem of a complex entry optimization was studied. The problem was transformed into a two-point boundary value problem by using classical calculus of variation methods. Two perturbation methods were devised. These methods attempted to desensitize the contingency of the solution of this type of problem on the required initial co-state estimates. Also numerical results are presented for the optimal solution resulting from a number of different initial co-states estimates. The perturbation methods were compared. It is found that they are an improvement over existing methods.

Inhibitory Control, but Not Prolonged Object-Related Experience Appears to Affect Physical Problem-Solving Performance of Pet Dogs.

PubMed

Müller, Corsin A; Riemer, Stefanie; Virányi, Zsófia; Huber, Ludwig; Range, Friederike

2016-01-01

Human infants develop an understanding of their physical environment through playful interactions with objects. Similar processes may influence also the performance of non-human animals in physical problem-solving tasks, but to date there is little empirical data to evaluate this hypothesis. In addition or alternatively to prior experiences, inhibitory control has been suggested as a factor underlying the considerable individual differences in performance reported for many species. Here we report a study in which we manipulated the extent of object-related experience for a cohort of dogs (Canis familiaris) of the breed Border Collie over a period of 18 months, and assessed their level of inhibitory control, prior to testing them in a series of four physical problem-solving tasks. We found no evidence that differences in object-related experience explain variability in performance in these tasks. It thus appears that dogs do not transfer knowledge about physical rules from one physical problem-solving task to another, but rather approach each task as a novel problem. Our results, however, suggest that individual performance in these tasks is influenced in a complex way by the subject's level of inhibitory control. Depending on the task, inhibitory control had a positive or a negative effect on performance and different aspects of inhibitory control turned out to be the best predictors of individual performance in the different tasks. Therefore, studying the interplay between inhibitory control and problem-solving performance will make an important contribution to our understanding of individual and species differences in physical problem-solving performance.

Inhibitory Control, but Not Prolonged Object-Related Experience Appears to Affect Physical Problem-Solving Performance of Pet Dogs

PubMed Central

Müller, Corsin A.; Riemer, Stefanie; Virányi, Zsófia; Huber, Ludwig; Range, Friederike

2016-01-01

Human infants develop an understanding of their physical environment through playful interactions with objects. Similar processes may influence also the performance of non-human animals in physical problem-solving tasks, but to date there is little empirical data to evaluate this hypothesis. In addition or alternatively to prior experiences, inhibitory control has been suggested as a factor underlying the considerable individual differences in performance reported for many species. Here we report a study in which we manipulated the extent of object-related experience for a cohort of dogs (Canis familiaris) of the breed Border Collie over a period of 18 months, and assessed their level of inhibitory control, prior to testing them in a series of four physical problem-solving tasks. We found no evidence that differences in object-related experience explain variability in performance in these tasks. It thus appears that dogs do not transfer knowledge about physical rules from one physical problem-solving task to another, but rather approach each task as a novel problem. Our results, however, suggest that individual performance in these tasks is influenced in a complex way by the subject’s level of inhibitory control. Depending on the task, inhibitory control had a positive or a negative effect on performance and different aspects of inhibitory control turned out to be the best predictors of individual performance in the different tasks. Therefore, studying the interplay between inhibitory control and problem-solving performance will make an important contribution to our understanding of individual and species differences in physical problem-solving performance. PMID:26863141

Equicontrollability and its application to model-following and decoupling.

NASA Technical Reports Server (NTRS)

Curran, R. T.

1971-01-01

Discussion of 'model following,' a term used to describe a class of problems characterized by having two dynamic systems, generically known as the 'plant' and the 'model,' it being required to find a controller to attach to the plant so as to make the resultant compensated system behave, in an input/output sense, in the same way as the model. The approach presented to the problem takes a structural point of view. The result is a complex but informative definition which solves the problem as posed. The application of both the algorithm and its basis, equicontrollability, to the decoupling problem is considered.

Matching of energetic, mechanic and control characteristics of positioning actuator

NASA Astrophysics Data System (ADS)

Y Nosova, N.; Misyurin, S. Yu; Kreinin, G. V.

2017-12-01

The problem of preliminary choice of parameters of the automated drive power channel is discussed. The drive of the mechatronic complex divides into two main units - power and control. The first determines the energy capabilities and, as a rule, the overall dimensions of the complex. The sufficient capacity of the power unit is a necessary condition for successful solution of control tasks without excessive complication of the control system structure. Preliminary selection of parameters is carried out based on the condition of providing the necessary drive power. The proposed approach is based on: a research of a sufficiently developed but not excessive dynamic model of the power block with the help of a conditional test control system; a transition to a normalized model with the formation of similarity criteria; constructing the synthesis procedure.

Decentralized control of large flexible structures by joint decoupling

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Juang, Jer-Nan

1994-01-01

This paper presents a novel method to design decentralized controllers for large complex flexible structures by using the idea of joint decoupling. Decoupling of joint degrees of freedom from the interior degrees of freedom is achieved by setting the joint actuator commands to cancel the internal forces exerting on the joint degrees of freedom. By doing so, the interactions between substructures are eliminated. The global structure control design problem is then decomposed into several substructure control design problems. Control commands for interior actuators are set to be localized state feedback using decentralized observers for state estimation. The proposed decentralized controllers can operate successfully at the individual substructure level as well as at the global structure level. Not only control design but also control implementation is decentralized. A two-component mass-spring-damper system is used as an example to demonstrate the proposed method.

Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics

NASA Astrophysics Data System (ADS)

Puzyrkov, Dmitry; Polyakov, Sergey; Podryga, Viktoriia; Markizov, Sergey

2018-02-01

At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.

Combining fuzzy mathematics with fuzzy logic to solve business management problems

NASA Astrophysics Data System (ADS)

Vrba, Joseph A.

1993-12-01

Fuzzy logic technology has been applied to control problems with great success. Because of this, many observers fell that fuzzy logic is applicable only in the control arena. However, business management problems almost never deal with crisp values. Fuzzy systems technology--a combination of fuzzy logic, fuzzy mathematics and a graphical user interface--is a natural fit for developing software to assist in typical business activities such as planning, modeling and estimating. This presentation discusses how fuzzy logic systems can be extended through the application of fuzzy mathematics and the use of a graphical user interface to make the information contained in fuzzy numbers accessible to business managers. As demonstrated through examples from actual deployed systems, this fuzzy systems technology has been employed successfully to provide solutions to the complex real-world problems found in the business environment.

Evolutionary Computation with Spatial Receding Horizon Control to Minimize Network Coding Resources

PubMed Central

Leeson, Mark S.

2014-01-01

The minimization of network coding resources, such as coding nodes and links, is a challenging task, not only because it is a NP-hard problem, but also because the problem scale is huge; for example, networks in real world may have thousands or even millions of nodes and links. Genetic algorithms (GAs) have a good potential of resolving NP-hard problems like the network coding problem (NCP), but as a population-based algorithm, serious scalability and applicability problems are often confronted when GAs are applied to large- or huge-scale systems. Inspired by the temporal receding horizon control in control engineering, this paper proposes a novel spatial receding horizon control (SRHC) strategy as a network partitioning technology, and then designs an efficient GA to tackle the NCP. Traditional network partitioning methods can be viewed as a special case of the proposed SRHC, that is, one-step-wide SRHC, whilst the method in this paper is a generalized N-step-wide SRHC, which can make a better use of global information of network topologies. Besides the SRHC strategy, some useful designs are also reported in this paper. The advantages of the proposed SRHC and GA for the NCP are illustrated by extensive experiments, and they have a good potential of being extended to other large-scale complex problems. PMID:24883371

Advanced computer architecture for large-scale real-time applications.

DOT National Transportation Integrated Search

1973-04-01

Air traffic control automation is identified as a crucial problem which provides a complex, real-time computer application environment. A novel computer architecture in the form of a pipeline associative processor is conceived to achieve greater perf...

Demonstration of a tool for automatic learning and re-use of knowledge in the activated sludge process.

PubMed

Comas, J; Rodríguez-Roda, I; Poch, M; Gernaey, K V; Rosen, C; Jeppsson, U

2006-01-01

Wastewater treatment plant operators encounter complex operational problems related to the activated sludge process and usually respond to these by applying their own intuition and by taking advantage of what they have learnt from past experiences of similar problems. However, previous process experiences are not easy to integrate in numerical control, and new tools must be developed to enable re-use of plant operating experience. The aim of this paper is to investigate the usefulness of a case-based reasoning (CBR) approach to apply learning and re-use of knowledge gained during past incidents to confront actual complex problems through the IWA/COST Benchmark protocol. A case study shows that the proposed CBR system achieves a significant improvement of the benchmark plant performance when facing a high-flow event disturbance.

Flight-deck automation - Promises and problems

NASA Technical Reports Server (NTRS)

Wiener, E. L.; Curry, R. E.

1980-01-01

The paper analyzes the role of human factors in flight-deck automation, identifies problem areas, and suggests design guidelines. Flight-deck automation using microprocessor technology and display systems improves performance and safety while leading to a decrease in size, cost, and power consumption. On the other hand negative factors such as failure of automatic equipment, automation-induced error compounded by crew error, crew error in equipment set-up, failure to heed automatic alarms, and loss of proficiency must also be taken into account. Among the problem areas discussed are automation of control tasks, monitoring of complex systems, psychosocial aspects of automation, and alerting and warning systems. Guidelines are suggested for designing, utilising, and improving control and monitoring systems. Investigation into flight-deck automation systems is important as the knowledge gained can be applied to other systems such as air traffic control and nuclear power generation, but the many problems encountered with automated systems need to be analyzed and overcome in future research.

Efficient Pricing Technique for Resource Allocation Problem in Downlink OFDM Cognitive Radio Networks

NASA Astrophysics Data System (ADS)

Abdulghafoor, O. B.; Shaat, M. M. R.; Ismail, M.; Nordin, R.; Yuwono, T.; Alwahedy, O. N. A.

2017-05-01

In this paper, the problem of resource allocation in OFDM-based downlink cognitive radio (CR) networks has been proposed. The purpose of this research is to decrease the computational complexity of the resource allocation algorithm for downlink CR network while concerning the interference constraint of primary network. The objective has been secured by adopting pricing scheme to develop power allocation algorithm with the following concerns: (i) reducing the complexity of the proposed algorithm and (ii) providing firm power control to the interference introduced to primary users (PUs). The performance of the proposed algorithm is tested for OFDM- CRNs. The simulation results show that the performance of the proposed algorithm approached the performance of the optimal algorithm at a lower computational complexity, i.e., O(NlogN), which makes the proposed algorithm suitable for more practical applications.

Promoting Experimental Problem-solving Ability in Sixth-grade Students Through Problem-oriented Teaching of Ecology: Findings of an intervention study in a complex domain

NASA Astrophysics Data System (ADS)

Roesch, Frank; Nerb, Josef; Riess, Werner

2015-03-01

Our study investigated whether problem-oriented designed ecology lessons with phases of direct instruction and of open experimentation foster the development of cross-domain and domain-specific components of experimental problem-solving ability better than conventional lessons in science. We used a paper-and-pencil test to assess students' abilities in a quasi-experimental intervention study utilizing a pretest/posttest control-group design (N = 340; average performing sixth-grade students). The treatment group received lessons on forest ecosystems consistent with the principle of education for sustainable development. This learning environment was expected to help students enhance their ecological knowledge and their theoretical and methodological experimental competencies. Two control groups received either the teachers' usual lessons on forest ecosystems or non-specific lessons on other science topics. We found that the treatment promoted specific components of experimental problem-solving ability (generating epistemic questions, planning two-factorial experiments, and identifying correct experimental controls). However, the observed effects were small, and awareness for aspects of higher ecological experimental validity was not promoted by the treatment.

Interference elimination in digital controllers of automation systems of oil and gas complex

NASA Astrophysics Data System (ADS)

Solomentsev, K. Yu; Fugarov, D. D.; Purchina, O. A.; Poluyan, A. Y.; Nesterchuk, V. V.; Petrenkova, S. B.

2018-05-01

The given article considers the problems arising in the process of digital governors development for the systems of automatic control. In the case of interference, and also in case of high frequency of digitization, digital differentiation gives a big error. The problem is that the derivative is calculated as the difference of two close variables. The method of differentiation is offered to reduce this error, when there is a case of averaging the difference quotient of the series of meanings. The structure chart for the implementation of this differentiation method is offered in the case of governors construction.

Designing Adaptive Low Dissipative High Order Schemes

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sjoegreen, B.; Parks, John W. (Technical Monitor)

2002-01-01

Proper control of the numerical dissipation/filter to accurately resolve all relevant multiscales of complex flow problems while still maintaining nonlinear stability and efficiency for long-time numerical integrations poses a great challenge to the design of numerical methods. The required type and amount of numerical dissipation/filter are not only physical problem dependent, but also vary from one flow region to another. This is particularly true for unsteady high-speed shock/shear/boundary-layer/turbulence/acoustics interactions and/or combustion problems since the dynamics of the nonlinear effect of these flows are not well-understood. Even with extensive grid refinement, it is of paramount importance to have proper control on the type and amount of numerical dissipation/filter in regions where it is needed.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

NASA Astrophysics Data System (ADS)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

Virtual Control Policy for Binary Ordered Resources Petri Net Class.

PubMed

Rovetto, Carlos A; Concepción, Tomás J; Cano, Elia Esther

2016-08-18

Prevention and avoidance of deadlocks in sensor networks that use the wormhole routing algorithm is an active research domain. There are diverse control policies that will address this problem being our approach a new method. In this paper we present a virtual control policy for the new specialized Petri net subclass called Binary Ordered Resources Petri Net (BORPN). Essentially, it is an ordinary class constructed from various state machines that share unitary resources in a complex form, which allows branching and joining of processes. The reduced structure of this new class gives advantages that allow analysis of the entire system's behavior, which is a prohibitive task for large systems because of the complexity and routing algorithms.

Complexity, information loss, and model building: from neuro- to cognitive dynamics

NASA Astrophysics Data System (ADS)

Arecchi, F. Tito

2007-06-01

A scientific problem described within a given code is mapped by a corresponding computational problem, We call complexity (algorithmic) the bit length of the shortest instruction which solves the problem. Deterministic chaos in general affects a dynamical systems making the corresponding problem experimentally and computationally heavy, since one must reset the initial conditions at a rate higher than that of information loss (Kolmogorov entropy). One can control chaos by adding to the system new degrees of freedom (information swapping: information lost by chaos is replaced by that arising from the new degrees of freedom). This implies a change of code, or a new augmented model. Within a single code, changing hypotheses is equivalent to fixing different sets of control parameters, each with a different a-priori probability, to be then confirmed and transformed to an a-posteriori probability via Bayes theorem. Sequential application of Bayes rule is nothing else than the Darwinian strategy in evolutionary biology. The sequence is a steepest ascent algorithm, which stops once maximum probability has been reached. At this point the hypothesis exploration stops. By changing code (and hence the set of relevant variables) one can start again to formulate new classes of hypotheses . We call semantic complexity the number of accessible scientific codes, or models, that describe a situation. It is however a fuzzy concept, in so far as this number changes due to interaction of the operator with the system under investigation. These considerations are illustrated with reference to a cognitive task, starting from synchronization of neuron arrays in a perceptual area and tracing the putative path toward a model building.

Problems of Automation and Management Principles Information Flow in Manufacturing

NASA Astrophysics Data System (ADS)

Grigoryuk, E. N.; Bulkin, V. V.

2017-07-01

Automated control systems of technological processes are complex systems that are characterized by the presence of elements of the overall focus, the systemic nature of the implemented algorithms for the exchange and processing of information, as well as a large number of functional subsystems. The article gives examples of automatic control systems and automated control systems of technological processes held parallel between them by identifying strengths and weaknesses. Other proposed non-standard control system of technological process.

Performance of subjects with and without severe mental illness on a clinical test of problem solving.

PubMed

Marshall, R C; McGurk, S R; Karow, C M; Kairy, T J; Flashman, L A

2006-06-01

Severe mental illness is associated with impairments in executive functions, such as conceptual reasoning, planning, and strategic thinking all of which impact problem solving. The present study examined the utility of a novel assessment tool for problem solving, the Rapid Assessment of Problem Solving Test (RAPS) in persons with severe mental illness. Subjects were 47 outpatients with severe mental illness and an equal number healthy controls matched for age and gender. Results confirmed all hypotheses with respect to how subjects with severe mental illness would perform on the RAPS. Specifically, the severely mentally ill subjects (1) solved fewer problems on the RAPS, (2) when they did solve problems on the test, they did so far less efficiently than their healthy counterparts, and (3) the two groups differed markedly in the types of questions asked on the RAPS. The healthy control subjects tended to take a systematic, organized, but not always optimal approach to solving problems on the RAPS. The subjects with severe mental illness used some of the problem solving strategies of the healthy controls, but their performance was less consistent and tended to deteriorate when the complexity of the problem solving task increased. This was reflected by a high degree of guessing in lieu of asking constraint questions, particularly if a category-limited question was insufficient to continue the problem solving effort.

Multimodal Perception and Multicriterion Control of Nested Systems. 1; Coordination of Postural Control and Vehicular Control

NASA Technical Reports Server (NTRS)

Riccio, Gary E.; McDonald, P. Vernon

1998-01-01

The purpose of this report is to identify the essential characteristics of goal-directed whole-body motion. The report is organized into three major sections (Sections 2, 3, and 4). Section 2 reviews general themes from ecological psychology and control-systems engineering that are relevant to the perception and control of whole-body motion. These themes provide an organizational framework for analyzing the complex and interrelated phenomena that are the defining characteristics of whole-body motion. Section 3 of this report applies the organization framework from the first section to the problem of perception and control of aircraft motion. This is a familiar problem in control-systems engineering and ecological psychology. Section 4 examines an essential but generally neglected aspect of vehicular control: coordination of postural control and vehicular control. To facilitate presentation of this new idea, postural control and its coordination with vehicular control are analyzed in terms of conceptual categories that are familiar in the analysis of vehicular control.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alvarez-Ramirez, J.; Aguilar, R.; Lopez-Isunza, F.

FCC processes involve complex interactive dynamics which are difficult to operate and control as well as poorly known reaction kinetics. This work concerns the synthesis of temperature controllers for FCC units. The problem is addressed first for the case where perfect knowledge of the reaction kinetics is assumed, leading to an input-output linearizing state feedback. However, in most industrial FCC units, perfect knowledge of reaction kinetics and composition measurements is not available. To address the problem of robustness against uncertainties in the reaction kinetics, an adaptive model-based nonlinear controller with simplified reaction models is presented. The adaptive strategy makes usemore » of estimates of uncertainties derived from calorimetric (energy) balances. The resulting controller is similar in form to standard input-output linearizing controllers and can be tuned analogously. Alternatively, the controller can be tuned using a single gain parameter and is computationally efficient. The performance of the closed-loop system and the controller design procedure are shown with simulations.« less

Minimizing communication cost among distributed controllers in software defined networks

NASA Astrophysics Data System (ADS)

Arlimatti, Shivaleela; Elbreiki, Walid; Hassan, Suhaidi; Habbal, Adib; Elshaikh, Mohamed

2016-08-01

Software Defined Networking (SDN) is a new paradigm to increase the flexibility of today's network by promising for a programmable network. The fundamental idea behind this new architecture is to simplify network complexity by decoupling control plane and data plane of the network devices, and by making the control plane centralized. Recently controllers have distributed to solve the problem of single point of failure, and to increase scalability and flexibility during workload distribution. Even though, controllers are flexible and scalable to accommodate more number of network switches, yet the problem of intercommunication cost between distributed controllers is still challenging issue in the Software Defined Network environment. This paper, aims to fill the gap by proposing a new mechanism, which minimizes intercommunication cost with graph partitioning algorithm, an NP hard problem. The methodology proposed in this paper is, swapping of network elements between controller domains to minimize communication cost by calculating communication gain. The swapping of elements minimizes inter and intra communication cost among network domains. We validate our work with the OMNeT++ simulation environment tool. Simulation results show that the proposed mechanism minimizes the inter domain communication cost among controllers compared to traditional distributed controllers.

Input-output oriented computation algorithms for the control of large flexible structures

NASA Technical Reports Server (NTRS)

Minto, K. D.

1989-01-01

An overview is given of work in progress aimed at developing computational algorithms addressing two important aspects in the control of large flexible space structures; namely, the selection and placement of sensors and actuators, and the resulting multivariable control law design problem. The issue of sensor/actuator set selection is particularly crucial to obtaining a satisfactory control design, as clearly a poor choice will inherently limit the degree to which good control can be achieved. With regard to control law design, the researchers are driven by concerns stemming from the practical issues associated with eventual implementation of multivariable control laws, such as reliability, limit protection, multimode operation, sampling rate selection, processor throughput, etc. Naturally, the burden imposed by dealing with these aspects of the problem can be reduced by ensuring that the complexity of the compensator is minimized. Our approach to these problems is based on extensions to input/output oriented techniques that have proven useful in the design of multivariable control systems for aircraft engines. In particular, researchers are exploring the use of relative gain analysis and the condition number as a means of quantifying the process of sensor/actuator selection and placement for shape control of a large space platform.

Make no mistake—errors can be controlled*

PubMed Central

Hinckley, C

2003-01-01



 Traditional quality control methods identify "variation" as the enemy. However, the control of variation by itself can never achieve the remarkably low non-conformance rates of world class quality leaders. Because the control of variation does not achieve the highest levels of quality, an inordinate focus on these techniques obscures key quality improvement opportunities and results in unnecessary pain and suffering for patients, and embarrassment, litigation, and loss of revenue for healthcare providers. Recent experience has shown that mistakes are the most common cause of problems in health care as well as in other industrial environments. Excessive product and process complexity contributes to both excessive variation and unnecessary mistakes. The best methods for controlling variation, mistakes, and complexity are each a form of mistake proofing. Using these mistake proofing techniques, virtually every mistake and non-conformance can be controlled at a fraction of the cost of traditional quality control methods. PMID:14532368

Effectiveness and cost-effectiveness of a proactive, goal-oriented, integrated care model in general practice for older people. A cluster randomised controlled trial: Integrated Systematic Care for older People--the ISCOPE study.

PubMed

Blom, Jeanet; den Elzen, Wendy; van Houwelingen, Anne H; Heijmans, Margot; Stijnen, Theo; Van den Hout, Wilbert; Gussekloo, Jacobijn

2016-01-01

older people often experience complex problems. Because of multiple problems, care for older people in general practice needs to shift from a 'problem-based, disease-oriented' care aiming at improvement of outcomes per disease to a 'goal-oriented care', aiming at improvement of functioning and personal quality of life, integrating all healthcare providers. Feasibility and cost-effectiveness of this proactive and integrated way of working are not yet established. cluster randomised trial. all persons aged ≥75 in 59 general practices (30 intervention, 29 control), with a combination of problems, as identified with a structured postal questionnaire with 21 questions on four health domains. for participants with problems on ≥3 domains, general practitioners (GPs) made an integrated care plan using a functional geriatric approach. Control practices: care as usual. (i) quality of life (QoL), (ii) activities of daily living, (iii) satisfaction with delivered health care and (iv) cost-effectiveness of the intervention at 1-year follow-up. Netherlands trial register, NTR1946. of the 11,476 registered eligible older persons, 7,285 (63%) participated in the screening. One thousand nine hundred and twenty-one (26%) had problems on ≥3 health domains. For 225 randomly chosen persons, a care plan was made. No beneficial effects were found on QoL, patients' functioning or healthcare use/costs. GPs experienced better overview of the care and stability, e.g. less unexpected demands, in the care. GPs prefer proactive integrated care. 'Horizontal' care using care plans for older people with complex problems can be a valuable tool in general practice. However, no direct beneficial effect was found for older persons. © The Author 2016. Published by Oxford University Press on behalf of the British Geriatrics Society.

Aiding the search: Examining individual differences in multiply-constrained problem solving.

PubMed

Ellis, Derek M; Brewer, Gene A

2018-07-01

Understanding and resolving complex problems is of vital importance in daily life. Problems can be defined by the limitations they place on the problem solver. Multiply-constrained problems are traditionally examined with the compound remote associates task (CRAT). Performance on the CRAT is partially dependent on an individual's working memory capacity (WMC). These findings suggest that executive processes are critical for problem solving and that there are reliable individual differences in multiply-constrained problem solving abilities. The goals of the current study are to replicate and further elucidate the relation between WMC and CRAT performance. To achieve these goals, we manipulated preexposure to CRAT solutions and measured WMC with complex-span tasks. In Experiment 1, we report evidence that preexposure to CRAT solutions improved problem solving accuracy, WMC was correlated with problem solving accuracy, and that WMC did not moderate the effect of preexposure on problem solving accuracy. In Experiment 2, we preexposed participants to correct and incorrect solutions. We replicated Experiment 1 and found that WMC moderates the effect of exposure to CRAT solutions such that high WMC participants benefit more from preexposure to correct solutions than low WMC (although low WMC participants have preexposure benefits as well). Broadly, these results are consistent with theories of working memory and problem solving that suggest a mediating role of attention control processes. Published by Elsevier Inc.

Optimisation of flight dynamic control based on many-objectives meta-heuristic: a comparative study

NASA Astrophysics Data System (ADS)

Bureerat, Sujin; Pholdee, Nantiwat; Radpukdee, Thana

2018-05-01

Development of many objective meta-heuristics (MnMHs) is a currently interesting topic as they are suitable to real applications of optimisation problems which usually require many ob-jectives. However, most of MnMHs have been mostly developed and tested based on stand-ard testing functions while the use of MnMHs to real applications is rare. Therefore, in this work, MnMHs are applied for optimisation design of flight dynamic control. The design prob-lem is posed to find control gains for minimising; the control effort, the spiral root, the damp-ing in roll root, sideslip angle deviation, and maximising; the damping ratio of the dutch-roll complex pair, the dutch-roll frequency, bank angle at pre-specified times 1 seconds and 2.8 second subjected to several constraints based on Military Specifications (1969) requirement. Several established many-objective meta-heuristics (MnMHs) are used to solve the problem while their performances are compared. With this research work, performance of several MnMHs for flight control is investigated. The results obtained will be the baseline for future development of flight dynamic and control.

Educational Technology Research in a VUCA World

ERIC Educational Resources Information Center

Reeves, Thomas C.; Reeves, Patricia M.

2015-01-01

The status of educational technology research in a VUCA world is examined. The acronym, VUCA, stands for "Volatility" (rapidly changing contexts and conditions), "Uncertainty" (information missing that is critical to problem solving), "Complexity" (multiple factors difficult to categorize or control), and…

Review of LMIs, Interior Point Methods, Complexity Theory, and Robustness Analysis

NASA Technical Reports Server (NTRS)

Mesbahi, M.

1996-01-01

From end of intro: ...We would like to show that for certain problems in systems and control theory, there exist algorithms for which corresponding (xi) can be viewed as a certain measure of robustness, e.g., stability margin.

Wireless sensing and vibration control with increased redundancy and robustness design.

PubMed

Li, Peng; Li, Luyu; Song, Gangbing; Yu, Yan

2014-11-01

Control systems with long distance sensor and actuator wiring have the problem of high system cost and increased sensor noise. Wireless sensor network (WSN)-based control systems are an alternative solution involving lower setup and maintenance costs and reduced sensor noise. However, WSN-based control systems also encounter problems such as possible data loss, irregular sampling periods (due to the uncertainty of the wireless channel), and the possibility of sensor breakdown (due to the increased complexity of the overall control system). In this paper, a wireless microcontroller-based control system is designed and implemented to wirelessly perform vibration control. The wireless microcontroller-based system is quite different from regular control systems due to its limited speed and computational power. Hardware, software, and control algorithm design are described in detail to demonstrate this prototype. Model and system state compensation is used in the wireless control system to solve the problems of data loss and sensor breakdown. A positive position feedback controller is used as the control law for the task of active vibration suppression. Both wired and wireless controllers are implemented. The results show that the WSN-based control system can be successfully used to suppress the vibration and produces resilient results in the presence of sensor failure.

Numerical Analysis on Seepage in the deep overburden CFRD

NASA Astrophysics Data System (ADS)

Zeyu, GUO; Junrui, CHAI; Yuan, QIN

2017-12-01

There are many problems in the construction of hydraulic structures on deep overburden because of its complex foundation structure and poor geological condition. Seepage failure is one of the main problems. The Combination of the seepage control system of the face rockfill dam and the deep overburden can effectively control the seepage of construction of the concrete face rockfill dam on the deep overburden. Widely used anti-seepage measures are horizontal blanket, waterproof wall, curtain grouting and so on, but the method, technique and its effect of seepage control still have many problems thus need further study. Due to the above considerations, Three-dimensional seepage field numerical analysis based on practical engineering case is conducted to study the seepage prevention effect under different seepage prevention methods, which is of great significance to the development of dam technology and the development of hydropower resources in China.

Rapid Preliminary Design of Interplanetary Trajectories Using the Evolutionary Mission Trajectory Generator

NASA Technical Reports Server (NTRS)

Englander, Jacob

2016-01-01

Preliminary design of interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a hybrid optimal control problem. The method is demonstrated on notional high-thrust chemical and low-thrust electric propulsion missions. In the low-thrust case, the hybrid optimal control problem is augmented to include systems design optimization.

The Proposal of the Model for Developing Dispatch System for Nationwide One-Day Integrative Planning

NASA Astrophysics Data System (ADS)

Kim, Hyun Soo; Choi, Hyung Rim; Park, Byung Kwon; Jung, Jae Un; Lee, Jin Wook

The problems of dispatch planning for container truck are classified as the pickup and delivery problems, which are highly complex issues that consider various constraints in the real world. However, in case of the current situation, it is developed by the control system so that it requires the automated planning system under the view of nationwide integrative planning. Therefore, the purpose of this study is to suggest model to develop the automated dispatch system through the constraint satisfaction problem and meta-heuristic technique-based algorithm. In the further study, the practical system is developed and evaluation is performed in aspect of various results. This study suggests model to undergo the study which promoted the complexity of the problems by considering the various constraints which were not considered in the early study. However, it is suggested that it is necessary to add the study which includes the real-time monitoring function for vehicles and cargos based on the information technology.

Putting the puzzle together: the role of ‘problem definition’ in complex clinical judgement

PubMed Central

Cristancho, Sayra; Lingard, Lorelei; Forbes, Thomas; Ott, Michael; Novick, Richard

2017-01-01

CONTEXT We teach judgement in pieces; that is, we talk about each aspect separately (patient, plan, resources, technique, etc.). We also let trainees figure out how to put the pieces together. In complex situations, this might be problematic. Using data from a drawing-based study on surgeons’ experiences with complex situations, we explore the notion of ‘problem definition’ in real-world clinical judgement using the theoretical lens of systems engineering. METHODS ‘Emergence’, the sensitising concept for analysis, is rooted in two key systems premises: that person and context are inseparable and that what emerges is an act of choice. Via a ‘gallery walk’ we used these premises to perform analysis on individual drawings as well as cross-comparisons of multiple drawings. Our focus was to understand similarities and differences among the vantage points used by multiple surgeons. RESULTS In this paper we challenge two assumptions from current models of clinical judgement: that experts hold a fixed and static definition of the problem and that consequently the focus of the expert’s work is on solving the problem. Each situation described by our participants revealed different but complementary perspectives of what a surgical problem might come to be: from concerns about ensuring standard of care, to balancing personal emotions versus care choices, to coordinating resources, and to maintaining control while in the midst of personality clashes. CONCLUSION We suggest that it is only at the situation and system level, not at the individual level, that we are able to appreciate the nuances of defining the problem when experts make judgements during real-world complex situations. PMID:27943366

Putting the puzzle together: the role of 'problem definition' in complex clinical judgement.

PubMed

Cristancho, Sayra; Lingard, Lorelei; Forbes, Thomas; Ott, Michael; Novick, Richard

2017-02-01

We teach judgement in pieces; that is, we talk about each aspect separately (patient, plan, resources, technique, etc.). We also let trainees figure out how to put the pieces together. In complex situations, this might be problematic. Using data from a drawing-based study on surgeons' experiences with complex situations, we explore the notion of 'problem definition' in real-world clinical judgement using the theoretical lens of systems engineering. 'Emergence', the sensitising concept for analysis, is rooted in two key systems premises: that person and context are inseparable and that what emerges is an act of choice. Via a 'gallery walk' we used these premises to perform analysis on individual drawings as well as cross-comparisons of multiple drawings. Our focus was to understand similarities and differences among the vantage points used by multiple surgeons. In this paper we challenge two assumptions from current models of clinical judgement: that experts hold a fixed and static definition of the problem and that consequently the focus of the expert's work is on solving the problem. Each situation described by our participants revealed different but complementary perspectives of what a surgical problem might come to be: from concerns about ensuring standard of care, to balancing personal emotions versus care choices, to coordinating resources, and to maintaining control while in the midst of personality clashes. We suggest that it is only at the situation and system level, not at the individual level, that we are able to appreciate the nuances of defining the problem when experts make judgements during real-world complex situations. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Managing Complexity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Posse, Christian; Malard, Joel M.

2004-08-01

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today’s most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically-based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This paper explores the state of the art in the use physical analogs for understanding the behavior of some econophysical systems and to deriving stable and robust controlmore » strategies for them. In particular we review and discussion applications of some analytic methods based on the thermodynamic metaphor according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood.« less

A Case Study of Controlling Crossover in a Selection Hyper-heuristic Framework Using the Multidimensional Knapsack Problem.

PubMed

Drake, John H; Özcan, Ender; Burke, Edmund K

2016-01-01

Hyper-heuristics are high-level methodologies for solving complex problems that operate on a search space of heuristics. In a selection hyper-heuristic framework, a heuristic is chosen from an existing set of low-level heuristics and applied to the current solution to produce a new solution at each point in the search. The use of crossover low-level heuristics is possible in an increasing number of general-purpose hyper-heuristic tools such as HyFlex and Hyperion. However, little work has been undertaken to assess how best to utilise it. Since a single-point search hyper-heuristic operates on a single candidate solution, and two candidate solutions are required for crossover, a mechanism is required to control the choice of the other solution. The frameworks we propose maintain a list of potential solutions for use in crossover. We investigate the use of such lists at two conceptual levels. First, crossover is controlled at the hyper-heuristic level where no problem-specific information is required. Second, it is controlled at the problem domain level where problem-specific information is used to produce good-quality solutions to use in crossover. A number of selection hyper-heuristics are compared using these frameworks over three benchmark libraries with varying properties for an NP-hard optimisation problem: the multidimensional 0-1 knapsack problem. It is shown that allowing crossover to be managed at the domain level outperforms managing crossover at the hyper-heuristic level in this problem domain.

Role of temperament in early adolescent pure and co-occurring internalizing and externalizing problems using a bifactor model: Moderation by parenting and gender

PubMed Central

WANG, FRANCES L.; EISENBERG, NANCY; VALIENTE, CARLOS; SPINRAD, TRACY L.

2015-01-01

We contribute to the literature on the relations of temperament to externalizing and internalizing problems by considering parental emotional expressivity and child gender as moderators of such relations and examining prediction of pure and co-occurring problem behaviors during early to middle adolescence using bifactor models (which provide unique and continuous factors for pure and co-occurring internalizing and externalizing problems). Parents and teachers reported on children’s (4.5- to 8-year-olds; N = 214) and early adolescents’ (6 years later; N = 168) effortful control, impulsivity, anger, sadness, and problem behaviors. Parental emotional expressivity was measured observationally and with parents’ self-reports. Early-adolescents’ pure externalizing and co-occurring problems shared childhood and/or early-adolescent risk factors of low effortful control, high impulsivity, and high anger. Lower childhood and early-adolescent impulsivity and higher early-adolescent sadness predicted early-adolescents’ pure internalizing. Childhood positive parental emotional expressivity more consistently related to early-adolescents’ lower pure externalizing compared to co-occurring problems and pure internalizing. Lower effortful control predicted changes in externalizing (pure and co-occurring) over 6 years, but only when parental positive expressivity was low. Higher impulsivity predicted co-occurring problems only for boys. Findings highlight the probable complex developmental pathways to adolescent pure and co-occurring externalizing and internalizing problems. PMID:26646352

Role of temperament in early adolescent pure and co-occurring internalizing and externalizing problems using a bifactor model: Moderation by parenting and gender.

PubMed

Wang, Frances L; Eisenberg, Nancy; Valiente, Carlos; Spinrad, Tracy L

2016-11-01

We contribute to the literature on the relations of temperament to externalizing and internalizing problems by considering parental emotional expressivity and child gender as moderators of such relations and examining prediction of pure and co-occurring problem behaviors during early to middle adolescence using bifactor models (which provide unique and continuous factors for pure and co-occurring internalizing and externalizing problems). Parents and teachers reported on children's (4.5- to 8-year-olds; N = 214) and early adolescents' (6 years later; N = 168) effortful control, impulsivity, anger, sadness, and problem behaviors. Parental emotional expressivity was measured observationally and with parents' self-reports. Early-adolescents' pure externalizing and co-occurring problems shared childhood and/or early-adolescent risk factors of low effortful control, high impulsivity, and high anger. Lower childhood and early-adolescent impulsivity and higher early-adolescent sadness predicted early-adolescents' pure internalizing. Childhood positive parental emotional expressivity more consistently related to early-adolescents' lower pure externalizing compared to co-occurring problems and pure internalizing. Lower effortful control predicted changes in externalizing (pure and co-occurring) over 6 years, but only when parental positive expressivity was low. Higher impulsivity predicted co-occurring problems only for boys. Findings highlight the probable complex developmental pathways to adolescent pure and co-occurring externalizing and internalizing problems.

Dynamic emulation modelling for the optimal operation of water systems: an overview

NASA Astrophysics Data System (ADS)

Castelletti, A.; Galelli, S.; Giuliani, M.

2014-12-01

Despite sustained increase in computing power over recent decades, computational limitations remain a major barrier to the effective and systematic use of large-scale, process-based simulation models in rational environmental decision-making. Whereas complex models may provide clear advantages when the goal of the modelling exercise is to enhance our understanding of the natural processes, they introduce problems of model identifiability caused by over-parameterization and suffer from high computational burden when used in management and planning problems. As a result, increasing attention is now being devoted to emulation modelling (or model reduction) as a way of overcoming these limitations. An emulation model, or emulator, is a low-order approximation of the process-based model that can be substituted for it in order to solve high resource-demanding problems. In this talk, an overview of emulation modelling within the context of the optimal operation of water systems will be provided. Particular emphasis will be given to Dynamic Emulation Modelling (DEMo), a special type of model complexity reduction in which the dynamic nature of the original process-based model is preserved, with consequent advantages in a wide range of problems, particularly feedback control problems. This will be contrasted with traditional non-dynamic emulators (e.g. response surface and surrogate models) that have been studied extensively in recent years and are mainly used for planning purposes. A number of real world numerical experiences will be used to support the discussion ranging from multi-outlet water quality control in water reservoir through erosion/sedimentation rebalancing in the operation of run-off-river power plants to salinity control in lake and reservoirs.

Research on the adaptive optical control technology based on DSP

NASA Astrophysics Data System (ADS)

Zhang, Xiaolu; Xue, Qiao; Zeng, Fa; Zhao, Junpu; Zheng, Kuixing; Su, Jingqin; Dai, Wanjun

2018-02-01

Adaptive optics is a real-time compensation technique using high speed support system for wavefront errors caused by atmospheric turbulence. However, the randomness and instantaneity of atmospheric changing introduce great difficulties to the design of adaptive optical systems. A large number of complex real-time operations lead to large delay, which is an insurmountable problem. To solve this problem, hardware operation and parallel processing strategy are proposed, and a high-speed adaptive optical control system based on DSP is developed. The hardware counter is used to check the system. The results show that the system can complete a closed loop control in 7.1ms, and improve the controlling bandwidth of the adaptive optical system. Using this system, the wavefront measurement and closed loop experiment are carried out, and obtain the good results.

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance - Empirical Results and a Plea for Ecologically Valid Microworlds.

PubMed

Süß, Heinz-Martin; Kretzschmar, André

2018-01-01

The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell's investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory ( Tailorshop ; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario ( FSYS ; i.e., a complex artificial world system). The results indicate that reasoning - specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) - are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications.

Proportional plus integral MIMO controller for regulation and tracking with anti-wind-up features

DOE Office of Scientific and Technical Information (OSTI.GOV)

Puleston, P.F.; Mantz, R.J.

1993-11-01

A proportional plus integral matrix control structure for MIMO systems is proposed. Based on a standard optimal control structure with integral action, it permits a greater degree of independence of the design and tuning of the regulating and tracking features, without considerably increasing the controller complexity. Fast recovery from load disturbances is achieved, while large overshoots associated with set-point changes and reset wind-up problems can be reduced. A simple effective procedure for practical tuning is introduced.

Modeling Power Systems as Complex Adaptive Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chassin, David P.; Malard, Joel M.; Posse, Christian

2004-12-30

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We reviewmore » and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.« less

Optimization of Highway Work Zone Decisions Considering Short-Term and Long-Term Impacts

DTIC Science & Technology

2010-01-01

strategies which can minimize the one-time work zone cost. Considering the complex and combinatorial nature of this optimization problem, a heuristic...combination of lane closure and traffic control strategies which can minimize the one-time work zone cost. Considering the complex and combinatorial nature ...zone) NV # the number of vehicle classes NPV $ Net Present Value p’(t) % Adjusted traffic diversion rate at time t p(t) % Natural diversion rate

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras.

PubMed

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-08-30

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

PubMed Central

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-01-01

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme. PMID:27589748

Noise Response Data Reveal Novel Controllability Gramian for Nonlinear Network Dynamics

PubMed Central

Kashima, Kenji

2016-01-01

Control of nonlinear large-scale dynamical networks, e.g., collective behavior of agents interacting via a scale-free connection topology, is a central problem in many scientific and engineering fields. For the linear version of this problem, the so-called controllability Gramian has played an important role to quantify how effectively the dynamical states are reachable by a suitable driving input. In this paper, we first extend the notion of the controllability Gramian to nonlinear dynamics in terms of the Gibbs distribution. Next, we show that, when the networks are open to environmental noise, the newly defined Gramian is equal to the covariance matrix associated with randomly excited, but uncontrolled, dynamical state trajectories. This fact theoretically justifies a simple Monte Carlo simulation that can extract effectively controllable subdynamics in nonlinear complex networks. In addition, the result provides a novel insight into the relationship between controllability and statistical mechanics. PMID:27264780

Intelligent on-line fault tolerant control for unanticipated catastrophic failures.

PubMed

Yen, Gary G; Ho, Liang-Wei

2004-10-01

As dynamic systems become increasingly complex, experience rapidly changing environments, and encounter a greater variety of unexpected component failures, solving the control problems of such systems is a grand challenge for control engineers. Traditional control design techniques are not adequate to cope with these systems, which may suffer from unanticipated dynamic failures. In this research work, we investigate the on-line fault tolerant control problem and propose an intelligent on-line control strategy to handle the desired trajectories tracking problem for systems suffering from various unanticipated catastrophic faults. Through theoretical analysis, the sufficient condition of system stability has been derived and two different on-line control laws have been developed. The approach of the proposed intelligent control strategy is to continuously monitor the system performance and identify what the system's current state is by using a fault detection method based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, the proposed intelligent controller will adjust its control signal to compensate for the unknown system failure dynamics by using an artificial neural network as an on-line estimator to approximate the unexpected and unknown failure dynamics. The first control law is derived directly from the Lyapunov stability theory, while the second control law is derived based upon the discrete-time sliding mode control technique. Both control laws have been implemented in a variety of failure scenarios to validate the proposed intelligent control scheme. The simulation results, including a three-tank benchmark problem, comply with theoretical analysis and demonstrate a significant improvement in trajectory following performance based upon the proposed intelligent control strategy.

Tracked robot controllers for climbing obstacles autonomously

NASA Astrophysics Data System (ADS)

Vincent, Isabelle

2009-05-01

Research in mobile robot navigation has demonstrated some success in navigating flat indoor environments while avoiding obstacles. However, the challenge of analyzing complex environments to climb obstacles autonomously has had very little success due to the complexity of the task. Unmanned ground vehicles currently exhibit simple autonomous behaviours compared to the human ability to move in the world. This paper presents the control algorithms designed for a tracked mobile robot to autonomously climb obstacles by varying its tracks configuration. Two control algorithms are proposed to solve the autonomous locomotion problem for climbing obstacles. First, a reactive controller evaluates the appropriate geometric configuration based on terrain and vehicle geometric considerations. Then, a reinforcement learning algorithm finds alternative solutions when the reactive controller gets stuck while climbing an obstacle. The methodology combines reactivity to learning. The controllers have been demonstrated in box and stair climbing simulations. The experiments illustrate the effectiveness of the proposed approach for crossing obstacles.

Direct Maximization of Protein Identifications from Tandem Mass Spectra*

PubMed Central

Spivak, Marina; Weston, Jason; Tomazela, Daniela; MacCoss, Michael J.; Noble, William Stafford

2012-01-01

The goal of many shotgun proteomics experiments is to determine the protein complement of a complex biological mixture. For many mixtures, most methodological approaches fall significantly short of this goal. Existing solutions to this problem typically subdivide the task into two stages: first identifying a collection of peptides with a low false discovery rate and then inferring from the peptides a corresponding set of proteins. In contrast, we formulate the protein identification problem as a single optimization problem, which we solve using machine learning methods. This approach is motivated by the observation that the peptide and protein level tasks are cooperative, and the solution to each can be improved by using information about the solution to the other. The resulting algorithm directly controls the relevant error rate, can incorporate a wide variety of evidence and, for complex samples, provides 18–34% more protein identifications than the current state of the art approaches. PMID:22052992

STARS: An integrated general-purpose finite element structural, aeroelastic, and aeroservoelastic analysis computer program

NASA Technical Reports Server (NTRS)

Gupta, Kajal K.

1991-01-01

The details of an integrated general-purpose finite element structural analysis computer program which is also capable of solving complex multidisciplinary problems is presented. Thus, the SOLIDS module of the program possesses an extensive finite element library suitable for modeling most practical problems and is capable of solving statics, vibration, buckling, and dynamic response problems of complex structures, including spinning ones. The aerodynamic module, AERO, enables computation of unsteady aerodynamic forces for both subsonic and supersonic flow for subsequent flutter and divergence analysis of the structure. The associated aeroservoelastic analysis module, ASE, effects aero-structural-control stability analysis yielding frequency responses as well as damping characteristics of the structure. The program is written in standard FORTRAN to run on a wide variety of computers. Extensive graphics, preprocessing, and postprocessing routines are also available pertaining to a number of terminals.

Simulation and optimization of an experimental membrane wastewater treatment plant using computational intelligence methods.

PubMed

Ludwig, T; Kern, P; Bongards, M; Wolf, C

2011-01-01

The optimization of relaxation and filtration times of submerged microfiltration flat modules in membrane bioreactors used for municipal wastewater treatment is essential for efficient plant operation. However, the optimization and control of such plants and their filtration processes is a challenging problem due to the underlying highly nonlinear and complex processes. This paper presents the use of genetic algorithms for this optimization problem in conjunction with a fully calibrated simulation model, as computational intelligence methods are perfectly suited to the nonconvex multi-objective nature of the optimization problems posed by these complex systems. The simulation model is developed and calibrated using membrane modules from the wastewater simulation software GPS-X based on the Activated Sludge Model No.1 (ASM1). Simulation results have been validated at a technical reference plant. They clearly show that filtration process costs for cleaning and energy can be reduced significantly by intelligent process optimization.

An approach to determination of shunt circuits parameters for damping vibrations

NASA Astrophysics Data System (ADS)

Matveenko; Iurlova; Oshmarin; Sevodina; Iurlov

2018-04-01

This paper considers the problem of natural vibrations of a deformable structure containing elements made of piezomaterials. The piezoelectric elements are connected through electrodes to an external electric circuit, which consists of resistive, inductive and capacitive elements. Based on the solution of this problem, the parameters of external electric circuits are searched for to allow optimal passive control of the structural vibrations. The solution to the problem is complex natural vibration frequencies, the real part of which corresponds to the circular eigenfrequency of vibrations and the imaginary part corresponds to its damping rate (damping ratio). The analysis of behaviour of the imaginary parts of complex eigenfrequencies in the space of external circuit parameters allows one to damp given modes of structure vibrations. The effectiveness of the proposed approach is demonstrated using a cantilever-clamped plate and a shell structure in the form of a semi-cylinder connected to series resonant ? circuits.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moore, Thomas W.; Quach, Tu-Thach; Detry, Richard Joseph

Complex Adaptive Systems of Systems, or CASoS, are vastly complex ecological, sociological, economic and/or technical systems which we must understand to design a secure future for the nation and the world. Perturbations/disruptions in CASoS have the potential for far-reaching effects due to pervasive interdependencies and attendant vulnerabilities to cascades in associated systems. Phoenix was initiated to address this high-impact problem space as engineers. Our overarching goals are maximizing security, maximizing health, and minimizing risk. We design interventions, or problem solutions, that influence CASoS to achieve specific aspirations. Through application to real-world problems, Phoenix is evolving the principles and discipline ofmore » CASoS Engineering while growing a community of practice and the CASoS engineers to populate it. Both grounded in reality and working to extend our understanding and control of that reality, Phoenix is at the same time a solution within a CASoS and a CASoS itself.« less

The Applied Mathematics for Power Systems (AMPS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chertkov, Michael

2012-07-24

Increased deployment of new technologies, e.g., renewable generation and electric vehicles, is rapidly transforming electrical power networks by crossing previously distinct spatiotemporal scales and invalidating many traditional approaches for designing, analyzing, and operating power grids. This trend is expected to accelerate over the coming years, bringing the disruptive challenge of complexity, but also opportunities to deliver unprecedented efficiency and reliability. Our Applied Mathematics for Power Systems (AMPS) Center will discover, enable, and solve emerging mathematics challenges arising in power systems and, more generally, in complex engineered networks. We will develop foundational applied mathematics resulting in rigorous algorithms and simulation toolboxesmore » for modern and future engineered networks. The AMPS Center deconstruction/reconstruction approach 'deconstructs' complex networks into sub-problems within non-separable spatiotemporal scales, a missing step in 20th century modeling of engineered networks. These sub-problems are addressed within the appropriate AMPS foundational pillar - complex systems, control theory, and optimization theory - and merged or 'reconstructed' at their boundaries into more general mathematical descriptions of complex engineered networks where important new questions are formulated and attacked. These two steps, iterated multiple times, will bridge the growing chasm between the legacy power grid and its future as a complex engineered network.« less

An Automated Solution of the Low-Thrust Interplanetary Trajectory Problem.

PubMed

Englander, Jacob A; Conway, Bruce A

2017-01-01

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated, which can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a hybrid optimal control problem. The method is demonstrated on hypothetical missions to Mercury, the main asteroid belt, and Pluto.

An Automated Solution of the Low-Thrust Interplanetary Trajectory Problem

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Conway, Bruce

2016-01-01

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated, which can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a hybrid optimal control problem. The method is demonstrated on hypothetical missions to Mercury, the main asteroid belt, and Pluto.

An Automated Solution of the Low-Thrust Interplanetary Trajectory Problem

PubMed Central

Englander, Jacob A.; Conway, Bruce A.

2017-01-01

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated, which can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a hybrid optimal control problem. The method is demonstrated on hypothetical missions to Mercury, the main asteroid belt, and Pluto. PMID:29515289

Using block pulse functions for seismic vibration semi-active control of structures with MR dampers

NASA Astrophysics Data System (ADS)

Rahimi Gendeshmin, Saeed; Davarnia, Daniel

2018-03-01

This article applied the idea of block pulse functions in the semi-active control of structures. The BP functions give effective tools to approximate complex problems. The applied control algorithm has a major effect on the performance of the controlled system and the requirements of the control devices. In control problems, it is important to devise an accurate analytical technique with less computational cost. It is proved that the BP functions are fundamental tools in approximation problems which have been applied in disparate areas in last decades. This study focuses on the employment of BP functions in control algorithm concerning reduction the computational cost. Magneto-rheological (MR) dampers are one of the well-known semi-active tools that can be used to control the response of civil Structures during earthquake. For validation purposes, numerical simulations of a 5-story shear building frame with MR dampers are presented. The results of suggested method were compared with results obtained by controlling the frame by the optimal control method based on linear quadratic regulator theory. It can be seen from simulation results that the suggested method can be helpful in reducing seismic structural responses. Besides, this method has acceptable accuracy and is in agreement with optimal control method with less computational costs.

Neural networks for continuous online learning and control.

PubMed

Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long

2006-11-01

This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.

An overview of the genetic dissection of complex traits.

PubMed

Rao, D C

2008-01-01

Thanks to the recent revolutionary genomic advances such as the International HapMap consortium, resolution of the genetic architecture of common complex traits is beginning to look hopeful. While demonstrating the feasibility of genome-wide association (GWA) studies, the pathbreaking Wellcome Trust Case Control Consortium (WTCCC) study also serves to underscore the critical importance of very large sample sizes and draws attention to potential problems, which need to be addressed as part of the study design. Even the large WTCCC study had vastly inadequate power for several of the associations reported (and confirmed) and, therefore, most of the regions harboring relevant associations may not be identified anytime soon. This chapter provides an overview of some of the key developments in the methodological approaches to genetic dissection of common complex traits. Constrained Bayesian networks are suggested as especially useful for analysis of pathway-based SNPs. Likewise, composite likelihood is suggested as a promising method for modeling complex systems. It discusses the key steps in a study design, with an emphasis on GWA studies. Potential limitations highlighted by the WTCCC GWA study are discussed, including problems associated with massive genotype imputation, analysis of pooled national samples, shared controls, and the critical role of interactions. GWA studies clearly need massive sample sizes that are only possible through genuine collaborations. After all, for common complex traits, the question is not whether we can find some pieces of the puzzle, but how large and what kind of a sample we need to (nearly) solve the genetic puzzle.

Virtual Control Policy for Binary Ordered Resources Petri Net Class

PubMed Central

Rovetto, Carlos A.; Concepción, Tomás J.; Cano, Elia Esther

2016-01-01

Prevention and avoidance of deadlocks in sensor networks that use the wormhole routing algorithm is an active research domain. There are diverse control policies that will address this problem being our approach a new method. In this paper we present a virtual control policy for the new specialized Petri net subclass called Binary Ordered Resources Petri Net (BORPN). Essentially, it is an ordinary class constructed from various state machines that share unitary resources in a complex form, which allows branching and joining of processes. The reduced structure of this new class gives advantages that allow analysis of the entire system’s behavior, which is a prohibitive task for large systems because of the complexity and routing algorithms. PMID:27548170

Social and cultural factors in the successful control of tuberculosis.

PubMed Central

Rubel, A J; Garro, L C

1992-01-01

The burden of tuberculosis on the public health is staggering. Worldwide, annual incidence of new cases is estimated to be about 8 million. Almost 3 million deaths occur yearly. Early case identification and adherence to treatment regimens are the remaining barriers to successful control. In many nations, however, fewer than half those with active disease receive a diagnosis, and fewer than half those beginning treatment complete it. The twin problems of delay in seeking treatment and abandonment of a prescribed regimen derive from complex factors. People's confusion as to the implications of the tuberculosis symptoms, costs of transportation to clinic services, the social stigma that attaches to tuberculosis, the high cost of medication, organizational problems in providing adequate followup services, and patients' perception of clinic facilities as inhospitable all contribute to the complexity. Sociocultural factors are emphasized in this report because hitherto they have not been adequately explored. Salient among those sociocultural factors is the health culture of the patients. That is, the understanding and information people have from family, friends, and neighbors as to the nature of a health problem, its cause, and its implications. A knowledge of the health culture of their patients has become a critical tool if tuberculosis control programs are to be successful. Several anthropological procedures are recommended to help uncover the health culture of people served by tuberculosis clinics. PMID:1454974

Computational approaches to motor learning by imitation.

PubMed Central

Schaal, Stefan; Ijspeert, Auke; Billard, Aude

2003-01-01

Movement imitation requires a complex set of mechanisms that map an observed movement of a teacher onto one's own movement apparatus. Relevant problems include movement recognition, pose estimation, pose tracking, body correspondence, coordinate transformation from external to egocentric space, matching of observed against previously learned movement, resolution of redundant degrees-of-freedom that are unconstrained by the observation, suitable movement representations for imitation, modularization of motor control, etc. All of these topics by themselves are active research problems in computational and neurobiological sciences, such that their combination into a complete imitation system remains a daunting undertaking-indeed, one could argue that we need to understand the complete perception-action loop. As a strategy to untangle the complexity of imitation, this paper will examine imitation purely from a computational point of view, i.e. we will review statistical and mathematical approaches that have been suggested for tackling parts of the imitation problem, and discuss their merits, disadvantages and underlying principles. Given the focus on action recognition of other contributions in this special issue, this paper will primarily emphasize the motor side of imitation, assuming that a perceptual system has already identified important features of a demonstrated movement and created their corresponding spatial information. Based on the formalization of motor control in terms of control policies and their associated performance criteria, useful taxonomies of imitation learning can be generated that clarify different approaches and future research directions. PMID:12689379

Systems engineering and integration of control centers in support of multiple programs. [ground control for STS payloads and unmanned vehicles

NASA Technical Reports Server (NTRS)

Miller, David N.

1989-01-01

The NASA Johnson Space Center's new Multiprogram Control Center (MPCC) addresses the control requirements of complex STS payloads as well as unmanned vehicles. An account is given of the relationship of the MPCC to the STS Mission Control Center, with a view to significant difficulties that may be encountered and solutions thus far devised for generic problems. Examples of MPCC workstation applications encompass telemetry decommutation, engineering unit conversion, data-base management, trajectory processing, and flight design.

A service-oriented data access control model

NASA Astrophysics Data System (ADS)

Meng, Wei; Li, Fengmin; Pan, Juchen; Song, Song; Bian, Jiali

2017-01-01

The development of mobile computing, cloud computing and distributed computing meets the growing individual service needs. Facing with complex application system, it's an urgent problem to ensure real-time, dynamic, and fine-grained data access control. By analyzing common data access control models, on the basis of mandatory access control model, the paper proposes a service-oriented access control model. By regarding system services as subject and data of databases as object, the model defines access levels and access identification of subject and object, and ensures system services securely to access databases.

Discrimination theory of rule-governed behavior

PubMed Central

Cerutti, Daniel T.

1989-01-01

In rule-governed behavior, previously established elementary discriminations are combined in complex instructions and thus result in complex behavior. Discriminative combining and recombining of responses produce behavior with characteristics differing from those of behavior that is established through the effects of its direct consequences. For example, responding in instructed discrimination may be occasioned by discriminative stimuli that are temporally and situationally removed from the circumstances under which the discrimination is instructed. The present account illustrates properties of rule-governed behavior with examples from research in instructional control and imitation learning. Units of instructed behavior, circumstances controlling compliance with instructions, and rule-governed problem solving are considered. PMID:16812579

Validation and Verification of Future Integrated Safety-Critical Systems Operating under Off-Nominal Conditions

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.

2010-01-01

Loss of control remains one of the largest contributors to aircraft fatal accidents worldwide. Aircraft loss-of-control accidents are highly complex in that they can result from numerous causal and contributing factors acting alone or (more often) in combination. Hence, there is no single intervention strategy to prevent these accidents and reducing them will require a holistic integrated intervention capability. Future onboard integrated system technologies developed for preventing loss of vehicle control accidents must be able to assure safe operation under the associated off-nominal conditions. The transition of these technologies into the commercial fleet will require their extensive validation and verification (V and V) and ultimate certification. The V and V of complex integrated systems poses major nontrivial technical challenges particularly for safety-critical operation under highly off-nominal conditions associated with aircraft loss-of-control events. This paper summarizes the V and V problem and presents a proposed process that could be applied to complex integrated safety-critical systems developed for preventing aircraft loss-of-control accidents. A summary of recent research accomplishments in this effort is also provided.

Complex Problem Solving: What It Is and What It Is Not

PubMed Central

Dörner, Dietrich; Funke, Joachim

2017-01-01

Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems. Psychometric issues such as reliable assessments and addressing correlations with other instruments have been in the foreground of these discussions and have left the content validity of complex problem solving in the background. In this paper, we return the focus to content issues and address the important features that define complex problems. PMID:28744242

Parallel Optimization of Polynomials for Large-scale Problems in Stability and Control

NASA Astrophysics Data System (ADS)

Kamyar, Reza

In this thesis, we focus on some of the NP-hard problems in control theory. Thanks to the converse Lyapunov theory, these problems can often be modeled as optimization over polynomials. To avoid the problem of intractability, we establish a trade off between accuracy and complexity. In particular, we develop a sequence of tractable optimization problems --- in the form of Linear Programs (LPs) and/or Semi-Definite Programs (SDPs) --- whose solutions converge to the exact solution of the NP-hard problem. However, the computational and memory complexity of these LPs and SDPs grow exponentially with the progress of the sequence - meaning that improving the accuracy of the solutions requires solving SDPs with tens of thousands of decision variables and constraints. Setting up and solving such problems is a significant challenge. The existing optimization algorithms and software are only designed to use desktop computers or small cluster computers --- machines which do not have sufficient memory for solving such large SDPs. Moreover, the speed-up of these algorithms does not scale beyond dozens of processors. This in fact is the reason we seek parallel algorithms for setting-up and solving large SDPs on large cluster- and/or super-computers. We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to efficiently utilize hundreds and potentially thousands of processors, and analyze systems with 100+ dimensional state-space. Furthermore, we extend our algorithms to analyze robust stability over more complicated geometries such as hypercubes and arbitrary convex polytopes. Our algorithms can be readily extended to address a wide variety of problems in control such as Hinfinity synthesis for systems with parametric uncertainty and computing control Lyapunov functions.

LCTV Holographic Imaging

NASA Technical Reports Server (NTRS)

Knopp, Jerome

1996-01-01

Astronauts are required to interface with complex systems that require sophisticated displays to communicate effectively. Lightweight, head-mounted real-time displays that present holographic images for comfortable viewing may be the ideal solution. We describe an implementation of a liquid crystal television (LCTV) as a spatial light modulator (SLM) for the display of holograms. The implementation required the solution of a complex set of problems. These include field calculations, determination of the LCTV-SLM complex transmittance characteristics and a precise knowledge of the signal mapping between the LCTV and frame grabbing board that controls it. Realizing the hologram is further complicated by the coupling that occurs between the phase and amplitude in the LCTV transmittance. A single drive signal (a gray level signal from a framegrabber) determines both amplitude and phase. Since they are not independently controllable (as is true in the ideal SLM) one must deal with the problem of optimizing (in some sense) the hologram based on this constraint. Solutions for the above problems have been found. An algorithm has been for field calculations that uses an efficient outer product formulation. Juday's MEDOF 7 (Minimum Euclidean Distance Optimal Filter) algorithm used for originally for filter calculations has been successfully adapted to handle metrics appropriate for holography. This has solved the problem of optimizing the hologram to the constraints imposed by coupling. Two laboratory methods have been developed for determining an accurate mapping of framegrabber pixels to LCTV pixels. A friendly software system has been developed that integrates the hologram calculation and realization process using a simple set of instructions. The computer code and all the laboratory measurement techniques determining SLM parameters have been proven with the production of a high quality test image.

Guaranteed cost control with poles assignment for a flexible air-breathing hypersonic vehicle

NASA Astrophysics Data System (ADS)

Li, Hongyi; Si, Yulin; Wu, Ligang; Hu, Xiaoxiang; Gao, Huijun

2011-05-01

This article investigates the problem of guaranteed cost control for a flexible air-breathing hypersonic vehicle (FAHV). The FAHV includes intricate coupling between the engine and flight dynamics as well as complex interplay between flexible and rigid modes, which results in an intractable system for the control design. A longitudinal model is adopted for control design due to the complexity of the vehicle. First, for a highly nonlinear and coupled FAHV, a linearised model is established around the trim condition, which includes the state of altitude, velocity, angle of attack, pitch angle and pitch rate, etc. Secondly, by using the Lyapunov approach, performance analysis is carried out for the resulting closed-loop FAHV system, whose criterion with respect to guaranteed performance cost and poles assignment is expressed in the framework of linear matrix inequalities (LMIs). The established criterion exhibits a kind of decoupling between the Lyapunov positive-definite matrices to be determined and the FAHV system matrices, which is enabled by the introduction of additional slack matrix variables. Thirdly, a convex optimisation problem with LMI constraints is formulated for designing an admissible controller, which guarantees a prescribed performance cost with the simultaneous consideration of poles assignment for the resulting closed-loop system. Finally, some simulation results are provided to show that the guaranteed cost controller could assign the poles into the desired regional and achieve excellent reference altitude and velocity tracking performance.

An intelligent advisor for the design manager

NASA Technical Reports Server (NTRS)

Rogers, James L.; Padula, Sharon L.

1989-01-01

A design problem is viewed as a complex system divisible into modules. Before the design of a complex system can begin, much time and money are spent in determining the couplings among modules and the presence of iterative loops. This is important because the design manager must know how to group the modules into substems and how to assign subsystems to design teams so that changes in one subsystem will have predictable effects on other subsystems. Determining these subsystems is not an easy, straightforward process and often important couplings are overlooked. Moreover, the planning task must be repeated as new information becomes available or as the design specifications change. The purchase of this research effort is to develop a knowledge-based tool to act as an intelligent advisor for the design manager. This tool identifies the subsystems of a complex design problem, orders them into a well-structured format, and marks the couplings among the subsystems to facilitate the use of multilevel tools. The tool was tested in the decomposition of the COFS (Control of Flexible Structures) mast design which has about 50 modules. This test indicated that this type of approach could lead to a substantial savings by organizing and displaying a complex problem as a sequence of subsystems easily divisible among design teams.

Using mobile probes to inform and measure the effectiveness of traffic control strategies on urban networks.

DOT National Transportation Integrated Search

2015-07-01

Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this : congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work ha...

33 CFR 273.13 - Program policy.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Program is designed to deal primarily with weed infestations of major economic significance including... should constitute investigation of a specific problem weed or weed complex, not generalized surveys of... Control Program, except as such areas may be used for experimental purposes in research performed for the...

33 CFR 273.13 - Program policy.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Program is designed to deal primarily with weed infestations of major economic significance including... should constitute investigation of a specific problem weed or weed complex, not generalized surveys of... Control Program, except as such areas may be used for experimental purposes in research performed for the...

33 CFR 273.13 - Program policy.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Program is designed to deal primarily with weed infestations of major economic significance including... should constitute investigation of a specific problem weed or weed complex, not generalized surveys of... Control Program, except as such areas may be used for experimental purposes in research performed for the...

33 CFR 273.13 - Program policy.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Program is designed to deal primarily with weed infestations of major economic significance including... should constitute investigation of a specific problem weed or weed complex, not generalized surveys of... Control Program, except as such areas may be used for experimental purposes in research performed for the...

33 CFR 273.13 - Program policy.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Program is designed to deal primarily with weed infestations of major economic significance including... should constitute investigation of a specific problem weed or weed complex, not generalized surveys of... Control Program, except as such areas may be used for experimental purposes in research performed for the...

Cloud Model-Based Artificial Immune Network for Complex Optimization Problem

PubMed Central

Wang, Mingan; Li, Jianming; Guo, Dongliang

2017-01-01

This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators—cloning, mutation, and suppression—are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust the dynamic clone multipliers of antibodies, an asymmetrical cloud-based mutation operator is used to control the adaptive evolution of antibodies, and a normal similarity cloud-based suppressor is used to keep the diversity of the antibody population. To quicken the searching convergence, a dynamic searching step length strategy is adopted. For comparative study, a series of numerical simulations are arranged between AINet-CM and the other three artificial immune systems, that is, opt-aiNet, IA-AIS, and AAIS-2S. Furthermore, two industrial applications—finite impulse response (FIR) filter design and proportional-integral-differential (PID) controller tuning—are investigated and the results demonstrate the potential searching capability and practical value of the proposed AINet-CM algorithm. PMID:28630620

Cloud Model-Based Artificial Immune Network for Complex Optimization Problem.

PubMed

Wang, Mingan; Feng, Shuo; Li, Jianming; Li, Zhonghua; Xue, Yu; Guo, Dongliang

2017-01-01

This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators-cloning, mutation, and suppression-are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust the dynamic clone multipliers of antibodies, an asymmetrical cloud-based mutation operator is used to control the adaptive evolution of antibodies, and a normal similarity cloud-based suppressor is used to keep the diversity of the antibody population. To quicken the searching convergence, a dynamic searching step length strategy is adopted. For comparative study, a series of numerical simulations are arranged between AINet-CM and the other three artificial immune systems, that is, opt-aiNet, IA-AIS, and AAIS-2S. Furthermore, two industrial applications-finite impulse response (FIR) filter design and proportional-integral-differential (PID) controller tuning-are investigated and the results demonstrate the potential searching capability and practical value of the proposed AINet-CM algorithm.

Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

PubMed

Li, Shuai; Li, Yangming

2013-10-28

The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

The prevalence of foot problems in older women: a cause for concern.

PubMed

Dawson, Jill; Thorogood, Margaret; Marks, Sally-Anne; Juszczak, Ed; Dodd, Chris; Lavis, Grahame; Fitzpatrick, Ray

2002-06-01

Painful feet are an extremely common problem amongst older women. Such problems increase the risk of falls and hamper mobility. The aetiology of painful and deformed feet is poorly understood. Data were obtained during a pilot case-control study about past high heel usage in women, in relation to osteoarthritis of the knee. A total of 127 women aged 50-70 were interviewed (31 cases, 96 controls); case-control sets were matched for age. The following information was obtained about footwear: (1) age when first wore shoes with heels 1, 2 and 3 inches high; (2) height of heels worn for work; (3) maximum height of heels worn regularly for work, going out socially and for dancing, in 10-year age bands. Information about work-related activities and lifetime occupational history was gathered using a Life-Grid. The interview included a foot inspection. Foot problems, particularly foot arthritis, affected considerably more cases than controls (45 per cent versus 16 per cent, p = 0.001) and was considered a confounder. Cases were therefore excluded from subsequent analyses. Amongst controls, the prevalence of any foot problems was very high (83 per cent). All women had regularly worn one inch heels and few (8 per cent) had never worn 2 inch heels. Foot problems were significantly associated with a history of wearing relatively lower heels. Few work activities were related to foot problems; regular lifting was associated with foot pain (p = 0.03). Most women in this age-group have been exposed to high-heeled shoes over many years, making aetiological research difficult in this area. Foot pain and deformities are widespread. The relationship between footwear, occupational activities and foot problems is a complex one that deserves considerably more research.

A Fuzzy Logic Optimal Control Law Solution to the CMMCA Tracking Problem

DTIC Science & Technology

1993-03-01

or from a transfer function. Many times, however, the resulting algorithms are so complex as to be completely or essentially useless. Applications...implemented in a nearly real time computer simulation. Located within the LQ framework are all the performance data for both the ClMCA and the CX...repuired nor desired. 34 - / k more general and less exacting framework was used. In order to concentrate on tho theory and problem solution, it was

Quality of life of people with mental health problems: a synthesis of qualitative research

PubMed Central

2012-01-01

Purpose To identify the domains of quality of life important to people with mental health problems. Method A systematic review of qualitative research undertaken with people with mental health problems using a framework synthesis. Results We identified six domains: well-being and ill-being; control, autonomy and choice; self-perception; belonging; activity; and hope and hopelessness. Firstly, symptoms or ‘ill-being’ were an intrinsic aspect of quality of life for people with severe mental health problems. Additionally, a good quality of life was characterised by the feeling of being in control (particularly of distressing symptoms), autonomy and choice; a positive self-image; a sense of belonging; engagement in meaningful and enjoyable activities; and feelings of hope and optimism. Conversely, a poor quality life, often experienced by those with severe mental health difficulties, was characterized by feelings of distress; lack of control, choice and autonomy; low self-esteem and confidence; a sense of not being part of society; diminished activity; and a sense of hopelessness and demoralization. Conclusions Generic measures fail to address the complexity of quality of life measurement and the broad range of domains important to people with mental health problems. PMID:23173689

Multiobjective Optimal Control Methodology for the Analysis of Certain Sociodynamic Problems

DTIC Science & Technology

2009-03-01

but less expensive in both time and memory. 137 References [1] R. Albert and A-L Barabasi. Statistical mechanics of complex networks. Reviews of Modern...Review, E(51):4282–4286, 1995. [24] D. Helbing, P. Molnar, and F. Schweitzer . Computer simulation of pedestrian dynamics and trail formation. May 1998...Patterson AFB, OH, 2001. [49] F. Schweitzer . Brownian Agents and Active Particles. Springer, Santa Fe, NM, 2003. [50] P. Sen. Complexities of social

H∞ control for switched fuzzy systems via dynamic output feedback: Hybrid and switched approaches

NASA Astrophysics Data System (ADS)

Xiang, Weiming; Xiao, Jian; Iqbal, Muhammad Naveed

2013-06-01

Fuzzy T-S model has been proven to be a practical and effective way to deal with the analysis and synthesis problems for complex nonlinear systems. As for switched nonlinear system, describing its subsystems as fuzzy T-S models, namely switched fuzzy system, naturally is an alternative method to conventional control approaches. In this paper, the H∞ control problem for a class of switched fuzzy systems is addressed. Hybrid and switched design approaches are proposed with different availability of switching signal information at switching instant. The hybrid control strategy includes two parts: fuzzy controllers for subsystems and state updating controller at switching instant, and the switched control strategy contains the controllers for subsystems. It is demonstrated that the conservativeness is reduced by introducing the state updating behavior but its cost is an online prediction of switching signal. Numerical examples are given to illustrate the effectiveness of proposed approaches and compare the conservativeness of two approaches.

Coordinated Dynamic Behaviors for Multirobot Systems With Collision Avoidance.

PubMed

Sabattini, Lorenzo; Secchi, Cristian; Fantuzzi, Cesare

2017-12-01

In this paper, we propose a novel methodology for achieving complex dynamic behaviors in multirobot systems. In particular, we consider a multirobot system partitioned into two subgroups: 1) dependent and 2) independent robots. Independent robots are utilized as a control input, and their motion is controlled in such a way that the dependent robots solve a tracking problem, that is following arbitrarily defined setpoint trajectories, in a coordinated manner. The control strategy proposed in this paper explicitly addresses the collision avoidance problem, utilizing a null space-based behavioral approach: this leads to combining, in a non conflicting manner, the tracking control law with a collision avoidance strategy. The combination of these control actions allows the robots to execute their task in a safe way. Avoidance of collisions is formally proven in this paper, and the proposed methodology is validated by means of simulations and experiments on real robots.

A boundedness result for the direct heuristic dynamic programming.

PubMed

Liu, Feng; Sun, Jian; Si, Jennie; Guo, Wentao; Mei, Shengwei

2012-08-01

Approximate/adaptive dynamic programming (ADP) has been studied extensively in recent years for its potential scalability to solve large state and control space problems, including those involving continuous states and continuous controls. The applicability of ADP algorithms, especially the adaptive critic designs has been demonstrated in several case studies. Direct heuristic dynamic programming (direct HDP) is one of the ADP algorithms inspired by the adaptive critic designs. It has been shown applicable to industrial scale, realistic and complex control problems. In this paper, we provide a uniformly ultimately boundedness (UUB) result for the direct HDP learning controller under mild and intuitive conditions. By using a Lyapunov approach we show that the estimation errors of the learning parameters or the weights in the action and critic networks remain UUB. This result provides a useful controller convergence guarantee for the first time for the direct HDP design. Copyright © 2012 Elsevier Ltd. All rights reserved.

Rumination, Social Problem Solving and Suicide Intent Among Egyptians With a Recent Suicide Attempt.

PubMed

Sharaf, Amira Y; Lachine, Ola A; Thompson, Elaine A

2018-02-01

The more complex influences of social problem-solving abilities and rumination-specifically brooding and reflection-on suicide intent is not well understood. We hypothesized that social problem solving would moderate the association between reflection and suicide intent, and mediate the influence of brooding on suicide intent. A convenience sample (N=186) of individuals hospitalized for recent suicide attempt was interviewed, assessing suicide intent, social problem solving, brooding, reflection and depression. Brooding and reflection were positively associated with suicide intent. The mediating, but not the moderating, hypothesis was supported. Brooding was not significant (β=0.15, t=1.92, p=0.06) with social problem solving controlled. Interventions to disengage rumination and improve social problem-solving skills are underscored. Copyright © 2017 Elsevier Inc. All rights reserved.

Cooperative Adaptive Output Regulation for Second-Order Nonlinear Multiagent Systems With Jointly Connected Switching Networks.

PubMed

Liu, Wei; Huang, Jie

2018-03-01

This paper studies the cooperative global robust output regulation problem for a class of heterogeneous second-order nonlinear uncertain multiagent systems with jointly connected switching networks. The main contributions consist of the following three aspects. First, we generalize the result of the adaptive distributed observer from undirected jointly connected switching networks to directed jointly connected switching networks. Second, by performing a new coordinate and input transformation, we convert our problem into the cooperative global robust stabilization problem of a more complex augmented system via the distributed internal model principle. Third, we solve the stabilization problem by a distributed state feedback control law. Our result is illustrated by the leader-following consensus problem for a group of Van der Pol oscillators.

Genetic Fuzzy Trees for Intelligent Control of Unmanned Combat Aerial Vehicles

NASA Astrophysics Data System (ADS)

Ernest, Nicholas D.

Fuzzy Logic Control is a powerful tool that has found great success in a variety of applications. This technique relies less on complex mathematics and more "expert knowledge" of a system to bring about high-performance, resilient, and efficient control through linguistic classification of inputs and outputs and if-then rules. Genetic Fuzzy Systems (GFSs) remove the need of this expert knowledge and instead rely on a Genetic Algorithm (GA) and have similarly found great success. However, the combination of these methods suffer severely from scalability; the number of rules required to control the system increases exponentially with the number of states the inputs and outputs can take. Therefor GFSs have thus far not been applicable to complex, artificial intelligence type problems. The novel Genetic Fuzzy Tree (GFT) method breaks down complex problems hierarchically, makes sub-decisions when possible, and thus greatly reduces the burden on the GA. This development significantly changes the field of possible applications for GFSs. Within this study, this is demonstrated through applying this technique to a difficult air combat problem. Looking forward to an autonomous Unmanned Combat Aerial Vehicle (UCAV) in the 2030 time-frame, it becomes apparent that the mission, flight, and ground controls will utilize the emerging paradigm of Intelligent Systems (IS); namely, the ability to learn, adapt, exhibit robustness in uncertain situations, make sense of the data collected in real-time and extrapolate when faced with scenarios significantly different from those used in training. LETHA (Learning Enhanced Tactical Handling Algorithm) was created to develop intelligent controllers for these advanced unmanned craft as the first GFT. A simulation space referred to as HADES (Hoplological Autonomous Defend and Engage Simulation) was created in which LETHA can train the UCAVs. Equipped with advanced sensors, a limited supply of Self-Defense Missiles (SDMs), and a recharging Laser Weapon System (LWS), these UCAVs can navigate a mission space, counter enemy threats, cope with losses in communications, and destroy mission-critical targets. Monte Carlo simulations of the resulting controllers were tested in mission scenarios that are distinct from the training scenarios to determine the training effectiveness in new environments and the presence of deep learning. Despite an incredibly large solution space, LETHA has demonstrated remarkable effectiveness in training intelligent controllers for the UCAV squadron and shown robustness to drastically changing states, uncertainty, and limited information while maintaining extreme levels of computational efficiency.

Characteristics of an ITS that evolves from tutor to operator's assistant. [intelligent tutoring system

NASA Technical Reports Server (NTRS)

Chu, R. W.; Mitchell, C. M.; Govindaraj, T.

1989-01-01

This paper discusses the motivation and goals of a research project which addresses the problems and issues of operator training in complex engineering sytems. The research proposes a tutor/aid paradigm for the design of an intelligent tutoring system (ITS) that evolves from a tutor to an operator's assistant for supervisory control of complex dynamic systems. Characteristics of an intelligent tutoring/aiding system are identified with respect to the representation of domain knowledge, the tutor's pedagogical structure, and the student knowledge representation. The research represents a first step in the design of an intelligent complex dynamic systems.

Mathematical concepts for modeling human behavior in complex man-machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.; Rouse, W. B.

1979-01-01

Many human behavior (e.g., manual control) models have been found to be inadequate for describing processes in certain real complex man-machine systems. An attempt is made to find a way to overcome this problem by examining the range of applicability of existing mathematical models with respect to the hierarchy of human activities in real complex tasks. Automobile driving is chosen as a baseline scenario, and a hierarchy of human activities is derived by analyzing this task in general terms. A structural description leads to a block diagram and a time-sharing computer analogy.

Baseline scheme for polarization preservation and control in the MEIC ion complex

DOE Office of Scientific and Technical Information (OSTI.GOV)

Derbenev, Yaroslav S.; Lin, Fanglei; Morozov, Vasiliy

2015-09-01

The scheme for preservation and control of the ion polarization in the Medium-energy Electron-Ion Collider (MEIC) has been under active development in recent years. The figure-8 configuration of the ion rings provides a unique capability to control the polarization of any ion species including deuterons by means of "weak" solenoids rotating the particle spins by small angles. Insertion of "weak" solenoids into the magnetic lattices of the booster and collider rings solves the problem of polarization preservation during acceleration of the ion beam. Universal 3D spin rotators designed on the basis of "weak" solenoids allow one to obtain any polarizationmore » orientation at an interaction point of MEIC. This paper presents the baseline scheme for polarization preservation and control in the MEIC ion complex.« less

The MYO6 interactome reveals adaptor complexes coordinating early endosome and cytoskeletal dynamics.

PubMed

O'Loughlin, Thomas; Masters, Thomas A; Buss, Folma

2018-04-01

The intracellular functions of myosin motors requires a number of adaptor molecules, which control cargo attachment, but also fine-tune motor activity in time and space. These motor-adaptor-cargo interactions are often weak, transient or highly regulated. To overcome these problems, we use a proximity labelling-based proteomics strategy to map the interactome of the unique minus end-directed actin motor MYO6. Detailed biochemical and functional analysis identified several distinct MYO6-adaptor modules including two complexes containing RhoGEFs: the LIFT (LARG-Induced F-actin for Tethering) complex that controls endosome positioning and motility through RHO-driven actin polymerisation; and the DISP (DOCK7-Induced Septin disPlacement) complex, a novel regulator of the septin cytoskeleton. These complexes emphasise the role of MYO6 in coordinating endosome dynamics and cytoskeletal architecture. This study provides the first in vivo interactome of a myosin motor protein and highlights the power of this approach in uncovering dynamic and functionally diverse myosin motor complexes. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

DNA - peptide polyelectrolyte complexes: Phase control by hybridization

NASA Astrophysics Data System (ADS)

Vieregg, Jeffrey; Lueckheide, Michael; Marciel, Amanda; Leon, Lorraine; Tirrell, Matthew

DNA is one of the most highly-charged molecules known, and interacts strongly with charged molecules in the cell. Condensation of long double-stranded DNA is one of the classic problems of biophysics, but the polyelectrolyte behavior of short and/or single-stranded nucleic acids has attracted far less study despite its importance for both biological and engineered systems. We report here studies of DNA oligonucleotides complexed with cationic peptides and polyamines. As seen previously for longer sequences, double-stranded oligonucleotides form solid precipitates, but single-stranded oligonucleotides instead undergo liquid-liquid phase separation to form coacervate droplets. Complexed oligonucleotides remain competent for hybridization, and display sequence-dependent environmental response. We observe similar behavior for RNA oligonucleotides, and methylphosphonate substitution of the DNA backbone indicates that nucleic acid charge density controls whether liquid or solid complexes are formed. Liquid-liquid phase separations of this type have been implicated in formation of membraneless organelles in vivo, and have been suggested as protocells in early life scenarios; oligonucleotides offer an excellent method to probe the physics controlling these phenomena.

Atomic switch networks as complex adaptive systems

NASA Astrophysics Data System (ADS)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

Hierarchical Control Using Networks Trained with Higher-Level Forward Models

PubMed Central

Wayne, Greg; Abbott, L.F.

2015-01-01

We propose and develop a hierarchical approach to network control of complex tasks. In this approach, a low-level controller directs the activity of a “plant,” the system that performs the task. However, the low-level controller may only be able to solve fairly simple problems involving the plant. To accomplish more complex tasks, we introduce a higher-level controller that controls the lower-level controller. We use this system to direct an articulated truck to a specified location through an environment filled with static or moving obstacles. The final system consists of networks that have memorized associations between the sensory data they receive and the commands they issue. These networks are trained on a set of optimal associations that are generated by minimizing cost functions. Cost function minimization requires predicting the consequences of sequences of commands, which is achieved by constructing forward models, including a model of the lower-level controller. The forward models and cost minimization are only used during training, allowing the trained networks to respond rapidly. In general, the hierarchical approach can be extended to larger numbers of levels, dividing complex tasks into more manageable sub-tasks. The optimization procedure and the construction of the forward models and controllers can be performed in similar ways at each level of the hierarchy, which allows the system to be modified to perform other tasks, or to be extended for more complex tasks without retraining lower-levels. PMID:25058706

Writing Expertise and Second-Language Proficiency.

ERIC Educational Resources Information Center

Cumming, Alister

1989-01-01

Assessment of the English writing proficiency of 23 native French speaking students on 3 composition tasks found variance in the qualities of written texts and problem-solving behaviors. Writing expertise was found to affect discourse organization and content, writing complexity, heuristic strategies, and control strategies, while second-language…

Using mobile probes to inform and measure the effectiveness of macroscopic traffic control strategies on urban networks.

DOT National Transportation Integrated Search

2015-06-01

Urban traffic congestion is a problem that plagues many cities in the United States. Testing strategies to alleviate this : congestion is especially challenging due to the difficulty of modeling complex urban traffic networks. However, recent work ha...

BFV-Complex and Higher Homotopy Structures

NASA Astrophysics Data System (ADS)

Schätz, Florian

2009-03-01

We present a connection between the BFV-complex (abbreviation for Batalin-Fradkin-Vilkovisky complex) and the strong homotopy Lie algebroid associated to a coisotropic submanifold of a Poisson manifold. We prove that the latter structure can be derived from the BFV-complex by means of homotopy transfer along contractions. Consequently the BFV-complex and the strong homotopy Lie algebroid structure are L ∞ quasi-isomorphic and control the same formal deformation problem. However there is a gap between the non-formal information encoded in the BFV-complex and in the strong homotopy Lie algebroid respectively. We prove that there is a one-to-one correspondence between coisotropic submanifolds given by graphs of sections and equivalence classes of normalized Maurer-Cartan elemens of the BFV-complex. This does not hold if one uses the strong homotopy Lie algebroid instead.

Maximum Entropy/Optimal Projection (MEOP) control design synthesis: Optimal quantification of the major design tradeoffs

NASA Technical Reports Server (NTRS)

Hyland, D. C.; Bernstein, D. S.

1987-01-01

The underlying philosophy and motivation of the optimal projection/maximum entropy (OP/ME) stochastic modeling and reduced control design methodology for high order systems with parameter uncertainties are discussed. The OP/ME design equations for reduced-order dynamic compensation including the effect of parameter uncertainties are reviewed. The application of the methodology to several Large Space Structures (LSS) problems of representative complexity is illustrated.

Controllability and observability of Boolean networks arising from biology

NASA Astrophysics Data System (ADS)

Li, Rui; Yang, Meng; Chu, Tianguang

2015-02-01

Boolean networks are currently receiving considerable attention as a computational scheme for system level analysis and modeling of biological systems. Studying control-related problems in Boolean networks may reveal new insights into the intrinsic control in complex biological systems and enable us to develop strategies for manipulating biological systems using exogenous inputs. This paper considers controllability and observability of Boolean biological networks. We propose a new approach, which draws from the rich theory of symbolic computation, to solve the problems. Consequently, simple necessary and sufficient conditions for reachability, controllability, and observability are obtained, and algorithmic tests for controllability and observability which are based on the Gröbner basis method are presented. As practical applications, we apply the proposed approach to several different biological systems, namely, the mammalian cell-cycle network, the T-cell activation network, the large granular lymphocyte survival signaling network, and the Drosophila segment polarity network, gaining novel insights into the control and/or monitoring of the specific biological systems.

Breakdowns in Coordination Between Air Traffic Controllers

NASA Technical Reports Server (NTRS)

Bearman, Chris; Orasanu, Judith; Miller, Ronald C.

2011-01-01

This talk outlines the complexity of coordination in air traffic control, introduces the NextGen technologies, identifies common causes for coordination breakdowns in air traffic control and examines whether these causes are likely to be reduced with the introduction of NextGen technologies. While some of the common causes of breakdowns will be reduced in a NextGen environment this conclusion should be drawn carefully given the current stage of development of the technologies and the observation that new technologies often shift problems rather than reduce them.

From path models to commands during additive printing of large-scale architectural designs

NASA Astrophysics Data System (ADS)

Chepchurov, M. S.; Zhukov, E. M.; Yakovlev, E. A.; Matveykin, V. G.

2018-05-01

The article considers the problem of automation of the formation of large complex parts, products and structures, especially for unique or small-batch objects produced by a method of additive technology [1]. Results of scientific research in search for the optimal design of a robotic complex, its modes of operation (work), structure of its control helped to impose the technical requirements on the technological process for manufacturing and design installation of the robotic complex. Research on virtual models of the robotic complexes allowed defining the main directions of design improvements and the main goal (purpose) of testing of the the manufactured prototype: checking the positioning accuracy of the working part.

Adaptive exponential synchronization of complex-valued Cohen-Grossberg neural networks with known and unknown parameters.

PubMed

Hu, Jin; Zeng, Chunna

2017-02-01

The complex-valued Cohen-Grossberg neural network is a special kind of complex-valued neural network. In this paper, the synchronization problem of a class of complex-valued Cohen-Grossberg neural networks with known and unknown parameters is investigated. By using Lyapunov functionals and the adaptive control method based on parameter identification, some adaptive feedback schemes are proposed to achieve synchronization exponentially between the drive and response systems. The results obtained in this paper have extended and improved some previous works on adaptive synchronization of Cohen-Grossberg neural networks. Finally, two numerical examples are given to demonstrate the effectiveness of the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonparametric method for failures diagnosis in the actuating subsystem of aircraft control system

NASA Astrophysics Data System (ADS)

Terentev, M. N.; Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

2018-02-01

In this paper we design a nonparametric method for failures diagnosis in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on analytical nonparametric one-step-ahead state prediction approach. This makes it possible to predict the behavior of unidentified and failure dynamic systems, to weaken the requirements to control signals, and to reduce the diagnostic time and problem complexity.

Multicriteria hierarchical iterative interactive algorithm for organizing operational modes of large heat supply systems

NASA Astrophysics Data System (ADS)

Korotkova, T. I.; Popova, V. I.

2017-11-01

The generalized mathematical model of decision-making in the problem of planning and mode selection providing required heat loads in a large heat supply system is considered. The system is multilevel, decomposed into levels of main and distribution heating networks with intermediate control stages. Evaluation of the effectiveness, reliability and safety of such a complex system is carried out immediately according to several indicators, in particular pressure, flow, temperature. This global multicriteria optimization problem with constraints is decomposed into a number of local optimization problems and the coordination problem. An agreed solution of local problems provides a solution to the global multicriterion problem of decision making in a complex system. The choice of the optimum operational mode of operation of a complex heat supply system is made on the basis of the iterative coordination process, which converges to the coordinated solution of local optimization tasks. The interactive principle of multicriteria task decision-making includes, in particular, periodic adjustment adjustments, if necessary, guaranteeing optimal safety, reliability and efficiency of the system as a whole in the process of operation. The degree of accuracy of the solution, for example, the degree of deviation of the internal air temperature from the required value, can also be changed interactively. This allows to carry out adjustment activities in the best way and to improve the quality of heat supply to consumers. At the same time, an energy-saving task is being solved to determine the minimum required values of heads at sources and pumping stations.

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

NASA Astrophysics Data System (ADS)

Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

2015-08-01

This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

Multirate control with incomplete information over Profibus-DP network

NASA Astrophysics Data System (ADS)

Salt, J.; Casanova, V.; Cuenca, A.; Pizá, R.

2014-07-01

When a process field bus-decentralized peripherals (Profibus-DP) network is used in an industrial environment, a deterministic behaviour is usually claimed. However, due to some concerns such as bandwidth limitations, lack of synchronisation among different clocks and existence of time-varying delays, a more complex problem must be faced. This problem implies the transmission of irregular and, even, random sequences of incomplete information. The main consequence of this issue is the appearance of different sampling periods at different network devices. In this paper, this aspect is checked by means of a detailed Profibus-DP timescale study. In addition, in order to deal with the different periods, a delay-dependent dual-rate proportional-integral-derivative control is introduced. Stability for the proposed control system is analysed in terms of linear matrix inequalities.

Neuropsychological study of FASD in a sample of American Indian children: processing simple versus complex information.

PubMed

Aragón, Alfredo S; Kalberg, Wendy O; Buckley, David; Barela-Scott, Lindsey M; Tabachnick, Barbara G; May, Philip A

2008-12-01

Although a large body of literature exists on cognitive functioning in alcohol-exposed children, it is unclear if there is a signature neuropsychological profile in children with Fetal Alcohol Spectrum Disorders (FASD). This study assesses cognitive functioning in children with FASD from several American Indian reservations in the Northern Plains States, and it applies a hierarchical model of simple versus complex information processing to further examine cognitive function. We hypothesized that complex tests would discriminate between children with FASD and culturally similar controls, while children with FASD would perform similar to controls on relatively simple tests. Our sample includes 32 control children and 24 children with a form of FASD [fetal alcohol syndrome (FAS) = 10, partial fetal alcohol syndrome (PFAS) = 14]. The test battery measures general cognitive ability, verbal fluency, executive functioning, memory, and fine-motor skills. Many of the neuropsychological tests produced results consistent with a hierarchical model of simple versus complex processing. The complexity of the tests was determined "a priori" based on the number of cognitive processes involved in them. Multidimensional scaling was used to statistically analyze the accuracy of classifying the neurocognitive tests into a simple versus complex dichotomy. Hierarchical logistic regression models were then used to define the contribution made by complex versus simple tests in predicting the significant differences between children with FASD and controls. Complex test items discriminated better than simple test items. The tests that conformed well to the model were the Verbal Fluency, Progressive Planning Test (PPT), the Lhermitte memory tasks, and the Grooved Pegboard Test (GPT). The FASD-grouped children, when compared with controls, demonstrated impaired performance on letter fluency, while their performance was similar on category fluency. On the more complex PPT trials (problems 5 to 8), as well as the Lhermitte logical tasks, the FASD group performed the worst. The differential performance between children with FASD and controls was evident across various neuropsychological measures. The children with FASD performed significantly more poorly on the complex tasks than did the controls. The identification of a neurobehavioral profile in children with prenatal alcohol exposure will help clinicians identify and diagnose children with FASD.

Global planning of several plants

NASA Technical Reports Server (NTRS)

Bescos, Sylvie

1992-01-01

This paper discusses an attempt to solve the problem of planning several pharmaceutical plants at a global level. The interest in planning at this level is to increase the global control over the production process, to improve its overall efficiency, and to reduce the need for interaction between production plants. In order to reduce the complexity of this problem and to make it tractable, some abstractions were made. Based on these abstractions, a prototype is being developed within the framework of the EUREKA project PROTOS, using Constraint Logic Programming techniques.

Development of an exercise intervention for the prevention of musculoskeletal shoulder problems after breast cancer treatment: the prevention of shoulder problems trial (UK PROSPER).

PubMed

Richmond, Helen; Lait, Clare; Srikesavan, Cynthia; Williamson, Esther; Moser, Jane; Newman, Meredith; Betteley, Lauren; Fordham, Beth; Rees, Sophie; Lamb, Sarah E; Bruce, Julie

2018-06-18

Musculoskeletal shoulder problems are common after breast cancer treatment. There is some evidence to suggest that early postoperative exercise is safe and may improve shoulder function. We describe the development and delivery of a complex intervention for evaluation within a randomised controlled trial (RCT), designed to target prevention of musculoskeletal shoulder problems after breast cancer surgery (The Prevention of Shoulder Problems Trial; PROSPER). A pragmatic, multicentre RCT to compare the clinical and cost-effectiveness of best practice usual care versus a physiotherapy-led exercise and behavioural support intervention in women at high risk of shoulder problems after breast cancer treatment. PROSPER will recruit 350 women from approximately 15 UK centres, with follow-up at 6 and 12 months. The primary outcome is shoulder function at 12 months; secondary outcomes include postoperative pain, health related quality of life, adverse events and healthcare resource use. A multi-phased approach was used to develop the PROSPER intervention which was underpinned by existing evidence and modified for implementation after input from clinical experts and women with breast cancer. The intervention was tested and refined further after qualitative interviews with patients newly diagnosed with breast cancer; a pilot RCT was then conducted at three UK clinical centres. The PROSPER intervention incorporates three main components: shoulder-specific exercises targeting range of movement and strength; general physical activity; and behavioural strategies to encourage adherence and support exercise behaviour. The final PROSPER intervention is fully manualised with clear, documented pathways for clinical assessment, exercise prescription, use of behavioural strategies, and with guidance for treatment of postoperative complications. This paper adheres to TIDieR and CERT recommendations for the transparent, comprehensive and explicit reporting of complex interventions. International Standard Randomised Controlled Trial Number: ISRCTN 35358984 .

Prefrontal and parietal activity is modulated by the rule complexity of inductive reasoning and can be predicted by a cognitive model.

PubMed

Jia, Xiuqin; Liang, Peipeng; Shi, Lin; Wang, Defeng; Li, Kuncheng

2015-01-01

In neuroimaging studies, increased task complexity can lead to increased activation in task-specific regions or to activation of additional regions. How the brain adapts to increased rule complexity during inductive reasoning remains unclear. In the current study, three types of problems were created: simple rule induction (i.e., SI, with rule complexity of 1), complex rule induction (i.e., CI, with rule complexity of 2), and perceptual control. Our findings revealed that increased activations accompany increased rule complexity in the right dorsal lateral prefrontal cortex (DLPFC) and medial posterior parietal cortex (precuneus). A cognitive model predicted both the behavioral and brain imaging results. The current findings suggest that neural activity in frontal and parietal regions is modulated by rule complexity, which may shed light on the neural mechanisms of inductive reasoning. Copyright © 2014. Published by Elsevier Ltd.

State analysis requirements database for engineering complex embedded systems

NASA Technical Reports Server (NTRS)

Bennett, Matthew B.; Rasmussen, Robert D.; Ingham, Michel D.

2004-01-01

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer's intent, potentially leading to software errors. This problem is addressed by a systems engineering tool called the State Analysis Database, which provides a tool for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using the State Analysis Database.

Manufacturing DTaP-based combination vaccines: industrial challenges around essential public health tools.

PubMed

Vidor, Emmanuel; Soubeyrand, Benoit

2016-12-01

The manufacture of DTP-backboned combination vaccines is complex, and vaccine quality is evaluated by both batch composition and conformance of manufacturing history. Since their first availability, both the manufacturing regulations for DTP combination vaccines and their demand have evolved significantly. This has resulted in a constant need to modify manufacturing and quality control processes. Areas covered: Regulations that govern the manufacture of complex vaccines can be inconsistent between countries and need to be aligned with the regulatory requirements that apply in all countries of distribution. Changes in product mix and quantities can lead to uncertainty in vaccine supply maintenance. These problems are discussed in the context of the importance of these products as essential public health tools. Expert commentary: Increasing demand for complex vaccines globally has led to problems in supply due to intrinsically complex manufacturing and regulatory procedures. Vaccine manufacturers are fully engaged in the resolution of these challenges, but currently changes in demand need ideally to be anticipated approximately 3 years in advance due to long production cycle times.

Quality data collection and management technology of aerospace complex product assembly process

NASA Astrophysics Data System (ADS)

Weng, Gang; Liu, Jianhua; He, Yongxi; Zhuang, Cunbo

2017-04-01

Aiming at solving problems of difficult management and poor traceability for discrete assembly process quality data, a data collection and management method is proposed which take the assembly process and BOM as the core. Data collection method base on workflow technology, data model base on BOM and quality traceability of assembly process is included in the method. Finally, assembly process quality data management system is developed and effective control and management of quality information for complex product assembly process is realized.

Alternative management technologies for postharvest disease control: the journey from simplicity to complexity

USDA-ARS?s Scientific Manuscript database

It has been often stated that we have moved from an age of chemistry to an age of biology. The ease of sequencing genomes and obtaining related genotypic, transcriptomic, proteomic, and metabolomics information is leading to the development of new commercial technologies where problems are solved "...

Simple Logic for Big Problems: An Inside Look at Relational Databases.

ERIC Educational Resources Information Center

Seba, Douglas B.; Smith, Pat

1982-01-01

Discusses database design concept termed "normalization" (process replacing associations between data with associations in two-dimensional tabular form) which results in formation of relational databases (they are to computers what dictionaries are to spoken languages). Applications of the database in serials control and complex systems…

Simulations for the Test Flight of an Experimental HALE Aircraft

DTIC Science & Technology

2011-06-01

as a plant representation for HALE aircraft control design. It focuses on a reduced number of states to represent the complex nonlinear problem...Atkins, Ella M., Shearer, Christopher M. and Nathan A. Pitcher . “X-HALE: A Very Flexible UAV for Nonlinear Aeroelastic Tests.” (AIAA 2010-2715), April

Sub-Lexical Reading Intervention in a Student with Dyslexia and Asperger's Disorder

ERIC Educational Resources Information Center

Wright, Craig; Conlon, Elizabeth; Wright, Michalle; Dyck, Murray

2011-01-01

Dyslexia is a common presenting condition in clinic and educational settings. Unlike the homogenous groups used in randomised trials, educators typically manage children who have multiple developmental problems. Investigations are required into how these complex cases respond to treatment identified as efficacious by controlled trials. This study…

Increasingly automated procedure acquisition in dynamic systems

NASA Technical Reports Server (NTRS)

Mathe, Nathalie; Kedar, Smadar

1992-01-01

Procedures are widely used by operators for controlling complex dynamic systems. Currently, most development of such procedures is done manually, consuming a large amount of paper, time, and manpower in the process. While automated knowledge acquisition is an active field of research, not much attention has been paid to the problem of computer-assisted acquisition and refinement of complex procedures for dynamic systems. The Procedure Acquisition for Reactive Control Assistant (PARC), which is designed to assist users in more systematically and automatically encoding and refining complex procedures. PARC is able to elicit knowledge interactively from the user during operation of the dynamic system. We categorize procedure refinement into two stages: diagnosis - diagnose the failure and choose a repair - and repair - plan and perform the repair. The basic approach taken in PARC is to assist the user in all steps of this process by providing increased levels of assistance with layered tools. We illustrate the operation of PARC in refining procedures for the control of a robot arm.

Grounding explanations in evolving, diagnostic situations

NASA Technical Reports Server (NTRS)

Johannesen, Leila J.; Cook, Richard I.; Woods, David D.

1994-01-01

Certain fields of practice involve the management and control of complex dynamic systems. These include flight deck operations in commercial aviation, control of space systems, anesthetic management during surgery or chemical or nuclear process control. Fault diagnosis of these dynamic systems generally must occur with the monitored process on-line and in conjunction with maintaining system integrity.This research seeks to understand in more detail what it means for an intelligent system to function cooperatively, or as a 'team player' in complex, dynamic environments. The approach taken was to study human practitioners engaged in the management of a complex, dynamic process: anesthesiologists during neurosurgical operations. The investigation focused on understanding how team members cooperate in management and fault diagnosis and comparing this interaction to the situation with an Artificial Intelligence(AI) system that provides diagnoses and explanations. Of particular concern was to study the ways in which practitioners support one another in keeping aware of relevant information concerning the state of the monitored process and of the problem solving process.

Optimal lunar soft landing trajectories using taboo evolutionary programming

NASA Astrophysics Data System (ADS)

Mutyalarao, M.; Raj, M. Xavier James

A safe lunar landing is a key factor to undertake an effective lunar exploration. Lunar lander consists of four phases such as launch phase, the earth-moon transfer phase, circumlunar phase and landing phase. The landing phase can be either hard landing or soft landing. Hard landing means the vehicle lands under the influence of gravity without any deceleration measures. However, soft landing reduces the vertical velocity of the vehicle before landing. Therefore, for the safety of the astronauts as well as the vehicle lunar soft landing with an acceptable velocity is very much essential. So it is important to design the optimal lunar soft landing trajectory with minimum fuel consumption. Optimization of Lunar Soft landing is a complex optimal control problem. In this paper, an analysis related to lunar soft landing from a parking orbit around Moon has been carried out. A two-dimensional trajectory optimization problem is attempted. The problem is complex due to the presence of system constraints. To solve the time-history of control parameters, the problem is converted into two point boundary value problem by using the maximum principle of Pontrygen. Taboo Evolutionary Programming (TEP) technique is a stochastic method developed in recent years and successfully implemented in several fields of research. It combines the features of taboo search and single-point mutation evolutionary programming. Identifying the best unknown parameters of the problem under consideration is the central idea for many space trajectory optimization problems. The TEP technique is used in the present methodology for the best estimation of initial unknown parameters by minimizing objective function interms of fuel requirements. The optimal estimation subsequently results into an optimal trajectory design of a module for soft landing on the Moon from a lunar parking orbit. Numerical simulations demonstrate that the proposed approach is highly efficient and it reduces the minimum fuel consumption. The results are compared with the available results in literature shows that the solution of present algorithm is better than some of the existing algorithms. Keywords: soft landing, trajectory optimization, evolutionary programming, control parameters, Pontrygen principle.

Effect of correlations on controllability transition in network control

PubMed Central

Nie, Sen; Wang, Xu-Wen; Wang, Bing-Hong; Jiang, Luo-Luo

2016-01-01

The network control problem has recently attracted an increasing amount of attention, owing to concerns including the avoidance of cascading failures of power-grids and the management of ecological networks. It has been proven that numerical control can be achieved if the number of control inputs exceeds a certain transition point. In the present study, we investigate the effect of degree correlation on the numerical controllability in networks whose topological structures are reconstructed from both real and modeling systems, and we find that the transition point of the number of control inputs depends strongly on the degree correlation in both undirected and directed networks with moderately sparse links. More interestingly, the effect of the degree correlation on the transition point cannot be observed in dense networks for numerical controllability, which contrasts with the corresponding result for structural controllability. In particular, for directed random networks and scale-free networks, the influence of the degree correlation is determined by the types of correlations. Our approach provides an understanding of control problems in complex sparse networks. PMID:27063294

Decentralized control of large flexible structures by joint decoupling

NASA Technical Reports Server (NTRS)

Su, Tzu-Jeng; Juang, Jer-Nan

1992-01-01

A decentralized control design method is presented for large complex flexible structures by using the idea of joint decoupling. The derivation is based on a coupled substructure state-space model, which is obtained from enforcing conditions of interface compatibility and equilibrium to the substructure state-space models. It is shown that by restricting the control law to be localized state feedback and by setting the joint actuator input commands to decouple joint 'degrees of freedom' (dof) from interior dof, the global structure control design problem can be decomposed into several substructure control design problems. The substructure control gains and substructure observers are designed based on modified substructure state-space models. The controllers produced by the proposed method can operate successfully at the individual substructure level as well as at the global structure level. Therefore, not only control design but also control implementation is decentralized. Stability and performance requirement of the closed-loop system can be achieved by using any existing state feedback control design method. A two-component mass-spring damper system and a three-truss structure are used as examples to demonstrate the proposed method.

A multiagent evolutionary algorithm for constraint satisfaction problems.

PubMed

Liu, Jing; Zhong, Weicai; Jiao, Licheng

2006-02-01

With the intrinsic properties of constraint satisfaction problems (CSPs) in mind, we divide CSPs into two types, namely, permutation CSPs and nonpermutation CSPs. According to their characteristics, several behaviors are designed for agents by making use of the ability of agents to sense and act on the environment. These behaviors are controlled by means of evolution, so that the multiagent evolutionary algorithm for constraint satisfaction problems (MAEA-CSPs) results. To overcome the disadvantages of the general encoding methods, the minimum conflict encoding is also proposed. Theoretical analyzes show that MAEA-CSPs has a linear space complexity and converges to the global optimum. The first part of the experiments uses 250 benchmark binary CSPs and 79 graph coloring problems from the DIMACS challenge to test the performance of MAEA-CSPs for nonpermutation CSPs. MAEA-CSPs is compared with six well-defined algorithms and the effect of the parameters is analyzed systematically. The second part of the experiments uses a classical CSP, n-queen problems, and a more practical case, job-shop scheduling problems (JSPs), to test the performance of MAEA-CSPs for permutation CSPs. The scalability of MAEA-CSPs along n for n-queen problems is studied with great care. The results show that MAEA-CSPs achieves good performance when n increases from 10(4) to 10(7), and has a linear time complexity. Even for 10(7)-queen problems, MAEA-CSPs finds the solutions by only 150 seconds. For JSPs, 59 benchmark problems are used, and good performance is also obtained.

Wellbeing and resilience: mechanisms of transmission of health and risk in parents with complex mental health problems and their offspring--The WARM Study.

PubMed

Harder, Susanne; Davidsen, Kirstine; MacBeth, Angus; Lange, Theis; Minnis, Helen; Andersen, Marianne Skovsager; Simonsen, Erik; Lundy, Jenna-Marie; Nyström-Hansen, Maja; Trier, Christopher Høier; Røhder, Katrine; Gumley, Andrew

2015-12-09

The WARM study is a longitudinal cohort study following infants of mothers with schizophrenia, bipolar disorder, depression and control from pregnancy to infant 1 year of age. Children of parents diagnosed with complex mental health problems including schizophrenia, bipolar disorder and depression, are at increased risk of developing mental health problems compared to the general population. Little is known regarding the early developmental trajectories of infants who are at ultra-high risk and in particular the balance of risk and protective factors expressed in the quality of early caregiver-interaction. We are establishing a cohort of pregnant women with a lifetime diagnosis of schizophrenia, bipolar disorder, major depressive disorder and a non-psychiatric control group. Factors in the parents, the infant and the social environment will be evaluated at 1, 4, 16 and 52 weeks in terms of evolution of very early indicators of developmental risk and resilience focusing on three possible environmental transmission mechanisms: stress, maternal caregiver representation, and caregiver-infant interaction. The study will provide data on very early risk developmental status and associated psychosocial risk factors, which will be important for developing targeted preventive interventions for infants of parents with severe mental disorder. NCT02306551, date of registration November 12, 2014.

Requirements Analysis and Modeling with Problem Frames and SysML: A Case Study

NASA Astrophysics Data System (ADS)

Colombo, Pietro; Khendek, Ferhat; Lavazza, Luigi

Requirements analysis based on Problem Frames is getting an increasing attention in the academic community and has the potential to become of relevant interest also for industry. However the approach lacks an adequate notational support and methodological guidelines, and case studies that demonstrate its applicability to problems of realistic complexity are still rare. These weaknesses may hinder its adoption. This paper aims at contributing towards the elimination of these weaknesses. We report on an experience in analyzing and specifying the requirements of a controller for traffic lights of an intersection using Problem Frames in combination with SysML. The analysis was performed by decomposing the problem, addressing the identified sub-problems, and recomposing them while solving the identified interferences. The experience allowed us to identify certain guidelines for decomposition and re-composition patterns.

Improving Multi-Objective Management of Water Quality Tipping Points: Revisiting the Classical Shallow Lake Problem

NASA Astrophysics Data System (ADS)

Quinn, J. D.; Reed, P. M.; Keller, K.

2015-12-01

Recent multi-objective extensions of the classical shallow lake problem are useful for exploring the conceptual and computational challenges that emerge when managing irreversible water quality tipping points. Building on this work, we explore a four objective version of the lake problem where a hypothetical town derives economic benefits from polluting a nearby lake, but at the risk of irreversibly tipping the lake into a permanently polluted state. The trophic state of the lake exhibits non-linear threshold dynamics; below some critical phosphorus (P) threshold it is healthy and oligotrophic, but above this threshold it is irreversibly eutrophic. The town must decide how much P to discharge each year, a decision complicated by uncertainty in the natural P inflow to the lake. The shallow lake problem provides a conceptually rich set of dynamics, low computational demands, and a high level of mathematical difficulty. These properties maximize its value for benchmarking the relative merits and limitations of emerging decision support frameworks, such as Direct Policy Search (DPS). Here, we explore the use of DPS as a formal means of developing robust environmental pollution control rules that effectively account for deeply uncertain system states and conflicting objectives. The DPS reformulation of the shallow lake problem shows promise in formalizing pollution control triggers and signposts, while dramatically reducing the computational complexity of the multi-objective pollution control problem. More broadly, the insights from the DPS variant of the shallow lake problem formulated in this study bridge emerging work related to socio-ecological systems management, tipping points, robust decision making, and robust control.

[Multiple colonic anastomoses in the surgical treatment of short bowel syndrome. A new technique].

PubMed

Robledo-Ogazón, Felipe; Becerril-Martínez, Guillermo; Hernández-Saldaña, Víctor; Zavala-Aznar, Marí Luisa; Bojalil-Durán, Luis

2008-01-01

Some surgical pathologies eventually require intestinal resection. This may lead to an extended procedure such as leaving 30 cm of proximal jejunum and left and sigmoid colon. One of the most important consequences of this type of resection is "intestinal failure" or short bowel syndrome. This complex syndrome leads to different metabolic and water and acid/base imbalances, as well as nutritional and immunological challenges along with the problem accompanying an abdomen subjected to many surgical procedures and high mortality. Many surgical techniques have been developed to improve quality of life of patients. We designed a non-transplant surgical approach and performed the procedure on two patients with postoperative short bowel syndrome with <40 cm of proximal jejunum and left colon. There are a variety of non-transplant surgical procedures that, due to their complex technique or high mortality rate, have not resolved this important problem. However, the technique we present in this work can be performed by a large number of surgeons. The procedure has a low morbimortality rate and offers the opportunity for better control of metabolic and acid/base balance, intestinal transit and proper nutrition. We consider that this technique offers a new alternative for the complex management required by patients with short bowel syndrome and facilitates their long-term nutritional control.

The Challenge of Cardiovascular Diseases and Diabetes to Public Health: A Study Based on Qualitative Systemic Approach

PubMed Central

Carvalho, Marilia Sá; Coeli, Claudia Medina; Chor, Dóra; Pinheiro, Rejane Sobrino; da Fonseca, Maria de Jesus Mendes; de Sá Carvalho, Luiz Carlos

2015-01-01

The most common modeling approaches to understanding incidence, prevalence and control of chronic diseases in populations, such as statistical regression models, are limited when it comes to dealing with the complexity of those problems. Those complex adaptive systems have characteristics such as emerging properties, self-organization and feedbacks, which structure the system stability and resistance to changes. Recently, system science approaches have been proposed to deal with the range, complexity, and multifactor nature of those public health problems. In this paper we applied a multilevel systemic approach to create an integrated, coherent, and increasingly precise conceptual framework, capable of aggregating different partial or specialized studies, based on the challenges of the Longitudinal Study of Adult Health – ELSA-Brasil. The failure to control blood pressure found in several of the study's subjects was discussed, based on the proposed model, analyzing different loops, time lags, and feedback that influence this outcome in a population with high educational level, with reasonably good health services access. We were able to identify the internal circularities and cycles that generate the system’s resistance to change. We believe that this study can contribute to propose some new possibilities of the research agenda and to the discussion of integrated actions in the field of public health. PMID:26171854

Observer-Based Adaptive Fault-Tolerant Tracking Control of Nonlinear Nonstrict-Feedback Systems.

PubMed

Wu, Chengwei; Liu, Jianxing; Xiong, Yongyang; Wu, Ligang

2017-06-28

This paper studies an output-based adaptive fault-tolerant control problem for nonlinear systems with nonstrict-feedback form. Neural networks are utilized to identify the unknown nonlinear characteristics in the system. An observer and a general fault model are constructed to estimate the unavailable states and describe the fault, respectively. Adaptive parameters are constructed to overcome the difficulties in the design process for nonstrict-feedback systems. Meanwhile, dynamic surface control technique is introduced to avoid the problem of ''explosion of complexity''. Furthermore, based on adaptive backstepping control method, an output-based adaptive neural tracking control strategy is developed for the considered system against actuator fault, which can ensure that all the signals in the resulting closed-loop system are bounded, and the system output signal can be regulated to follow the response of the given reference signal with a small error. Finally, the simulation results are provided to validate the effectiveness of the control strategy proposed in this paper.

Control theory based airfoil design using the Euler equations

NASA Technical Reports Server (NTRS)

Jameson, Antony; Reuther, James

1994-01-01

This paper describes the implementation of optimization techniques based on control theory for airfoil design. In our previous work it was shown that control theory could be employed to devise effective optimization procedures for two-dimensional profiles by using the potential flow equation with either a conformal mapping or a general coordinate system. The goal of our present work is to extend the development to treat the Euler equations in two-dimensions by procedures that can readily be generalized to treat complex shapes in three-dimensions. Therefore, we have developed methods which can address airfoil design through either an analytic mapping or an arbitrary grid perturbation method applied to a finite volume discretization of the Euler equations. Here the control law serves to provide computationally inexpensive gradient information to a standard numerical optimization method. Results are presented for both the inverse problem and drag minimization problem.

Neuromorphic walking gait control.

PubMed

Still, Susanne; Hepp, Klaus; Douglas, Rodney J

2006-03-01

We present a neuromorphic pattern generator for controlling the walking gaits of four-legged robots which is inspired by central pattern generators found in the nervous system and which is implemented as a very large scale integrated (VLSI) chip. The chip contains oscillator circuits that mimic the output of motor neurons in a strongly simplified way. We show that four coupled oscillators can produce rhythmic patterns with phase relationships that are appropriate to generate all four-legged animal walking gaits. These phase relationships together with frequency and duty cycle of the oscillators determine the walking behavior of a robot driven by the chip, and they depend on a small set of stationary bias voltages. We give analytic expressions for these dependencies. This chip reduces the complex, dynamic inter-leg control problem associated with walking gait generation to the problem of setting a few stationary parameters. It provides a compact and low power solution for walking gait control in robots.

The Integrated Airframe/Propulsion Control System Architecture program (IAPSA)

NASA Technical Reports Server (NTRS)

Palumbo, Daniel L.; Cohen, Gerald C.; Meissner, Charles W.

1990-01-01

The Integrated Airframe/Propulsion Control System Architecture program (IAPSA) is a two-phase program which was initiated by NASA in the early 80s. The first phase, IAPSA 1, studied different architectural approaches to the problem of integrating engine control systems with airframe control systems in an advanced tactical fighter. One of the conclusions of IAPSA 1 was that the technology to construct a suitable system was available, yet the ability to create these complex computer architectures has outpaced the ability to analyze the resulting system's performance. With this in mind, the second phase of IAPSA approached the same problem with the added constraint that the system be designed for validation. The intent of the design for validation requirement is that validation requirements should be shown to be achievable early in the design process. IAPSA 2 has demonstrated that despite diligent efforts, integrated systems can retain characteristics which are difficult to model and, therefore, difficult to validate.

Research and simulation of the decoupling transformation in AC motor vector control

NASA Astrophysics Data System (ADS)

He, Jiaojiao; Zhao, Zhongjie; Liu, Ken; Zhang, Yongping; Yao, Tuozhong

2018-04-01

Permanent magnet synchronous motor (PMSM) is a nonlinear, strong coupling, multivariable complex object, and transformation decoupling can solve the coupling problem of permanent magnet synchronous motor. This paper gives a permanent magnet synchronous motor (PMSM) mathematical model, introduces the permanent magnet synchronous motor vector control coordinate transformation in the process of modal matrix inductance matrix transform through the matrix related knowledge of different coordinates of diagonalization, which makes the coupling between the independent, realize the control of motor current and excitation the torque current coupling separation, and derived the coordinate transformation matrix, the thought to solve the coupling problem of AC motor. Finally, in the Matlab/Simulink environment, through the establishment and combination between the PMSM ontology, coordinate conversion module, built the simulation model of permanent magnet synchronous motor vector control, introduces the model of each part, and analyzed the simulation results.

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

PubMed Central

Süß, Heinz-Martin; Kretzschmar, André

2018-01-01

The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell’s investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory (Tailorshop; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario (FSYS; i.e., a complex artificial world system). The results indicate that reasoning – specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) – are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications. PMID:29867627

Co-evolution for Problem Simplification

NASA Technical Reports Server (NTRS)

Haith, Gary L.; Lohn, Jason D.; Cplombano, Silvano P.; Stassinopoulos, Dimitris

1999-01-01

This paper explores a co-evolutionary approach applicable to difficult problems with limited failure/success performance feedback. Like familiar "predator-prey" frameworks this algorithm evolves two populations of individuals - the solutions (predators) and the problems (prey). The approach extends previous work by rewarding only the problems that match their difficulty to the level of solut,ion competence. In complex problem domains with limited feedback, this "tractability constraint" helps provide an adaptive fitness gradient that, effectively differentiates the candidate solutions. The algorithm generates selective pressure toward the evolution of increasingly competent solutions by rewarding solution generality and uniqueness and problem tractability and difficulty. Relative (inverse-fitness) and absolute (static objective function) approaches to evaluating problem difficulty are explored and discussed. On a simple control task, this co-evolutionary algorithm was found to have significant advantages over a genetic algorithm with either a static fitness function or a fitness function that changes on a hand-tuned schedule.

Models of resource allocation optimization when solving the control problems in organizational systems

NASA Astrophysics Data System (ADS)

Menshikh, V.; Samorokovskiy, A.; Avsentev, O.

2018-03-01

The mathematical model of optimizing the allocation of resources to reduce the time for management decisions and algorithms to solve the general problem of resource allocation. The optimization problem of choice of resources in organizational systems in order to reduce the total execution time of a job is solved. This problem is a complex three-level combinatorial problem, for the solving of which it is necessary to implement the solution to several specific problems: to estimate the duration of performing each action, depending on the number of performers within the group that performs this action; to estimate the total execution time of all actions depending on the quantitative composition of groups of performers; to find such a distribution of the existing resource of performers in groups to minimize the total execution time of all actions. In addition, algorithms to solve the general problem of resource allocation are proposed.

[Critical reflexion on quality improvement and networking].

PubMed

Adler, R

2012-06-06

Qualitiy-control and networking are two issues of debate in modern medicine. The origin of these terms is not to be found in medicine, but rather in industry. However their naive transfer to the field of medicine causes damage. It is relatively easy to test industrial products for their quality. Dealing with meaningful medical problems is far too complex. Simple data such as blood pressure, HbA1c, etc. may be assessed. The only means of quality-control of complex medical situations and actions are ward rounds by attending physicians, case presentations at staff meetings, etc. Issues of clinical quality-control are discussed on the basis of the history of an aged couple. Furthermore a personal clinical experience illustrates how doctors create a useful network with other physicians and how they eliminate "useless" colleagues from their network. Economists should have no influence or impact whatsoever on the quality-control and networking of physicians.

[Induced abortion: a vulnerable public health problem].

PubMed

Requena, M

1991-03-01

Induced abortion is an urgent public health problem that can be controlled if it is approached in its true complexity and with a social and humanist perspective. Induced abortion has been discussed in Chile since the last century, but not always openly. Abortion is not just an individual and collective medical problem, it is also an ethical, religious, legal, demographic, political, and psychological problem. Above all it is a problem of human rights. In the past 60 years, more than 50 countries representing 76% of the world population have liberalized their abortion legislation. Around 980 million women have some degrees of access of legal abortion. The magnitude of illegal abortion is difficult to determine because of the desire of women to hide their experiences. Estimates of the incidence of abortion in Chile made some 25 years ago are no longer valid because of the numerous social changes in the intervening years. The number of abortions in Chile in 1987 was estimated using an indirect residual method at 195,441, of which 90%, or 175,897, were induced. By this estimate, 38.8% of pregnancies in Chile end in abortion. Data on hospitalizations for complications of induced abortion show an increase from 13.9/1000 fertile aged women in 1940 to 29.1 in 1965. By 1987, with increased contraceptive usage, the rate declined to 10.5 abortions per 1000 fertile aged women. The cost of hospitalization for abortion complications in 1987, despite the decline, was still estimated at US $4.3 million, a large sum in an era of declining health resources. The problem of induced abortion can be analyzed by placing it in the context of elements affecting the desire to control fertility. 4 complexes of variables are involved: those affecting the supply of contraceptive, the demand for contraceptives, the various costs of fertility control measure, and alternatives to fertility control for satisfying various needs. The analysis is further complicated when efforts are made to understand the dynamics of the process. Awareness of fertility control is a social process that matures slowly. Contraception and abortion have different significance for fertility control, with contraception preventing pregnancy and abortion is a sense curing it. Chile has progressed far in its fertility control awareness. 2/3 of sexually active women use some form of contraception. At the same time, induced abortion is also used. It is estimated that 58% of abortions occur after a contraceptive failure. It appears that recourse to abortion would be minimized if strategies centered on supply of contraceptives were complemented by stronger efforts to develop awareness of fertility control. Delivery of contraceptives should be accompanied by complete information on their effective use. Efforts should be targeted especially at groups at high risk abortion, including adolescents and women hospitalized for complications.

Air Defense: A Computer Game for Research in Human Performance.

DTIC Science & Technology

1981-07-01

warfare (ANW) threat analysis. M’ajor elements of the threat analysis problem \\\\,erc eoibedded in an interactive air detoense game controlled by a...The game requires sustained attention to a complex and interactive "hostile" environment, provides proper experimental control of relevant variables...AD-A102 725 NAVY PERSONNEL RESEARCH AND DEVELOPMENT CENTER SAN DETC F/6 5/10 AIR DEFENSE: A COMPUTER GAME FOR RESEARCH IN HUMAN PERFORMANCE.(U) JUL

Vista goes online: Decision-analytic systems for real-time decision-making in mission control

NASA Technical Reports Server (NTRS)

Barry, Matthew; Horvitz, Eric; Ruokangas, Corinne; Srinivas, Sampath

1994-01-01

The Vista project has centered on the use of decision-theoretic approaches for managing the display of critical information relevant to real-time operations decisions. The Vista-I project originally developed a prototype of these approaches for managing flight control displays in the Space Shuttle Mission Control Center (MCC). The follow-on Vista-II project integrated these approaches in a workstation program which currently is being certified for use in the MCC. To our knowledge, this will be the first application of automated decision-theoretic reasoning techniques for real-time spacecraft operations. We shall describe the development and capabilities of the Vista-II system, and provide an overview of the use of decision-theoretic reasoning techniques to the problems of managing the complexity of flight controller displays. We discuss the relevance of the Vista techniques within the MCC decision-making environment, focusing on the problems of detecting and diagnosing spacecraft electromechanical subsystems component failures with limited information, and the problem of determining what control actions should be taken in high-stakes, time-critical situations in response to a diagnosis performed under uncertainty. Finally, we shall outline our current research directions for follow-on projects.

How are things adding up? Neural differences between arithmetic operations are due to general problem solving strategies.

PubMed

Tschentscher, Nadja; Hauk, Olaf

2014-05-15

A number of previous studies have interpreted differences in brain activation between arithmetic operation types (e.g. addition and multiplication) as evidence in favor of distinct cortical representations, processes or neural systems. It is still not clear how differences in general task complexity contribute to these neural differences. Here, we used a mental arithmetic paradigm to disentangle brain areas related to general problem solving from those involved in operation type specific processes (addition versus multiplication). We orthogonally varied operation type and complexity. Importantly, complexity was defined not only based on surface criteria (for example number size), but also on the basis of individual participants' strategy ratings, which were validated in a detailed behavioral analysis. We replicated previously reported operation type effects in our analyses based on surface criteria. However, these effects vanished when controlling for individual strategies. Instead, procedural strategies contrasted with memory retrieval reliably activated fronto-parietal and motor regions, while retrieval strategies activated parietal cortices. This challenges views that operation types rely on partially different neural systems, and suggests that previously reported differences between operation types may have emerged due to invalid measures of complexity. We conclude that mental arithmetic is a powerful paradigm to study brain networks of abstract problem solving, as long as individual participants' strategies are taken into account. Copyright © 2014 Elsevier Inc. All rights reserved.

Computer-based training for improving mental calculation in third- and fifth-graders.

PubMed

Caviola, Sara; Gerotto, Giulia; Mammarella, Irene C

2016-11-01

The literature on intervention programs to improve arithmetical abilities is fragmentary and few studies have examined training on the symbolic representation of numbers (i.e. Arabic digits). In the present research, three groups of 3rd- and 5th-grade schoolchildren were given training on mental additions: 76 were assigned to a computer-based strategic training (ST) group, 73 to a process-based training (PBT) group, and 71 to a passive control (PC) group. Before and after the training, the children were given a criterion task involving complex addition problems, a nearest transfer task on complex subtraction problems, two near transfer tasks on math fluency, and a far transfer task on numerical reasoning. Our results showed developmental differences: 3rd-graders benefited more from the ST, with transfer effects on subtraction problems and math fluency, while 5th-graders benefited more from the PBT, improving their response times in the criterion task. Developmental, clinical and educational implications of these findings are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Rapid Generation of Optimal Asteroid Powered Descent Trajectories Via Convex Optimization

NASA Technical Reports Server (NTRS)

Pinson, Robin; Lu, Ping

2015-01-01

This paper investigates a convex optimization based method that can rapidly generate the fuel optimal asteroid powered descent trajectory. The ultimate goal is to autonomously design the optimal powered descent trajectory on-board the spacecraft immediately prior to the descent burn. Compared to a planetary powered landing problem, the major difficulty is the complex gravity field near the surface of an asteroid that cannot be approximated by a constant gravity field. This paper uses relaxation techniques and a successive solution process that seeks the solution to the original nonlinear, nonconvex problem through the solutions to a sequence of convex optimal control problems.

Propagating Qualitative Values Through Quantitative Equations

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak

1992-01-01

In most practical problems where traditional numeric simulation is not adequate, one need to reason about a system with both qualitative and quantitative equations. In this paper, we address the problem of propagating qualitative values represented as interval values through quantitative equations. Previous research has produced exponential-time algorithms for approximate solution of the problem. These may not meet the stringent requirements of many real time applications. This paper advances the state of art by producing a linear-time algorithm that can propagate a qualitative value through a class of complex quantitative equations exactly and through arbitrary algebraic expressions approximately. The algorithm was found applicable to Space Shuttle Reaction Control System model.

Solving Complex Problems: A Convergent Approach to Cognitive Load Measurement

ERIC Educational Resources Information Center

Zheng, Robert; Cook, Anne

2012-01-01

The study challenged the current practices in cognitive load measurement involving complex problem solving by manipulating the presence of pictures in multiple rule-based problem-solving situations and examining the cognitive load resulting from both off-line and online measures associated with complex problem solving. Forty-eight participants…

System analysis of vehicle active safety problem

NASA Astrophysics Data System (ADS)

Buznikov, S. E.

2018-02-01

The problem of the road transport safety affects the vital interests of the most of the population and is characterized by a global level of significance. The system analysis of problem of creation of competitive active vehicle safety systems is presented as an interrelated complex of tasks of multi-criterion optimization and dynamic stabilization of the state variables of a controlled object. Solving them requires generation of all possible variants of technical solutions within the software and hardware domains and synthesis of the control, which is close to optimum. For implementing the task of the system analysis the Zwicky “morphological box” method is used. Creation of comprehensive active safety systems involves solution of the problem of preventing typical collisions. For solving it, a structured set of collisions is introduced with its elements being generated also using the Zwicky “morphological box” method. The obstacle speed, the longitudinal acceleration of the controlled object and the unpredictable changes in its movement direction due to certain faults, the road surface condition and the control errors are taken as structure variables that characterize the conditions of collisions. The conditions for preventing typical collisions are presented as inequalities for physical variables that define the state vector of the object and its dynamic limits.

From problem solving to problem definition: scrutinizing the complex nature of clinical practice.

PubMed

Cristancho, Sayra; Lingard, Lorelei; Regehr, Glenn

2017-02-01

In medical education, we have tended to present problems as being singular, stable, and solvable. Problem solving has, therefore, drawn much of medical education researchers' attention. This focus has been important but it is limited in terms of preparing clinicians to deal with the complexity of the 21st century healthcare system in which they will provide team-based care for patients with complex medical illness. In this paper, we use the Soft Systems Engineering principles to introduce the idea that in complex, team-based situations, problems usually involve divergent views and evolve with multiple solution iterations. As such we need to shift the conversation from (1) problem solving to problem definition, and (2) from a problem definition derived exclusively at the level of the individual to a definition derived at the level of the situation in which the problem is manifested. Embracing such a focus on problem definition will enable us to advocate for novel educational practices that will equip trainees to effectively manage the problems they will encounter in complex, team-based healthcare.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems.

PubMed

Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N

2006-12-01

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

A novel approach to sports concussion assessment: Computerized multilimb reaction times and balance control testing.

PubMed

Vartiainen, Matti V; Holm, Anu; Lukander, Jani; Lukander, Kristian; Koskinen, Sanna; Bornstein, Robert; Hokkanen, Laura

2016-01-01

Mild traumatic brain injuries (MTBI) or concussions often result in problems with attention, executive functions, and motor control. For better identification of these diverse problems, novel approaches integrating tests of cognitive and motor functioning are needed. The aim was to characterize minor changes in motor and cognitive performance after sports-related concussions with a novel test battery, including balance tests and a computerized multilimb reaction time test. The cognitive demands of the battery gradually increase from a simple stimulus response to a complex task requiring executive attention. A total of 113 male ice hockey players (mean age = 24.6 years, SD = 5.7) were assessed before a season. During the season, nine concussed players were retested within 36 hours, four to six days after the concussion, and after the season. A control group of seven nonconcussed players from the same pool of players with comparable demographics were retested after the season. Performance was measured using a balance test and the Motor Cognitive Test battery (MotCoTe) with multilimb responses in simple reaction, choice reaction, inhibition, and conflict resolution conditions. The performance of the concussed group declined at the postconcussion assessment compared to both the baseline measurement and the nonconcussed controls. Significant changes were observed in the concussed group for the multilimb choice reaction and inhibition tests. Tapping and balance showed a similar trend, but no statistically significant difference in performance. In sports-related concussions, complex motor tests can be valuable additions in assessing the outcome and recovery. In the current study, using subtasks with varying cognitive demands, it was shown that while simple motor performance was largely unaffected, the more complex tasks induced impaired reaction times for the concussed subjects. The increased reaction times may reflect the disruption of complex and integrative cognitive function in concussions.

Neural networks for vertical microcode compaction

NASA Astrophysics Data System (ADS)

Chu, Pong P.

1992-09-01

Neural networks provide an alternative way to solve complex optimization problems. Instead of performing a program of instructions sequentially as in a traditional computer, neural network model explores many competing hypotheses simultaneously using its massively parallel net. The paper shows how to use the neural network approach to perform vertical micro-code compaction for a micro-programmed control unit. The compaction procedure includes two basic steps. The first step determines the compatibility classes and the second step selects a minimal subset to cover the control signals. Since the selection process is an NP- complete problem, to find an optimal solution is impractical. In this study, we employ a customized neural network to obtain the minimal subset. We first formalize this problem, and then define an `energy function' and map it to a two-layer fully connected neural network. The modified network has two types of neurons and can always obtain a valid solution.

A Control Variate Method for Probabilistic Performance Assessment. Improved Estimates for Mean Performance Quantities of Interest

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacKinnon, Robert J.; Kuhlman, Kristopher L

2016-05-01

We present a method of control variates for calculating improved estimates for mean performance quantities of interest, E(PQI) , computed from Monte Carlo probabilistic simulations. An example of a PQI is the concentration of a contaminant at a particular location in a problem domain computed from simulations of transport in porous media. To simplify the presentation, the method is described in the setting of a one- dimensional elliptical model problem involving a single uncertain parameter represented by a probability distribution. The approach can be easily implemented for more complex problems involving multiple uncertain parameters and in particular for application tomore » probabilistic performance assessment of deep geologic nuclear waste repository systems. Numerical results indicate the method can produce estimates of E(PQI)having superior accuracy on coarser meshes and reduce the required number of simulations needed to achieve an acceptable estimate.« less

Cognitive Behavioural Suicide Prevention for Male Prisoners: Case examples

PubMed Central

Pratt, Daniel; Gooding, Patricia; Awenat, Yvonne; Eccles, Steve; Tarrier, Nicholas

2015-01-01

Suicide is a serious public health problem but a problem that is preventable. This complex and challenging problem is particularly prevalent amongst prisoners; associated with a five-fold increase in risk compared to the general community. Being in prison can lead people to experience fear, distrust, lack of control, isolation, and shame, which is often experienced as overwhelming and intolerable with some choosing suicide as a way to escape. Few effective psychological interventions exist to prevent suicide although cognitive behaviour therapies appear to offer some promise. Offering cognitive behaviour suicide prevention (CBSP) therapy to high risk prisoners may help to reduce the likelihood of preventable self-inflicted deaths. In this paper we present three cases drawn from a randomised controlled trial designed to investigate the feasibility of CBSP for male prisoners. Implications of the current findings for future research and clinical practice are considered. PMID:27713616

Complex Mobile Independent Power Station for Urban Areas

NASA Astrophysics Data System (ADS)

Tunik, A. A.; Tolstoy, M. Y.

2017-11-01

A new type of a complex mobile independent power station developed in the Department of Engineering Communications and Life-Support Systems of Irkutsk National Research Technical University, is presented in this article. This station contains only solar panel, wind turbine, accumulator, diesel generator and microbial fuel cell for to produce electric energy, heat pump and solar collector to generate heat energy and also wastewater treatment plant and new complex control system. The complex mobile independent power station is intended for full power supply of a different kind of consumers located even in remote areas thus reducing their dependence from centralized energy supply systems, decrease the fossil fuel consumption, improve the environment of urban areas and solve the problems of the purification of industrial and municipal wastewater.

The Role of Specific Alcohol-Related Problems in Predicting Depressive Experiences in a Cross-Sectional National Household Survey.

PubMed

McBride, Orla; Cheng, Hui G; Slade, Tim; Lynskey, Michael T

2016-11-01

This study examines the type of alcohol-related problems that commonly occur before the onset of depressive experiences to shed light on the mechanisms underlying the alcohol-depression comorbidity relationship. Data were from the 1992 USA National Longitudinal Alcohol Epidemiologic Survey. Analytical sample comprised of drinkers with a prior to past year (PPY) history of alcohol-related problems with or without any experiences of depressed mood in the past year (PY). The prevalence of PPY alcohol-related problems was examined, as well as the ability of specific alcohol problems to predict PY experiences of depressed mood. The type of depressed mood experienced by drinkers with PPY history of alcohol-related problems was compared to those without. All but one alcohol-related problem PPY was more frequently endorsed among drinkers with PY experiences of depressed mood. Controlling for confounders, five alcohol-related problems experienced PPY were significantly predictive of depressed mood PY: tolerance, drinking longer than intended, inability to perform important social and occupational roles/obligations, as well as drinking in physically hazardous situations. Drinkers with alcohol-related problems PPY more frequently experienced difficulties with concentration, energy, and thoughts of death, than those without. Alcohol-related problems are likely associated with depressive experiences through a complex network, whereby experiences of physical dependence and negative consequences increase the likelihood of negative affect. Novel study designs are necessary to fully understand the complex mechanisms underlying this comorbidity. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Deadlock-free genetic scheduling algorithm for automated manufacturing systems based on deadlock control policy.

PubMed

Xing, KeYi; Han, LiBin; Zhou, MengChu; Wang, Feng

2012-06-01

Deadlock-free control and scheduling are vital for optimizing the performance of automated manufacturing systems (AMSs) with shared resources and route flexibility. Based on the Petri net models of AMSs, this paper embeds the optimal deadlock avoidance policy into the genetic algorithm and develops a novel deadlock-free genetic scheduling algorithm for AMSs. A possible solution of the scheduling problem is coded as a chromosome representation that is a permutation with repetition of parts. By using the one-step look-ahead method in the optimal deadlock control policy, the feasibility of a chromosome is checked, and infeasible chromosomes are amended into feasible ones, which can be easily decoded into a feasible deadlock-free schedule. The chromosome representation and polynomial complexity of checking and amending procedures together support the cooperative aspect of genetic search for scheduling problems strongly.

Experimental econophysics: Complexity, self-organization, and emergent properties

NASA Astrophysics Data System (ADS)

Huang, J. P.

2015-03-01

Experimental econophysics is concerned with statistical physics of humans in the laboratory, and it is based on controlled human experiments developed by physicists to study some problems related to economics or finance. It relies on controlled human experiments in the laboratory together with agent-based modeling (for computer simulations and/or analytical theory), with an attempt to reveal the general cause-effect relationship between specific conditions and emergent properties of real economic/financial markets (a kind of complex adaptive systems). Here I review the latest progress in the field, namely, stylized facts, herd behavior, contrarian behavior, spontaneous cooperation, partial information, and risk management. Also, I highlight the connections between such progress and other topics of traditional statistical physics. The main theme of the review is to show diverse emergent properties of the laboratory markets, originating from self-organization due to the nonlinear interactions among heterogeneous humans or agents (complexity).

Finite-Time and Fixed-Time Cluster Synchronization With or Without Pinning Control.

PubMed

Liu, Xiwei; Chen, Tianping

2018-01-01

In this paper, the finite-time and fixed-time cluster synchronization problem for complex networks with or without pinning control are discussed. Finite-time (or fixed-time) synchronization has been a hot topic in recent years, which means that the network can achieve synchronization in finite-time, and the settling time depends on the initial values for finite-time synchronization (or the settling time is bounded by a constant for any initial values for fixed-time synchronization). To realize the finite-time and fixed-time cluster synchronization, some simple distributed protocols with or without pinning control are designed and the effectiveness is rigorously proved. Several sufficient criteria are also obtained to clarify the effects of coupling terms for finite-time and fixed-time cluster synchronization. Especially, when the cluster number is one, the cluster synchronization becomes the complete synchronization problem; when the network has only one node, the coupling term between nodes will disappear, and the synchronization problem becomes the simplest master-slave case, which also includes the stability problem for nonlinear systems like neural networks. All these cases are also discussed. Finally, numerical simulations are presented to demonstrate the correctness of obtained theoretical results.

Analysis of explicit model predictive control for path-following control

PubMed Central

2018-01-01

In this paper, explicit Model Predictive Control(MPC) is employed for automated lane-keeping systems. MPC has been regarded as the key to handle such constrained systems. However, the massive computational complexity of MPC, which employs online optimization, has been a major drawback that limits the range of its target application to relatively small and/or slow problems. Explicit MPC can reduce this computational burden using a multi-parametric quadratic programming technique(mp-QP). The control objective is to derive an optimal front steering wheel angle at each sampling time so that autonomous vehicles travel along desired paths, including straight, circular, and clothoid parts, at high entry speeds. In terms of the design of the proposed controller, a method of choosing weighting matrices in an optimization problem and the range of horizons for path-following control are described through simulations. For the verification of the proposed controller, simulation results obtained using other control methods such as MPC, Linear-Quadratic Regulator(LQR), and driver model are employed, and CarSim, which reflects the features of a vehicle more realistically than MATLAB/Simulink, is used for reliable demonstration. PMID:29534080

Analysis of explicit model predictive control for path-following control.

PubMed

Lee, Junho; Chang, Hyuk-Jun

2018-01-01

In this paper, explicit Model Predictive Control(MPC) is employed for automated lane-keeping systems. MPC has been regarded as the key to handle such constrained systems. However, the massive computational complexity of MPC, which employs online optimization, has been a major drawback that limits the range of its target application to relatively small and/or slow problems. Explicit MPC can reduce this computational burden using a multi-parametric quadratic programming technique(mp-QP). The control objective is to derive an optimal front steering wheel angle at each sampling time so that autonomous vehicles travel along desired paths, including straight, circular, and clothoid parts, at high entry speeds. In terms of the design of the proposed controller, a method of choosing weighting matrices in an optimization problem and the range of horizons for path-following control are described through simulations. For the verification of the proposed controller, simulation results obtained using other control methods such as MPC, Linear-Quadratic Regulator(LQR), and driver model are employed, and CarSim, which reflects the features of a vehicle more realistically than MATLAB/Simulink, is used for reliable demonstration.

Adaptive Synchronization of Fractional Order Complex-Variable Dynamical Networks via Pinning Control

NASA Astrophysics Data System (ADS)

Ding, Da-Wei; Yan, Jie; Wang, Nian; Liang, Dong

2017-09-01

In this paper, the synchronization of fractional order complex-variable dynamical networks is studied using an adaptive pinning control strategy based on close center degree. Some effective criteria for global synchronization of fractional order complex-variable dynamical networks are derived based on the Lyapunov stability theory. From the theoretical analysis, one concludes that under appropriate conditions, the complex-variable dynamical networks can realize the global synchronization by using the proper adaptive pinning control method. Meanwhile, we succeed in solving the problem about how much coupling strength should be applied to ensure the synchronization of the fractional order complex networks. Therefore, compared with the existing results, the synchronization method in this paper is more general and convenient. This result extends the synchronization condition of the real-variable dynamical networks to the complex-valued field, which makes our research more practical. Finally, two simulation examples show that the derived theoretical results are valid and the proposed adaptive pinning method is effective. Supported by National Natural Science Foundation of China under Grant No. 61201227, National Natural Science Foundation of China Guangdong Joint Fund under Grant No. U1201255, the Natural Science Foundation of Anhui Province under Grant No. 1208085MF93, 211 Innovation Team of Anhui University under Grant Nos. KJTD007A and KJTD001B, and also supported by Chinese Scholarship Council

Reflection as a Means of Developing Expertise in Problem Solving, Decision Making, and Complex Thinking of Designers.

ERIC Educational Resources Information Center

Moallem, Mahnaz

This paper focuses on reflection and reflective thinking as a means of developing expertise in instructional designers. The need for the reflective instructional designer is discussed, and reflective thinking is examined from several perspectives, i.e., controlled thinking, tacit knowledge, epistemic assumption, abductive reasoning, willingness to…

Cybernation and Man--A Course Development Project. Final Report.

ERIC Educational Resources Information Center

Parkman, Ralph

An inter-disciplinary course entitled "Cybernation and Man," developed by the School of Engineering at San Jose State College, tries to evaluate the many problems posed to man by the expansion of his technology. It is contended in the course that the most effective approach to control of complex social phenomena within a technological…

A Socioeconomic Analysis of Environmental Concern: Case of the Four Corners Electric Power Complex. Bulletin No. 626.

ERIC Educational Resources Information Center

Eastman, Clyde; And Others

Recently American attention has focused on the problems of pollution and environmental protection. Focusing on the Four Corners Interstate Air Quality Control Region, this study determined which socioeconomic characteristics were associated with concern for environmental quality as measured by willingness to pay for pollution abatement. Sample…

PUNCHED CARD SYSTEM NEEDN'T BE COMPLEX TO GIVE COMPLETE CONTROL.

ERIC Educational Resources Information Center

BEMIS, HAZEL T.

AT WORCESTER JUNIOR COLLEGE, MASSACHUSETTS, USE OF A MANUALLY OPERATED PUNCHED CARD SYSTEM HAS RESULTED IN (1) SIMPLIFIED REGISTRATION PROCEDURES, (2) QUICK ANALYSIS OF CONFLICTS AND PROBLEMS IN CLASS SCHEDULING, (3) READY ACCESS TO STATISTICAL INFORMATION, (4) DIRECTORY INFORMATION IN A WIDE RANGE OF CLASSIFICATIONS, (5) EASY VERIFICATION OF…

Enabling next-gen sequencing and analysis at the USDA-ARS U.S. Meat Animal Research Center with MiniLIMS

USDA-ARS?s Scientific Manuscript database

There is a growing need to combine DNA sequencing technologies to address complex problems in genome biology. These genomic studies routinely generate voluminous image, sequence, and mapping files that should be associated with quality control information (gels, spectra, etc.), and other important ...

The Role of Training, Individual Differences and Knowledge Representation in Cognitive-Oriented Task Performance.

ERIC Educational Resources Information Center

Koubek, Richard J.

The roles of training, problem representation, and individual differences on performance of both automated (simple) and controlled (complex) process tasks were studied. The following hypotheses were tested: (1) training and cognitive style affect the representation developed; (2) training and cognitive style affect the development and performance…

Remote control system for high-perfomance computer simulation of crystal growth by the PFC method

NASA Astrophysics Data System (ADS)

Pavlyuk, Evgeny; Starodumov, Ilya; Osipov, Sergei

2017-04-01

Modeling of crystallization process by the phase field crystal method (PFC) - one of the important directions of modern computational materials science. In this paper, the practical side of the computer simulation of the crystallization process by the PFC method is investigated. To solve problems using this method, it is necessary to use high-performance computing clusters, data storage systems and other often expensive complex computer systems. Access to such resources is often limited, unstable and accompanied by various administrative problems. In addition, the variety of software and settings of different computing clusters sometimes does not allow researchers to use unified program code. There is a need to adapt the program code for each configuration of the computer complex. The practical experience of the authors has shown that the creation of a special control system for computing with the possibility of remote use can greatly simplify the implementation of simulations and increase the performance of scientific research. In current paper we show the principal idea of such a system and justify its efficiency.

Expanded DEMATEL for Determining Cause and Effect Group in Bidirectional Relations

PubMed Central

Falatoonitoosi, Elham; Ahmed, Shamsuddin; Sorooshian, Shahryar

2014-01-01

Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology has been proposed to solve complex and intertwined problem groups in many situations such as developing the capabilities, complex group decision making, security problems, marketing approaches, global managers, and control systems. DEMATEL is able to realize casual relationships by dividing important issues into cause and effect group as well as making it possible to visualize the casual relationships of subcriteria and systems in the course of casual diagram that it may demonstrate communication network or a little control relationships between individuals. Despite of its ability to visualize cause and effect inside a network, the original DEMATEL has not been able to find the cause and effect group between different networks. Therefore, the aim of this study is proposing the expanded DEMATEL to cover this deficiency by new formulations to determine cause and effect factors between separate networks that have bidirectional direct impact on each other. At the end, the feasibility of new extra formulations is validated by case study in three numerical examples of green supply chain networks for an automotive company. PMID:24693224

Expanded DEMATEL for determining cause and effect group in bidirectional relations.

PubMed

Falatoonitoosi, Elham; Ahmed, Shamsuddin; Sorooshian, Shahryar

2014-01-01

Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology has been proposed to solve complex and intertwined problem groups in many situations such as developing the capabilities, complex group decision making, security problems, marketing approaches, global managers, and control systems. DEMATEL is able to realize casual relationships by dividing important issues into cause and effect group as well as making it possible to visualize the casual relationships of subcriteria and systems in the course of casual diagram that it may demonstrate communication network or a little control relationships between individuals. Despite of its ability to visualize cause and effect inside a network, the original DEMATEL has not been able to find the cause and effect group between different networks. Therefore, the aim of this study is proposing the expanded DEMATEL to cover this deficiency by new formulations to determine cause and effect factors between separate networks that have bidirectional direct impact on each other. At the end, the feasibility of new extra formulations is validated by case study in three numerical examples of green supply chain networks for an automotive company.

An octopus-bioinspired solution to movement and manipulation for soft robots.

PubMed

Calisti, M; Giorelli, M; Levy, G; Mazzolai, B; Hochner, B; Laschi, C; Dario, P

2011-09-01

Soft robotics is a challenging and promising branch of robotics. It can drive significant improvements across various fields of traditional robotics, and contribute solutions to basic problems such as locomotion and manipulation in unstructured environments. A challenging task for soft robotics is to build and control soft robots able to exert effective forces. In recent years, biology has inspired several solutions to such complex problems. This study aims at investigating the smart solution that the Octopus vulgaris adopts to perform a crawling movement, with the same limbs used for grasping and manipulation. An ad hoc robot was designed and built taking as a reference a biological hypothesis on crawling. A silicone arm with cables embedded to replicate the functionality of the arm muscles of the octopus was built. This novel arm is capable of pushing-based locomotion and object grasping, mimicking the movements that octopuses adopt when crawling. The results support the biological observations and clearly show a suitable way to build a more complex soft robot that, with minimum control, can perform diverse tasks.

Multidisciplinary Optimization Approach for Design and Operation of Constrained and Complex-shaped Space Systems

NASA Astrophysics Data System (ADS)

Lee, Dae Young

The design of a small satellite is challenging since they are constrained by mass, volume, and power. To mitigate these constraint effects, designers adopt deployable configurations on the spacecraft that result in an interesting and difficult optimization problem. The resulting optimization problem is challenging due to the computational complexity caused by the large number of design variables and the model complexity created by the deployables. Adding to these complexities, there is a lack of integration of the design optimization systems into operational optimization, and the utility maximization of spacecraft in orbit. The developed methodology enables satellite Multidisciplinary Design Optimization (MDO) that is extendable to on-orbit operation. Optimization of on-orbit operations is possible with MDO since the model predictive controller developed in this dissertation guarantees the achievement of the on-ground design behavior in orbit. To enable the design optimization of highly constrained and complex-shaped space systems, the spherical coordinate analysis technique, called the "Attitude Sphere", is extended and merged with an additional engineering tools like OpenGL. OpenGL's graphic acceleration facilitates the accurate estimation of the shadow-degraded photovoltaic cell area. This technique is applied to the design optimization of the satellite Electric Power System (EPS) and the design result shows that the amount of photovoltaic power generation can be increased more than 9%. Based on this initial methodology, the goal of this effort is extended from Single Discipline Optimization to Multidisciplinary Optimization, which includes the design and also operation of the EPS, Attitude Determination and Control System (ADCS), and communication system. The geometry optimization satisfies the conditions of the ground development phase; however, the operation optimization may not be as successful as expected in orbit due to disturbances. To address this issue, for the ADCS operations, controllers based on Model Predictive Control that are effective for constraint handling were developed and implemented. All the suggested design and operation methodologies are applied to a mission "CADRE", which is space weather mission scheduled for operation in 2016. This application demonstrates the usefulness and capability of the methodology to enhance CADRE's capabilities, and its ability to be applied to a variety of missions.

Enhancing Integrated Pest Management in GM Cotton Systems Using Host Plant Resistance

PubMed Central

Trapero, Carlos; Wilson, Iain W.; Stiller, Warwick N.; Wilson, Lewis J.

2016-01-01

Cotton has lost many ancestral defensive traits against key invertebrate pests. This is suggested by the levels of resistance to some pests found in wild cotton genotypes as well as in cultivated landraces and is a result of domestication and a long history of targeted breeding for yield and fiber quality, along with the capacity to control pests with pesticides. Genetic modification (GM) allowed integration of toxins from a bacteria into cotton to control key Lepidopteran pests. Since the mid-1990s, use of GM cotton cultivars has greatly reduced the amount of pesticides used in many cotton systems. However, pests not controlled by the GM traits have usually emerged as problems, especially the sucking bug complex. Control of this complex with pesticides often causes a reduction in beneficial invertebrate populations, allowing other secondary pests to increase rapidly and require control. Control of both sucking bug complex and secondary pests is problematic due to the cost of pesticides and/or high risk of selecting for pesticide resistance. Deployment of host plant resistance (HPR) provides an opportunity to manage these issues in GM cotton systems. Cotton cultivars resistant to the sucking bug complex and/or secondary pests would require fewer pesticide applications, reducing costs and risks to beneficial invertebrate populations and pesticide resistance. Incorporation of HPR traits into elite cotton cultivars with high yield and fiber quality offers the potential to further reduce pesticide use and increase the durability of pest management in GM cotton systems. We review the challenges that the identification and use of HPR against invertebrate pests brings to cotton breeding. We explore sources of resistance to the sucking bug complex and secondary pests, the mechanisms that control them and the approaches to incorporate these defense traits to commercial cultivars. PMID:27148323

The CD control improvement by using CDSEM 2D measurement of complex OPC patterns

NASA Astrophysics Data System (ADS)

Chou, William; Cheng, Jeffrey; Lee, Adder; Cheng, James; Tzeng, Alex C.; Lu, Colbert; Yang, Ray; Lee, Hong Jen; Bandoh, Hideaki; Santo, Izumi; Zhang, Hao; Chen, Chien Kang

2016-10-01

As the process node becomes more advanced, the accuracy and precision in OPC pattern CD are required in mask manufacturing. CD SEM is an essential tool to confirm the mask quality such as CD control, CD uniformity and CD mean to target (MTT). Unfortunately, in some cases of arbitrary enclosed patterns or aggressive OPC patterns, for instance, line with tiny jogs and curvilinear SRAF, CD variation depending on region of interest (ROI) is a very serious problem in mask CD control, even it decreases the wafer yield. For overcoming this situation, the 2-dimensional (2D) method by Holon is adopted. In this paper, we summarize the comparisons of error budget between conventional (1D) and 2D data using CD SEM and the CD performance between mask and wafer by complex OPC patterns including ILT features.

Implicit Multibody Penalty-BasedDistributed Contact.

PubMed

Xu, Hongyi; Zhao, Yili; Barbic, Jernej

2014-09-01

The penalty method is a simple and popular approach to resolving contact in computer graphics and robotics. Penalty-based contact, however, suffers from stability problems due to the highly variable and unpredictable net stiffness, and this is particularly pronounced in simulations with time-varying distributed geometrically complex contact. We employ semi-implicit integration, exact analytical contact gradients, symbolic Gaussian elimination and a SVD solver to simulate stable penalty-based frictional contact with large, time-varying contact areas, involving many rigid objects and articulated rigid objects in complex conforming contact and self-contact. We also derive implicit proportional-derivative control forces for real-time control of articulated structures with loops. We present challenging contact scenarios such as screwing a hexbolt into a hole, bowls stacked in perfectly conforming configurations, and manipulating many objects using actively controlled articulated mechanisms in real time.

Distributed synchronization control of complex networks with communication constraints.

PubMed

Xu, Zhenhua; Zhang, Dan; Song, Hongbo

2016-11-01

This paper is concerned with the distributed synchronization control of complex networks with communication constraints. In this work, the controllers communicate with each other through the wireless network, acting as a controller network. Due to the constrained transmission power, techniques such as the packet size reduction and transmission rate reduction schemes are proposed which could help reduce communication load of the controller network. The packet dropout problem is also considered in the controller design since it is often encountered in networked control systems. We show that the closed-loop system can be modeled as a switched system with uncertainties and random variables. By resorting to the switched system approach and some stochastic system analysis method, a new sufficient condition is firstly proposed such that the exponential synchronization is guaranteed in the mean-square sense. The controller gains are determined by using the well-known cone complementarity linearization (CCL) algorithm. Finally, a simulation study is performed, which demonstrates the effectiveness of the proposed design algorithm. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Integrated Design and Implementation of Embedded Control Systems with Scilab

PubMed Central

Ma, Longhua; Xia, Feng; Peng, Zhe

2008-01-01

Embedded systems are playing an increasingly important role in control engineering. Despite their popularity, embedded systems are generally subject to resource constraints and it is therefore difficult to build complex control systems on embedded platforms. Traditionally, the design and implementation of control systems are often separated, which causes the development of embedded control systems to be highly time-consuming and costly. To address these problems, this paper presents a low-cost, reusable, reconfigurable platform that enables integrated design and implementation of embedded control systems. To minimize the cost, free and open source software packages such as Linux and Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers for interfacing Scilab with several communication protocols including serial, Ethernet, and Modbus are developed. Experiments are conducted to test the developed embedded platform. The use of Scilab enables implementation of complex control algorithms on embedded platforms. With the developed platform, it is possible to perform all phases of the development cycle of embedded control systems in a unified environment, thus facilitating the reduction of development time and cost. PMID:27873827

Integrated Design and Implementation of Embedded Control Systems with Scilab.

PubMed

Ma, Longhua; Xia, Feng; Peng, Zhe

2008-09-05

Embedded systems are playing an increasingly important role in control engineering. Despite their popularity, embedded systems are generally subject to resource constraints and it is therefore difficult to build complex control systems on embedded platforms. Traditionally, the design and implementation of control systems are often separated, which causes the development of embedded control systems to be highly timeconsuming and costly. To address these problems, this paper presents a low-cost, reusable, reconfigurable platform that enables integrated design and implementation of embedded control systems. To minimize the cost, free and open source software packages such as Linux and Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers for interfacing Scilab with several communication protocols including serial, Ethernet, and Modbus are developed. Experiments are conducted to test the developed embedded platform. The use of Scilab enables implementation of complex control algorithms on embedded platforms. With the developed platform, it is possible to perform all phases of the development cycle of embedded control systems in a unified environment, thus facilitating the reduction of development time and cost.

[Influence of mental rotation of objects on psychophysiological functions of women].

PubMed

Chikina, L V; Fedorchuk, S V; Trushina, V A; Ianchuk, P I; Makarchuk, M Iu

2012-01-01

An integral part of activity of modern human beings is an involvement to work with the computer systems which, in turn, produces a nervous - emotional tension. Hence, a problem of control of the psychophysiological state of workmen with the purpose of health preservation and success of their activity and the problem of application of rehabilitational actions are actual. At present it is known that the efficiency of rehabilitational procedures rises following application of the complex of regenerative programs. Previously performed by us investigation showed that mental rotation is capable to compensate the consequences of a nervous - emotional tension. Therefore, in the present work we investigated how the complex of spatial tasks developed by us influences psychophysiological performances of tested women for which the psycho-emotional tension with the usage of computer technologies is more essential, and the procedure of mental rotation is more complex task for them, than for men. The complex of spatial tasks applied in the given work included: mental rotation of simple objects (letters and digits), mental rotation of complex objects (geometrical figures) and mental rotation of complex objects with the usage of a short-term memory. Execution of the complex of spatial tasks reduces the time of simple and complex sensomotor response, raises parameters of a short-term memory, brain work capacity and improves nervous processes. Collectively, mental rotation of objects can be recommended as a rehabilitational resource for compensation of consequences of any psycho-emotional strain, both for men, and for women.

Design of integrated pitch axis for autopilot/autothrottle and integrated lateral axis for autopilot/yaw damper for NASA TSRV airplane using integral LQG methodology

NASA Technical Reports Server (NTRS)

Kaminer, Isaac; Benson, Russell A.; Coleman, Edward E.; Ebrahimi, Yaghoob S.

1990-01-01

Two designs are presented for control systems for the NASA Transport System Research Vehicle (TSRV) using integral Linear Quadratic Gaussian (LQG) methodology. The first is an integrated longitudinal autopilot/autothrottle design and the second design is an integrated lateral autopilot/yaw damper/sideslip controller design. It is shown that a systematic top-down approach to a complex design problem combined with proper application of modern control synthesis techniques yields a satisfactory solution in a reasonable period of time.

How the credit assignment problems in motor control could be solved after the cerebellum predicts increases in error.

PubMed

Verduzco-Flores, Sergio O; O'Reilly, Randall C

2015-01-01

We present a cerebellar architecture with two main characteristics. The first one is that complex spikes respond to increases in sensory errors. The second one is that cerebellar modules associate particular contexts where errors have increased in the past with corrective commands that stop the increase in error. We analyze our architecture formally and computationally for the case of reaching in a 3D environment. In the case of motor control, we show that there are synergies of this architecture with the Equilibrium-Point hypothesis, leading to novel ways to solve the motor error and distal learning problems. In particular, the presence of desired equilibrium lengths for muscles provides a way to know when the error is increasing, and which corrections to apply. In the context of Threshold Control Theory and Perceptual Control Theory we show how to extend our model so it implements anticipative corrections in cascade control systems that span from muscle contractions to cognitive operations.

How the credit assignment problems in motor control could be solved after the cerebellum predicts increases in error

PubMed Central

Verduzco-Flores, Sergio O.; O'Reilly, Randall C.

2015-01-01

We present a cerebellar architecture with two main characteristics. The first one is that complex spikes respond to increases in sensory errors. The second one is that cerebellar modules associate particular contexts where errors have increased in the past with corrective commands that stop the increase in error. We analyze our architecture formally and computationally for the case of reaching in a 3D environment. In the case of motor control, we show that there are synergies of this architecture with the Equilibrium-Point hypothesis, leading to novel ways to solve the motor error and distal learning problems. In particular, the presence of desired equilibrium lengths for muscles provides a way to know when the error is increasing, and which corrections to apply. In the context of Threshold Control Theory and Perceptual Control Theory we show how to extend our model so it implements anticipative corrections in cascade control systems that span from muscle contractions to cognitive operations. PMID:25852535

Distributed Optimization of Multi-Agent Systems: Framework, Local Optimizer, and Applications

NASA Astrophysics Data System (ADS)

Zu, Yue

Convex optimization problem can be solved in a centralized or distributed manner. Compared with centralized methods based on single-agent system, distributed algorithms rely on multi-agent systems with information exchanging among connected neighbors, which leads to great improvement on the system fault tolerance. Thus, a task within multi-agent system can be completed with presence of partial agent failures. By problem decomposition, a large-scale problem can be divided into a set of small-scale sub-problems that can be solved in sequence/parallel. Hence, the computational complexity is greatly reduced by distributed algorithm in multi-agent system. Moreover, distributed algorithm allows data collected and stored in a distributed fashion, which successfully overcomes the drawbacks of using multicast due to the bandwidth limitation. Distributed algorithm has been applied in solving a variety of real-world problems. Our research focuses on the framework and local optimizer design in practical engineering applications. In the first one, we propose a multi-sensor and multi-agent scheme for spatial motion estimation of a rigid body. Estimation performance is improved in terms of accuracy and convergence speed. Second, we develop a cyber-physical system and implement distributed computation devices to optimize the in-building evacuation path when hazard occurs. The proposed Bellman-Ford Dual-Subgradient path planning method relieves the congestion in corridor and the exit areas. At last, highway traffic flow is managed by adjusting speed limits to minimize the fuel consumption and travel time in the third project. Optimal control strategy is designed through both centralized and distributed algorithm based on convex problem formulation. Moreover, a hybrid control scheme is presented for highway network travel time minimization. Compared with no controlled case or conventional highway traffic control strategy, the proposed hybrid control strategy greatly reduces total travel time on test highway network.

Combining pressure and temperature control in dynamics on energy landscapes

NASA Astrophysics Data System (ADS)

Hoffmann, Karl Heinz; Christian Schön, J.

2017-05-01

Complex systems from science, technology or mathematics usually appear to be very different in their specific dynamical evolution. However, the concept of an energy landscape with its basins corresponding to locally ergodic regions separated by energy barriers provides a unifying approach to the description of complex systems dynamics. In such systems one is often confronted with the task to control the dynamics such that a certain basin is reached with the highest possible probability. Typically one aims for the global minimum, e.g. when dealing with global optimization problems, but frequently other local minima such as the metastable compounds in materials science are of primary interest. Here we show how this task can be solved by applying control theory using magnesium fluoride as an example system, where different modifications of MgF2 are considered as targets. In particular, we generalize previous work restricted to temperature controls only and present controls which simultaneously adjust temperature and pressure in an optimal fashion.

Neural network application to aircraft control system design

NASA Technical Reports Server (NTRS)

Troudet, Terry; Garg, Sanjay; Merrill, Walter C.

1991-01-01

The feasibility of using artificial neural networks as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research are identified to enhance the practical applicability of neural networks to flight control design.

Neural network application to aircraft control system design

NASA Technical Reports Server (NTRS)

Troudet, Terry; Garg, Sanjay; Merrill, Walter C.

1991-01-01

The feasibility of using artificial neural network as control systems for modern, complex aerospace vehicles is investigated via an example aircraft control design study. The problem considered is that of designing a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft to provide independent control of pitch rate and airspeed responses to pilot command inputs. An explicit model following controller using H infinity control design techniques is first designed to gain insight into the control problem as well as to provide a baseline for evaluation of the neurocontroller. Using the model of the desired dynamics as a command generator, a multilayer feedforward neural network is trained to control the vehicle model within the physical limitations of the actuator dynamics. This is achieved by minimizing an objective function which is a weighted sum of tracking errors and control input commands and rates. To gain insight in the neurocontrol, linearized representations of the nonlinear neurocontroller are analyzed along a commanded trajectory. Linear robustness analysis tools are then applied to the linearized neurocontroller models and to the baseline H infinity based controller. Future areas of research identified to enhance the practical applicability of neural networks to flight control design.

Big, Not So Easy: Comparing Insurgency Theory to the Complex Problem of Violence in New Orleans

DTIC Science & Technology

2014-05-16

concern to gaining control through demonstrated military strength.59 Castro and Guevara were indeed successful in Cuba ; however, it is arguable whether...already been losing control of the population. Guevara’s attempt to replicate the success achieved in Cuba , using the focoism model, met with disaster...Orleans in population size and economic base, both cities rely on tourism as their main source of income. During reporting year 2009-2010, Orlando

Toward Modeling the Intrinsic Complexity of Test Problems

ERIC Educational Resources Information Center

Shoufan, Abdulhadi

2017-01-01

The concept of intrinsic complexity explains why different problems of the same type, tackled by the same problem solver, can require different times to solve and yield solutions of different quality. This paper proposes a general four-step approach that can be used to establish a model for the intrinsic complexity of a problem class in terms of…

Investigating the Effect of Complexity Factors in Stoichiometry Problems Using Logistic Regression and Eye Tracking

ERIC Educational Resources Information Center

Tang, Hui; Kirk, John; Pienta, Norbert J.

2014-01-01

This paper includes two experiments, one investigating complexity factors in stoichiometry word problems, and the other identifying students' problem-solving protocols by using eye-tracking technology. The word problems used in this study had five different complexity factors, which were randomly assigned by a Web-based tool that we developed. The…

Contamination of the freshwater ecosystem by pesticides

USGS Publications Warehouse

Cope, Oliver B.

1966-01-01

A large part of our disquieting present-day pesticide problem is intimately tied to the freshwater ecosystem. Economic poisons are used in so many types of terrain to control so many kinds of organisms that almost all lakes and streams are likely to be contaminated. In addition to accidental contamination many pesticides are deliberately applied directly to fresh waters for suppression of aquatic animals or plants. The problem is intensified because of the extreme susceptibility of freshwater organisms. The complexity of freshwater environments and their variety makes it difficult to comprehend the total effect of pesticides.

Looking beyond first-world problems: an emerging global workplace is encouraging more biomedical engineers to address the health issues of the developing world.

PubMed

Tucker, Lindsay

2014-01-01

Each year, the developed world is flooded with complex new medical technologies, from robotic prosthetics to remote-controlled aspirin implants. Meanwhile, only about 10% of health research funds are spent addressing the pressing problems of developing nations, although these countries make up 93% of the worldwide burden of disease. In short, while a small fraction of the world pops brand-name pharmaceuticals, the majority suffers from poor sanitation, contaminated drinking water, preventable disease, and child mortality.

A linguistic geometry for space applications

NASA Technical Reports Server (NTRS)

Stilman, Boris

1994-01-01

We develop a formal theory, the so-called Linguistic Geometry, in order to discover the inner properties of human expert heuristics, which were successful in a certain class of complex control systems, and apply them to different systems. This research relies on the formalization of search heuristics of high-skilled human experts which allow for the decomposition of complex system into the hierarchy of subsystems, and thus solve intractable problems reducing the search. The hierarchy of subsystems is represented as a hierarchy of formal attribute languages. This paper includes a formal survey of the Linguistic Geometry, and new example of a solution of optimization problem for the space robotic vehicles. This example includes actual generation of the hierarchy of languages, some details of trajectory generation and demonstrates the drastic reduction of search in comparison with conventional search algorithms.

Analytical approaches to optimizing system "Semiconductor converter-electric drive complex"

NASA Astrophysics Data System (ADS)

Kormilicin, N. V.; Zhuravlev, A. M.; Khayatov, E. S.

2018-03-01

In the electric drives of the machine-building industry, the problem of optimizing the drive in terms of mass-size indicators is acute. The article offers analytical methods that ensure the minimization of the mass of a multiphase semiconductor converter. In multiphase electric drives, the form of the phase current at which the best possible use of the "semiconductor converter-electric drive complex" for active materials is different from the sinusoidal form. It is shown that under certain restrictions on the phase current form, it is possible to obtain an analytical solution. In particular, if one assumes the shape of the phase current to be rectangular, the optimal shape of the control actions will depend on the width of the interpolar gap. In the general case, the proposed algorithm can be used to solve the problem under consideration by numerical methods.

Scientific and technical complex for modeling, researching and testing of rocket-space vehicles’ electric power installations

NASA Astrophysics Data System (ADS)

Bezruchko, Konstantin; Davidov, Albert

2009-01-01

In the given article scientific and technical complex for modeling, researching and testing of rocket-space vehicles' power installations which was created in Power Source Laboratory of National Aerospace University "KhAI" is described. This scientific and technical complex gives the opportunity to replace the full-sized tests on model tests and to reduce financial and temporary inputs at modeling, researching and testing of rocket-space vehicles' power installations. Using the given complex it is possible to solve the problems of designing and researching of rocket-space vehicles' power installations efficiently, and also to provide experimental researches of physical processes and tests of solar and chemical batteries of rocket-space complexes and space vehicles. Scientific and technical complex also allows providing accelerated tests, diagnostics, life-time control and restoring of chemical accumulators for rocket-space vehicles' power supply systems.

Multigrid Methods for Aerodynamic Problems in Complex Geometries

NASA Technical Reports Server (NTRS)

Caughey, David A.

1995-01-01

Work has been directed at the development of efficient multigrid methods for the solution of aerodynamic problems involving complex geometries, including the development of computational methods for the solution of both inviscid and viscous transonic flow problems. The emphasis is on problems of complex, three-dimensional geometry. The methods developed are based upon finite-volume approximations to both the Euler and the Reynolds-Averaged Navier-Stokes equations. The methods are developed for use on multi-block grids using diagonalized implicit multigrid methods to achieve computational efficiency. The work is focused upon aerodynamic problems involving complex geometries, including advanced engine inlets.

Implicit methods for efficient musculoskeletal simulation and optimal control

PubMed Central

van den Bogert, Antonie J.; Blana, Dimitra; Heinrich, Dieter

2011-01-01

The ordinary differential equations for musculoskeletal dynamics are often numerically stiff and highly nonlinear. Consequently, simulations require small time steps, and optimal control problems are slow to solve and have poor convergence. In this paper, we present an implicit formulation of musculoskeletal dynamics, which leads to new numerical methods for simulation and optimal control, with the expectation that we can mitigate some of these problems. A first order Rosenbrock method was developed for solving forward dynamic problems using the implicit formulation. It was used to perform real-time dynamic simulation of a complex shoulder arm system with extreme dynamic stiffness. Simulations had an RMS error of only 0.11 degrees in joint angles when running at real-time speed. For optimal control of musculoskeletal systems, a direct collocation method was developed for implicitly formulated models. The method was applied to predict gait with a prosthetic foot and ankle. Solutions were obtained in well under one hour of computation time and demonstrated how patients may adapt their gait to compensate for limitations of a specific prosthetic limb design. The optimal control method was also applied to a state estimation problem in sports biomechanics, where forces during skiing were estimated from noisy and incomplete kinematic data. Using a full musculoskeletal dynamics model for state estimation had the additional advantage that forward dynamic simulations, could be done with the same implicitly formulated model to simulate injuries and perturbation responses. While these methods are powerful and allow solution of previously intractable problems, there are still considerable numerical challenges, especially related to the convergence of gradient-based solvers. PMID:22102983

The Multiple Control of Verbal Behavior

PubMed Central

Michael, Jack; Palmer, David C; Sundberg, Mark L

2011-01-01

Amid the novel terms and original analyses in Skinner's Verbal Behavior, the importance of his discussion of multiple control is easily missed, but multiple control of verbal responses is the rule rather than the exception. In this paper we summarize and illustrate Skinner's analysis of multiple control and introduce the terms convergent multiple control and divergent multiple control. We point out some implications for applied work and discuss examples of the role of multiple control in humor, poetry, problem solving, and recall. Joint control and conditional discrimination are discussed as special cases of multiple control. We suggest that multiple control is a useful analytic tool for interpreting virtually all complex behavior, and we consider the concepts of derived relations and naming as cases in point. PMID:22532752

Analytical design of an industrial two-term controller for optimal regulatory control of open-loop unstable processes under operational constraints.

PubMed

Tchamna, Rodrigue; Lee, Moonyong

2018-01-01

This paper proposes a novel optimization-based approach for the design of an industrial two-term proportional-integral (PI) controller for the optimal regulatory control of unstable processes subjected to three common operational constraints related to the process variable, manipulated variable and its rate of change. To derive analytical design relations, the constrained optimal control problem in the time domain was transformed into an unconstrained optimization problem in a new parameter space via an effective parameterization. The resulting optimal PI controller has been verified to yield optimal performance and stability of an open-loop unstable first-order process under operational constraints. The proposed analytical design method explicitly takes into account the operational constraints in the controller design stage and also provides useful insights into the optimal controller design. Practical procedures for designing optimal PI parameters and a feasible constraint set exclusive of complex optimization steps are also proposed. The proposed controller was compared with several other PI controllers to illustrate its performance. The robustness of the proposed controller against plant-model mismatch has also been investigated. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex and Dynamic Conditions

DTIC Science & Technology

2015-07-14

AFRL-OSR-VA-TR-2015-0202 Robust Decision Making: The Cognitive and Computational Modeling of Team Problem Solving for Decision Making under Complex...Computational Modeling of Team Problem Solving for Decision Making Under Complex and Dynamic Conditions 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1...functioning as they solve complex problems, and propose the means to improve the performance of teams, under changing or adversarial conditions. By

Microcomb-Based True-Time-Delay Network for Microwave Beamforming With Arbitrary Beam Pattern Control

NASA Astrophysics Data System (ADS)

Xue, Xiaoxiao; Xuan, Yi; Bao, Chengying; Li, Shangyuan; Zheng, Xiaoping; Zhou, Bingkun; Qi, Minghao; Weiner, Andrew M.

2018-06-01

Microwave phased array antennas (PAAs) are very attractive to defense applications and high-speed wireless communications for their abilities of fast beam scanning and complex beam pattern control. However, traditional PAAs based on phase shifters suffer from the beam-squint problem and have limited bandwidths. True-time-delay (TTD) beamforming based on low-loss photonic delay lines can solve this problem. But it is still quite challenging to build large-scale photonic TTD beamformers due to their high hardware complexity. In this paper, we demonstrate a photonic TTD beamforming network based on a miniature microresonator frequency comb (microcomb) source and dispersive time delay. A method incorporating optical phase modulation and programmable spectral shaping is proposed for positive and negative apodization weighting to achieve arbitrary microwave beam pattern control. The experimentally demonstrated TTD beamforming network can support a PAA with 21 elements. The microwave frequency range is $\\mathbf{8\\sim20\\ {GHz}}$, and the beam scanning range is $\\mathbf{\\pm 60.2^\\circ}$. Detailed measurements of the microwave amplitudes and phases are performed. The beamforming performances of Gaussian, rectangular beams and beam notch steering are evaluated through simulations by assuming a uniform radiating antenna array. The scheme can potentially support larger PAAs with hundreds of elements by increasing the number of comb lines with broadband microcomb generation.

Regulating Availability: How Access to Alcohol Affects Drinking and Problems in Youth and Adults

PubMed Central

Gruenewald, Paul J.

2011-01-01

Regulations on the availability of alcohol have been used to moderate alcohol problems in communities throughout the world for thousands of years. In the latter half of the 20th century, quantitative studies of the effects of these regulations on drinking and related problems began in earnest as public health practitioners began to recognize the full extent of the harmful consequences related to drinking. This article briefly outlines the history of this work over four areas, focusing on the minimum legal drinking age, the privatization of alcohol control systems, outlet densities, and hours and days of sale. Some historical background is provided to emphasize the theoretical and empirical roots of this work and to highlight the substantial progress that has been made in each area. In general, this assessment suggests that higher minimum legal drinking ages, greater monopoly controls over alcohol sales, lower outlet numbers and reduced outlet densities, and limited hours and days of sale can effectively reduce alcohol sales, use, and problems. There are, however, substantial gaps in the research literature and a near absence of the quantitative theoretical work needed to direct alcohol-control efforts. Local community responses to alcohol policies are complex and heterogeneous, sometimes reinforcing and sometimes mitigating the effects of availability regulations. Quantitative models of policy effects are essential to accelerate progress toward the formulation and testing of optimal control strategies for the reduction of alcohol problems. PMID:22330225

Methodological Problems of Nanotechnoscience

NASA Astrophysics Data System (ADS)

Gorokhov, V. G.

Recently, we have reported on the definitions of nanotechnology as a new type of NanoTechnoScience and on the nanotheory as a cluster of the different natural and engineering theories. Nanotechnology is not only a new type of scientific-engineering discipline, but it evolves also in a “nonclassical” way. Nanoontology or nano scientific world view has a function of the methodological orientation for the choice the theoretical means and methods toward a solution to the scientific and engineering problems. This allows to change from one explanation and scientific world view to another without any problems. Thus, nanotechnology is both a field of scientific knowledge and a sphere of engineering activity, in other words, NanoTechnoScience is similar to Systems Engineering as the analysis and design of large-scale, complex, man/machine systems but micro- and nanosystems. Nano systems engineering as well as Macro systems engineering includes not only systems design but also complex research. Design orientation has influence on the change of the priorities in the complex research and of the relation to the knowledge, not only to “the knowledge about something”, but also to the knowledge as the means of activity: from the beginning control and restructuring of matter at the nano-scale is a necessary element of nanoscience.

Managing search complexity in linguistic geometry.

PubMed

Stilman, B

1997-01-01

This paper is a new step in the development of linguistic geometry. This formal theory is intended to discover and generalize the inner properties of human expert heuristics, which have been successful in a certain class of complex control systems, and apply them to different systems. In this paper, we investigate heuristics extracted in the form of hierarchical networks of planning paths of autonomous agents. Employing linguistic geometry tools the dynamic hierarchy of networks is represented as a hierarchy of formal attribute languages. The main ideas of this methodology are shown in the paper on two pilot examples of the solution of complex optimization problems. The first example is a problem of strategic planning for the air combat, in which concurrent actions of four vehicles are simulated as serial interleaving moves. The second example is a problem of strategic planning for the space comb of eight autonomous vehicles (with interleaving moves) that requires generation of the search tree of the depth 25 with the branching factor 30. This is beyond the capabilities of modern and conceivable future computers (employing conventional approaches). In both examples the linguistic geometry tools showed deep and highly selective searches in comparison with conventional search algorithms. For the first example a sketch of the proof of optimality of the solution is considered.

Engineering Complex Embedded Systems with State Analysis and the Mission Data System

NASA Technical Reports Server (NTRS)

Ingham, Michel D.; Rasmussen, Robert D.; Bennett, Matthew B.; Moncada, Alex C.

2004-01-01

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer s intent, potentially leading to software errors. This problem is addressed by a systems engineering methodology called State Analysis, which provides a process for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using State Analysis and how these requirements inform the design of the system software, using representative spacecraft examples.

Adaptative synchronization in multi-output fractional-order complex dynamical networks and secure communications

NASA Astrophysics Data System (ADS)

Mata-Machuca, Juan L.; Aguilar-López, Ricardo

2018-01-01

This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.

Artificial Epigenetic Networks: Automatic Decomposition of Dynamical Control Tasks Using Topological Self-Modification.

PubMed

Turner, Alexander P; Caves, Leo S D; Stepney, Susan; Tyrrell, Andy M; Lones, Michael A

2017-01-01

This paper describes the artificial epigenetic network, a recurrent connectionist architecture that is able to dynamically modify its topology in order to automatically decompose and solve dynamical problems. The approach is motivated by the behavior of gene regulatory networks, particularly the epigenetic process of chromatin remodeling that leads to topological change and which underlies the differentiation of cells within complex biological organisms. We expected this approach to be useful in situations where there is a need to switch between different dynamical behaviors, and do so in a sensitive and robust manner in the absence of a priori information about problem structure. This hypothesis was tested using a series of dynamical control tasks, each requiring solutions that could express different dynamical behaviors at different stages within the task. In each case, the addition of topological self-modification was shown to improve the performance and robustness of controllers. We believe this is due to the ability of topological changes to stabilize attractors, promoting stability within a dynamical regime while allowing rapid switching between different regimes. Post hoc analysis of the controllers also demonstrated how the partitioning of the networks could provide new insights into problem structure.

Assessment of PIV-based unsteady load determination of an airfoil with actuated flap

NASA Astrophysics Data System (ADS)

Sterenborg, J. J. H. M.; Lindeboom, R. C. J.; Simão Ferreira, C. J.; van Zuijlen, A. H.; Bijl, H.

2014-02-01

For complex experimental setups involving movable structures it is not trivial to directly measure unsteady loads. An alternative is to deduce unsteady loads indirectly from measured velocity fields using Noca's method. The ultimate aim is to use this method in future work to determine unsteady loads for fluid-structure interaction problems. The focus in this paper is first on the application and assessment of Noca's method for an airfoil with an oscillating trailing edge flap. To our best knowledge Noca's method has not been applied yet to airfoils with moving control surfaces or fluid-structure interaction problems. In addition, wind tunnel corrections for this type of unsteady flow problem are considered.

Optimal symmetric flight with an intermediate vehicle model

NASA Technical Reports Server (NTRS)

Menon, P. K. A.; Kelley, H. J.; Cliff, E. M.

1983-01-01

Optimal flight in the vertical plane with a vehicle model intermediate in complexity between the point-mass and energy models is studied. Flight-path angle takes on the role of a control variable. Range-open problems feature subarcs of vertical flight and singular subarcs. The class of altitude-speed-range-time optimization problems with fuel expenditure unspecified is investigated and some interesting phenomena uncovered. The maximum-lift-to-drag glide appears as part of the family, final-time-open, with appropriate initial and terminal transient exceeding level-flight drag, some members exhibiting oscillations. Oscillatory paths generally fail the Jacobi test for durations exceeding a period and furnish a minimum only for short-duration problems.

Implementation method of multi-terminal DC control system

NASA Astrophysics Data System (ADS)

Yi, Liu; Hao-Ran, Huang; Jun-Wen, Zhou; Hong-Guang, Guo; Yu-Yong, Zhou

2018-04-01

Currently the multi-terminal DC system (MTDC) has more stations. Each station needs operators to monitor and control the device. It needs much more operation and maintenance, low efficiency and small reliability; for the most important reason, multi-terminal DC system has complex control mode. If one of the stations has some problem, the control of the whole system should have problems. According to research of the characteristics of multi-terminal DC (VSC-MTDC) systems, this paper presents a strong implementation of the multi-terminal DC Supervisory Control and Data Acquisition (SCADA) system. This system is intelligent, can be networking, integration and intelligent. A master control system is added in each station to communication with the other stations to send current and DC voltage value to pole control system for each station. Based on the practical application and information feedback in the China South Power Grid research center VSC-MTDC project, this system is higher efficiency and save the cost on the maintenance of convertor station to improve the intelligent level and comprehensive effect. And because of the master control system, a multi-terminal system hierarchy coordination control strategy is formed, this make the control and protection system more efficiency and reliability.

Design of bearings for rotor systems based on stability

NASA Technical Reports Server (NTRS)

Dhar, D.; Barrett, L. E.; Knospe, C. R.

1992-01-01

Design of rotor systems incorporating stable behavior is of great importance to manufacturers of high speed centrifugal machinery since destabilizing mechanisms (from bearings, seals, aerodynamic cross coupling, noncolocation effects from magnetic bearings, etc.) increase with machine efficiency and power density. A new method of designing bearing parameters (stiffness and damping coefficients or coefficients of the controller transfer function) is proposed, based on a numerical search in the parameter space. The feedback control law is based on a decentralized low order controller structure, and the various design requirements are specified as constraints in the specification and parameter spaces. An algorithm is proposed for solving the problem as a sequence of constrained 'minimax' problems, with more and more eigenvalues into an acceptable region in the complex plane. The algorithm uses the method of feasible directions to solve the nonlinear constrained minimization problem at each stage. This methodology emphasizes the designer's interaction with the algorithm to generate acceptable designs by relaxing various constraints and changing initial guesses interactively. A design oriented user interface is proposed to facilitate the interaction.

Leadership emergence in engineering design teams.

PubMed

Guastello, Stephen J

2011-01-01

Leaders emerge from leaderless groups as part of a more complex emerging social structure. Several studies have shown that the emerging structure is aptly described by a swallowtail catastrophe model where the control parameters differ depending on whether creative problem solving, production, coordination-intensive, or emergency management groups are involved. The present study explored creative problem solving further where the participants were engaged in real-world tasks extending over several months rather than short laboratory tasks. Participants were engineering students who were organized into groups of to people who designed, built, and tested a prototype product that would solve a real-world problem. At the th week of work they completed a questionnaire indicating who was most like the leader of their group, second most like the leader, along with other questions about individuals' contributions to the group process. Results showed that the swallowtail model (R = .) exhibited a strong advantage over the linear alternative model (R = .) for predicting leadership emergence. The three control variables were control of the task, creative contributions to the group's work, and facilitating the creative contributions of others.

Reducing the cognitive workload: Trouble managing power systems

NASA Technical Reports Server (NTRS)

Manner, David B.; Liberman, Eugene M.; Dolce, James L.; Mellor, Pamela A.

1993-01-01

The complexity of space-based systems makes monitoring them and diagnosing their faults taxing for human beings. Mission control operators are well-trained experts but they can not afford to have their attention diverted by extraneous information. During normal operating conditions monitoring the status of the components of a complex system alone is a big task. When a problem arises, immediate attention and quick resolution is mandatory. To aid humans in these endeavors we have developed an automated advisory system. Our advisory expert system, Trouble, incorporates the knowledge of the power system designers for Space Station Freedom. Trouble is designed to be a ground-based advisor for the mission controllers in the Control Center Complex at Johnson Space Center (JSC). It has been developed at NASA Lewis Research Center (LeRC) and tested in conjunction with prototype flight hardware contained in the Power Management and Distribution testbed and the Engineering Support Center, ESC, at LeRC. Our work will culminate with the adoption of these techniques by the mission controllers at JSC. This paper elucidates how we have captured power system failure knowledge, how we have built and tested our expert system, and what we believe are its potential uses.

Students' conceptual performance on synthesis physics problems with varying mathematical complexity

NASA Astrophysics Data System (ADS)

Ibrahim, Bashirah; Ding, Lin; Heckler, Andrew F.; White, Daniel R.; Badeau, Ryan

2017-06-01

A body of research on physics problem solving has focused on single-concept problems. In this study we use "synthesis problems" that involve multiple concepts typically taught in different chapters. We use two types of synthesis problems, sequential and simultaneous synthesis tasks. Sequential problems require a consecutive application of fundamental principles, and simultaneous problems require a concurrent application of pertinent concepts. We explore students' conceptual performance when they solve quantitative synthesis problems with varying mathematical complexity. Conceptual performance refers to the identification, follow-up, and correct application of the pertinent concepts. Mathematical complexity is determined by the type and the number of equations to be manipulated concurrently due to the number of unknowns in each equation. Data were collected from written tasks and individual interviews administered to physics major students (N =179 ) enrolled in a second year mechanics course. The results indicate that mathematical complexity does not impact students' conceptual performance on the sequential tasks. In contrast, for the simultaneous problems, mathematical complexity negatively influences the students' conceptual performance. This difference may be explained by the students' familiarity with and confidence in particular concepts coupled with cognitive load associated with manipulating complex quantitative equations. Another explanation pertains to the type of synthesis problems, either sequential or simultaneous task. The students split the situation presented in the sequential synthesis tasks into segments but treated the situation in the simultaneous synthesis tasks as a single event.

The Detection Method of Fire Abnormal Based on Directional Drilling in Complex Conditions of Mine

NASA Astrophysics Data System (ADS)

Huijun, Duan; Shijun, Hao; Jie, Feng

2018-06-01

In the light of more and more urgent hidden fire abnormal detection problem in complex conditions of mine, a method which is used directional drilling technology is put forward. The method can avoid the obstacles in mine, and complete the fire abnormal detection. This paper based on analyzing the trajectory control of directional drilling, measurement while drilling and the characteristic of open branch process, the project of the directional drilling is formulated combination with a complex condition mine, and the detection of fire abnormal is implemented. This method can provide technical support for fire prevention, which also can provide a new way for fire anomaly detection in the similar mine.

STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python

PubMed Central

Wils, Stefan; Schutter, Erik De

2008-01-01

We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Initial versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code. PMID:19623245

Emerging Challenges and Opportunities for Education and Research in Weed Science

PubMed Central

Chauhan, Bhagirath S.; Matloob, Amar; Mahajan, Gulshan; Aslam, Farhena; Florentine, Singarayer K.; Jha, Prashant

2017-01-01

In modern agriculture, with more emphasis on high input systems, weed problems are likely to increase and become more complex. With heightened awareness of adverse effects of herbicide residues on human health and environment and the evolution of herbicide-resistant weed biotypes, a significant focus within weed science has now shifted to the development of eco-friendly technologies with reduced reliance on herbicides. Further, with the large-scale adoption of herbicide-resistant crops, and uncertain climatic optima under climate change, the problems for weed science have become multi-faceted. To handle these complex weed problems, a holistic line of action with multi-disciplinary approaches is required, including adjustments to technology, management practices, and legislation. Improved knowledge of weed ecology, biology, genetics, and molecular biology is essential for developing sustainable weed control practices. Additionally, judicious use of advanced technologies, such as site-specific weed management systems and decision support modeling, will play a significant role in reducing costs associated with weed control. Further, effective linkages between farmers and weed researchers will be necessary to facilitate the adoption of technological developments. To meet these challenges, priorities in research need to be determined and the education system for weed science needs to be reoriented. In respect of the latter imperative, closer collaboration between weed scientists and other disciplines can help in defining and solving the complex weed management challenges of the 21st century. This consensus will provide more versatile and diverse approaches to innovative teaching and training practices, which will be needed to prepare future weed science graduates who are capable of handling the anticipated challenges of weed science facing in contemporary agriculture. To build this capacity, mobilizing additional funding for both weed research and weed management education is essential. PMID:28928765

Emerging Challenges and Opportunities for Education and Research in Weed Science.

PubMed

Chauhan, Bhagirath S; Matloob, Amar; Mahajan, Gulshan; Aslam, Farhena; Florentine, Singarayer K; Jha, Prashant

2017-01-01

In modern agriculture, with more emphasis on high input systems, weed problems are likely to increase and become more complex. With heightened awareness of adverse effects of herbicide residues on human health and environment and the evolution of herbicide-resistant weed biotypes, a significant focus within weed science has now shifted to the development of eco-friendly technologies with reduced reliance on herbicides. Further, with the large-scale adoption of herbicide-resistant crops, and uncertain climatic optima under climate change, the problems for weed science have become multi-faceted. To handle these complex weed problems, a holistic line of action with multi-disciplinary approaches is required, including adjustments to technology, management practices, and legislation. Improved knowledge of weed ecology, biology, genetics, and molecular biology is essential for developing sustainable weed control practices. Additionally, judicious use of advanced technologies, such as site-specific weed management systems and decision support modeling, will play a significant role in reducing costs associated with weed control. Further, effective linkages between farmers and weed researchers will be necessary to facilitate the adoption of technological developments. To meet these challenges, priorities in research need to be determined and the education system for weed science needs to be reoriented. In respect of the latter imperative, closer collaboration between weed scientists and other disciplines can help in defining and solving the complex weed management challenges of the 21st century. This consensus will provide more versatile and diverse approaches to innovative teaching and training practices, which will be needed to prepare future weed science graduates who are capable of handling the anticipated challenges of weed science facing in contemporary agriculture. To build this capacity, mobilizing additional funding for both weed research and weed management education is essential.

Computations of Aerodynamic Performance Databases Using Output-Based Refinement

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.

2009-01-01

Objectives: Handle complex geometry problems; Control discretization errors via solution-adaptive mesh refinement; Focus on aerodynamic databases of parametric and optimization studies: 1. Accuracy: satisfy prescribed error bounds 2. Robustness and speed: may require over 105 mesh generations 3. Automation: avoid user supervision Obtain "expert meshes" independent of user skill; and Run every case adaptively in production settings.

The Application of Traditional Martial Arts Practice and Theory to the Treatment of Violent Adolescents.

ERIC Educational Resources Information Center

Twemlow, Stuart W.; Sacco, Frank C.

1998-01-01

Reviews treatment programs, the complex problems posed by youth gangs, and the use of martial arts in the treatment of violence and proposes a program for violent adolescents. The program philosophy is committed to respect and self-control; emphasis is on leadership and community service. Provides clinical examples. (Author/EMK)

THE DIAGNOSIS AND TREATMENT OF SPEECH AND READING PROBLEMS.

ERIC Educational Resources Information Center

DELACATO, CARL H.

THE BASIC THESIS OF THE AUTHOR IS THAT THE NERVOUS SYSTEM OF MAN HAS EVOLVED FROM A VERY SIMPLE TO A VERY COMPLEX MECHANISM. MAN HAS ACHIEVED CORTICAL DOMINANCE WHEREIN ONE SIDE OF THE CORTEX CONTROLS THE SKILLS WHICH SEPARATE MAN FROM OTHER ANIMALS. THIS EVOLUTIONARY PROCESS MUST BE RECAPITULATED ONTOGENETICALLY OR MOBILITY AND COMMUNICATION…

Active flutter suppression using dipole filters

NASA Technical Reports Server (NTRS)

Srinathkumar, S.; Waszak, Martin R.

1992-01-01

By using traditional control concepts of gain root locus, the active suppression of a flutter mode of a flexible wing is examined. It is shown that the attraction of the unstable mode towards a critical system zero determines the degree to which the flutter mode can be stabilized. For control situations where the critical zero is adversely placed in the complex plane, a novel compensation scheme called a 'Dipole' filter is proposed. This filter ensures that the flutter mode is stabilized with acceptable control energy. The control strategy is illustrated by designing flutter suppression laws for an active flexible wing (AFW) wind-tunnel model, where minimal control effort solutions are mandated by control rate saturation problems caused by wind-tunnel turbulence.

Non-adaptive and adaptive hybrid approaches for enhancing water quality management

NASA Astrophysics Data System (ADS)

Kalwij, Ineke M.; Peralta, Richard C.

2008-09-01

SummaryUsing optimization to help solve groundwater management problems cost-effectively is becoming increasingly important. Hybrid optimization approaches, that combine two or more optimization algorithms, will become valuable and common tools for addressing complex nonlinear hydrologic problems. Hybrid heuristic optimizers have capabilities far beyond those of a simple genetic algorithm (SGA), and are continuously improving. SGAs having only parent selection, crossover, and mutation are inefficient and rarely used for optimizing contaminant transport management. Even an advanced genetic algorithm (AGA) that includes elitism (to emphasize using the best strategies as parents) and healing (to help assure optimal strategy feasibility) is undesirably inefficient. Much more efficient than an AGA is the presented hybrid (AGCT), which adds comprehensive tabu search (TS) features to an AGA. TS mechanisms (TS probability, tabu list size, search coarseness and solution space size, and a TS threshold value) force the optimizer to search portions of the solution space that yield superior pumping strategies, and to avoid reproducing similar or inferior strategies. An AGCT characteristic is that TS control parameters are unchanging during optimization. However, TS parameter values that are ideal for optimization commencement can be undesirable when nearing assumed global optimality. The second presented hybrid, termed global converger (GC), is significantly better than the AGCT. GC includes AGCT plus feedback-driven auto-adaptive control that dynamically changes TS parameters during run-time. Before comparing AGCT and GC, we empirically derived scaled dimensionless TS control parameter guidelines by evaluating 50 sets of parameter values for a hypothetical optimization problem. For the hypothetical area, AGCT optimized both well locations and pumping rates. The parameters are useful starting values because using trial-and-error to identify an ideal combination of control parameter values for a new optimization problem can be time consuming. For comparison, AGA, AGCT, and GC are applied to optimize pumping rates for assumed well locations of a complex large-scale contaminant transport and remediation optimization problem at Blaine Naval Ammunition Depot (NAD). Both hybrid approaches converged more closely to the optimal solution than the non-hybrid AGA. GC averaged 18.79% better convergence than AGCT, and 31.9% than AGA, within the same computation time (12.5 days). AGCT averaged 13.1% better convergence than AGA. The GC can significantly reduce the burden of employing computationally intensive hydrologic simulation models within a limited time period and for real-world optimization problems. Although demonstrated for a groundwater quality problem, it is also applicable to other arenas, such as managing salt water intrusion and surface water contaminant loading.

Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

NASA Technical Reports Server (NTRS)

Englander, Jacob; Vavrina, Matthew; Ghosh, Alexander

2015-01-01

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed and in some cases the final destination. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very diserable. This work presents such as an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.

Formative feedback and scaffolding for developing complex problem solving and modelling outcomes

NASA Astrophysics Data System (ADS)

Frank, Brian; Simper, Natalie; Kaupp, James

2018-07-01

This paper discusses the use and impact of formative feedback and scaffolding to develop outcomes for complex problem solving in a required first-year course in engineering design and practice at a medium-sized research-intensive Canadian university. In 2010, the course began to use team-based, complex, open-ended contextualised problems to develop problem solving, communications, teamwork, modelling, and professional skills. Since then, formative feedback has been incorporated into: task and process-level feedback on scaffolded tasks in-class, formative assignments, and post-assignment review. Development in complex problem solving and modelling has been assessed through analysis of responses from student surveys, direct criterion-referenced assessment of course outcomes from 2013 to 2015, and an external longitudinal study. The findings suggest that students are improving in outcomes related to complex problem solving over the duration of the course. Most notably, the addition of new feedback and scaffolding coincided with improved student performance.

Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert

PubMed Central

Schmidt, Henk G.; Rikers, Remy M. J. P.; Custers, Eugene J. F. M.; Splinter, Ted A. W.; van Saase, Jan L. C. M.

2010-01-01

Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices’ decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases. PMID:20354726

Conscious thought beats deliberation without attention in diagnostic decision-making: at least when you are an expert.

PubMed

Mamede, Sílvia; Schmidt, Henk G; Rikers, Remy M J P; Custers, Eugene J F M; Splinter, Ted A W; van Saase, Jan L C M

2010-11-01

Contrary to what common sense makes us believe, deliberation without attention has recently been suggested to produce better decisions in complex situations than deliberation with attention. Based on differences between cognitive processes of experts and novices, we hypothesized that experts make in fact better decisions after consciously thinking about complex problems whereas novices may benefit from deliberation-without-attention. These hypotheses were confirmed in a study among doctors and medical students. They diagnosed complex and routine problems under three conditions, an immediate-decision condition and two delayed conditions: conscious thought and deliberation-without-attention. Doctors did better with conscious deliberation when problems were complex, whereas reasoning mode did not matter in simple problems. In contrast, deliberation-without-attention improved novices' decisions, but only in simple problems. Experts benefit from consciously thinking about complex problems; for novices thinking does not help in those cases.

Mental workload in decision and control

NASA Technical Reports Server (NTRS)

Sheridan, T. B.

1979-01-01

This paper briefly reviews the problems of defining and measuring the 'mental workload' of aircraft pilots and other human operators of complex dynamic systems. Of the alternative approaches the author indicates a clear preference for the use of subjective scaling. Some recent experiments from MIT and elsewhere are described which utilize subjective mental workload scales in conjunction with human decision and control tasks in the laboratory. Finally a new three-dimensional mental workload rating scale, under current development for use by IFR aircraft pilots, is presented.

Transient Oscilliations in Mechanical Systems of Automatic Control with Random Parameters

NASA Astrophysics Data System (ADS)

Royev, B.; Vinokur, A.; Kulikov, G.

2018-04-01

Transient oscillations in mechanical systems of automatic control with random parameters is a relevant but insufficiently studied issue. In this paper, a modified spectral method was applied to investigate the problem. The nature of dynamic processes and the phase portraits are analyzed depending on the amplitude and frequency of external influence. It is evident from the obtained results, that the dynamic phenomena occurring in the systems with random parameters under external influence are complex, and their study requires further investigation.

Preparing new nurses with complexity science and problem-based learning.

PubMed

Hodges, Helen F

2011-01-01

Successful nurses function effectively with adaptability, improvability, and interconnectedness, and can see emerging and unpredictable complex problems. Preparing new nurses for complexity requires a significant change in prevalent but dated nursing education models for rising graduates. The science of complexity coupled with problem-based learning and peer review contributes a feasible framework for a constructivist learning environment to examine real-time systems data; explore uncertainty, inherent patterns, and ambiguity; and develop skills for unstructured problem solving. This article describes a pilot study of a problem-based learning strategy guided by principles of complexity science in a community clinical nursing course. Thirty-five senior nursing students participated during a 3-year period. Assessments included peer review, a final project paper, reflection, and a satisfaction survey. Results were higher than expected levels of student satisfaction, increased breadth and analysis of complex data, acknowledgment of community as complex adaptive systems, and overall higher level thinking skills than in previous years. 2011, SLACK Incorporated.

Neuropsychological functioning in older people with type 2 diabetes: the effect of controlling for confounding factors.

PubMed

Asimakopoulou, K G; Hampson, S E; Morrish, N J

2002-04-01

Neuropsychological functioning was examined in a group of 33 older (mean age 62.40 +/- 9.62 years) people with Type 2 diabetes (Group 1) and 33 non-diabetic participants matched with Group 1 on age, sex, premorbid intelligence and presence of hypertension and cardio/cerebrovascular conditions (Group 2). Data statistically corrected for confounding factors obtained from the diabetic group were compared with the matched control group. The results suggested small cognitive deficits in diabetic people's verbal memory and mental flexibility (Logical Memory A and SS7). No differences were seen between the two samples in simple and complex visuomotor attention, sustained complex visual attention, attention efficiency, mental double tracking, implicit memory, and self-reported memory problems. These findings indicate minimal cognitive impairment in relatively uncomplicated Type 2 diabetes and demonstrate the importance of control and matching for confounding factors.

A distributed finite-element modeling and control approach for large flexible structures

NASA Technical Reports Server (NTRS)

Young, K. D.

1989-01-01

An unconventional framework is described for the design of decentralized controllers for large flexible structures. In contrast to conventional control system design practice which begins with a model of the open loop plant, the controlled plant is assembled from controlled components in which the modeling phase and the control design phase are integrated at the component level. The developed framework is called controlled component synthesis (CCS) to reflect that it is motivated by the well developed Component Mode Synthesis (CMS) methods which were demonstrated to be effective for solving large complex structural analysis problems for almost three decades. The design philosophy behind CCS is also closely related to that of the subsystem decomposition approach in decentralized control.

A study of interactive control scheduling and economic assessment for robotic systems

NASA Technical Reports Server (NTRS)

1982-01-01

A class of interactive control systems is derived by generalizing interactive manipulator control systems. Tasks of interactive control systems can be represented as a network of a finite set of actions which have specific operational characteristics and specific resource requirements, and which are of limited duration. This has enabled the decomposition of the overall control algorithm simultaneously and asynchronously. The performance benefits of sensor referenced and computer-aided control of manipulators in a complex environment is evaluated. The first phase of the CURV arm control system software development and the basic features of the control algorithms and their software implementation are presented. An optimal solution for a production scheduling problem that will be easy to implement in practical situations is investigated.

Integrating a piezoelectric actuator with mechanical and hydraulic devices to control camless engines

NASA Astrophysics Data System (ADS)

Mercorelli, Paolo; Werner, Nils

2016-10-01

The paper deals with some interdisciplinary aspects and problems concerning the actuation control which occur in the integration of a piezoelectric structure in an aggregate actuator consisting of a piezoelectric, a stroke ratio displacement, a mechanical and a hydraulic part. Problems like compensation of the piezo hysteresis effect, scaling force-position to obtain an adequate displacement of the actuator and finally the control of such a complex aggregate system are considered and solved. Even though this work considers a particular application, the solutions proposed in the paper are quite general. In fact, the considered technical aspects occurring in systems which utilize piezoelectric technologies can be used in a variegated gamma of actuators integrating piezoelectric technologies. A cascade controller is proposed to combine a Feedforward action with an internal and an external PI-Controller. The Feedforward Controller is based on the model of the whole actuator, so particular attention is paid to the model structure. The resulting Feedforward action is an adaptive one to compensate hydraulic pressure faults. Real measurements are shown.

Computationally efficient control allocation

NASA Technical Reports Server (NTRS)

Durham, Wayne (Inventor)

2001-01-01

A computationally efficient method for calculating near-optimal solutions to the three-objective, linear control allocation problem is disclosed. The control allocation problem is that of distributing the effort of redundant control effectors to achieve some desired set of objectives. The problem is deemed linear if control effectiveness is affine with respect to the individual control effectors. The optimal solution is that which exploits the collective maximum capability of the effectors within their individual physical limits. Computational efficiency is measured by the number of floating-point operations required for solution. The method presented returned optimal solutions in more than 90% of the cases examined; non-optimal solutions returned by the method were typically much less than 1% different from optimal and the errors tended to become smaller than 0.01% as the number of controls was increased. The magnitude of the errors returned by the present method was much smaller than those that resulted from either pseudo inverse or cascaded generalized inverse solutions. The computational complexity of the method presented varied linearly with increasing numbers of controls; the number of required floating point operations increased from 5.5 i, to seven times faster than did the minimum-norm solution (the pseudoinverse), and at about the same rate as did the cascaded generalized inverse solution. The computational requirements of the method presented were much better than that of previously described facet-searching methods which increase in proportion to the square of the number of controls.

Explicitly solvable complex Chebyshev approximation problems related to sine polynomials

NASA Technical Reports Server (NTRS)

Freund, Roland

1989-01-01

Explicitly solvable real Chebyshev approximation problems on the unit interval are typically characterized by simple error curves. A similar principle is presented for complex approximation problems with error curves induced by sine polynomials. As an application, some new explicit formulae for complex best approximations are derived.

Addressing Complex Challenges through Adaptive Leadership: A Promising Approach to Collaborative Problem Solving

ERIC Educational Resources Information Center

Nelson, Tenneisha; Squires, Vicki

2017-01-01

Organizations are faced with solving increasingly complex problems. Addressing these issues requires effective leadership that can facilitate a collaborative problem solving approach where multiple perspectives are leveraged. In this conceptual paper, we critique the effectiveness of earlier leadership models in tackling complex organizational…

Computer aided reliability, availability, and safety modeling for fault-tolerant computer systems with commentary on the HARP program

NASA Technical Reports Server (NTRS)

Shooman, Martin L.

1991-01-01

Many of the most challenging reliability problems of our present decade involve complex distributed systems such as interconnected telephone switching computers, air traffic control centers, aircraft and space vehicles, and local area and wide area computer networks. In addition to the challenge of complexity, modern fault-tolerant computer systems require very high levels of reliability, e.g., avionic computers with MTTF goals of one billion hours. Most analysts find that it is too difficult to model such complex systems without computer aided design programs. In response to this need, NASA has developed a suite of computer aided reliability modeling programs beginning with CARE 3 and including a group of new programs such as: HARP, HARP-PC, Reliability Analysts Workbench (Combination of model solvers SURE, STEM, PAWS, and common front-end model ASSIST), and the Fault Tree Compiler. The HARP program is studied and how well the user can model systems using this program is investigated. One of the important objectives will be to study how user friendly this program is, e.g., how easy it is to model the system, provide the input information, and interpret the results. The experiences of the author and his graduate students who used HARP in two graduate courses are described. Some brief comparisons were made with the ARIES program which the students also used. Theoretical studies of the modeling techniques used in HARP are also included. Of course no answer can be any more accurate than the fidelity of the model, thus an Appendix is included which discusses modeling accuracy. A broad viewpoint is taken and all problems which occurred in the use of HARP are discussed. Such problems include: computer system problems, installation manual problems, user manual problems, program inconsistencies, program limitations, confusing notation, long run times, accuracy problems, etc.

Research on allocation efficiency of the daisy chain allocation algorithm

NASA Astrophysics Data System (ADS)

Shi, Jingping; Zhang, Weiguo

2013-03-01

With the improvement of the aircraft performance in reliability, maneuverability and survivability, the number of the control effectors increases a lot. How to distribute the three-axis moments into the control surfaces reasonably becomes an important problem. Daisy chain method is simple and easy to be carried out in the design of the allocation system. But it can not solve the allocation problem for entire attainable moment subset. For the lateral-directional allocation problem, the allocation efficiency of the daisy chain can be directly measured by the area of its subset of attainable moments. Because of the non-linear allocation characteristic, the subset of attainable moments of daisy-chain method is a complex non-convex polygon, and it is difficult to solve directly. By analyzing the two-dimensional allocation problems with a "micro-element" idea, a numerical calculation algorithm is proposed to compute the area of the non-convex polygon. In order to improve the allocation efficiency of the algorithm, a genetic algorithm with the allocation efficiency chosen as the fitness function is proposed to find the best pseudo-inverse matrix.

Assessment of optimal control mechanism complexity by experimental landscape Hessian analysis: fragmentation of CH2BrI

NASA Astrophysics Data System (ADS)

Xing, Xi; Rey-de-Castro, Roberto; Rabitz, Herschel

2014-12-01

Optimally shaped femtosecond laser pulses can often be effectively identified in adaptive feedback quantum control experiments, but elucidating the underlying control mechanism can be a difficult task requiring significant additional analysis. We introduce landscape Hessian analysis (LHA) as a practical experimental tool to aid in elucidating control mechanism insights. This technique is applied to the dissociative ionization of CH2BrI using shaped fs laser pulses for optimization of the absolute yields of ionic fragments as well as their ratios for the competing processes of breaking the C-Br and C-I bonds. The experimental results suggest that these nominally complex problems can be reduced to a low-dimensional control space with insights into the control mechanisms. While the optimal yield for some fragments is dominated by a non-resonant intensity-driven process, the optimal generation of other fragments maa difficult task requiring significant additionaly be explained by a non-resonant process coupled to few level resonant dynamics. Theoretical analysis and modeling is consistent with the experimental observations.

Control-structure interaction in precision pointing servo loops

NASA Technical Reports Server (NTRS)

Spanos, John T.

1989-01-01

The control-structure interaction problem is addressed via stability analysis of a generic linear servo loop model. With the plant described by the rigid body mode and a single elastic mode, structural flexibility is categorized into one of three types: (1) appendage, (2) in-the-loop minimum phase, and (3) in-the-loop nonminimum phase. Closing the loop with proportional-derivative (PD) control action and introducing sensor roll-off dynamics in the feedback path, stability conditions are obtained. Trade studies are conducted with modal frequency, modal participation, modal damping, loop bandwidth, and sensor bandwidth treated as free parameters. Results indicate that appendage modes are most likely to produce instability if they are near the sensor rolloff, whereas in-the-loop modes are most dangerous near the loop bandwidth. The main goal of this paper is to provide a fundamental understanding of the control-structure interaction problem so that it may benefit the design of complex spacecraft and pointing system servo loops. In this framework, the JPL Pathfinder gimbal pointer is considered as an example.

Autonomous stair-climbing with miniature jumping robots.

PubMed

Stoeter, Sascha A; Papanikolopoulos, Nikolaos

2005-04-01

The problem of vision-guided control of miniature mobile robots is investigated. Untethered mobile robots with small physical dimensions of around 10 cm or less do not permit powerful onboard computers because of size and power constraints. These challenges have, in the past, reduced the functionality of such devices to that of a complex remote control vehicle with fancy sensors. With the help of a computationally more powerful entity such as a larger companion robot, the control loop can be closed. Using the miniature robot's video transmission or that of an observer to localize it in the world, control commands can be computed and relayed to the inept robot. The result is a system that exhibits autonomous capabilities. The framework presented here solves the problem of climbing stairs with the miniature Scout robot. The robot's unique locomotion mode, the jump, is employed to hop one step at a time. Methods for externally tracking the Scout are developed. A large number of real-world experiments are conducted and the results discussed.

Enhancing the stabilization of aircraft pitch motion control via intelligent and classical method

NASA Astrophysics Data System (ADS)

Lukman, H.; Munawwarah, S.; Azizan, A.; Yakub, F.; Zaki, S. A.; Rasid, Z. A.

2017-12-01

The pitching movement of an aircraft is very important to ensure passengers are intrinsically safe and the aircraft achieve its maximum stability. The equations governing the motion of an aircraft are a complex set of six nonlinear coupled differential equations. Under certain assumptions, it can be decoupled and linearized into longitudinal and lateral equations. Pitch control is a longitudinal problem and thus, only the longitudinal dynamics equations are involved in this system. It is a third order nonlinear system, which is linearized about the operating point. The system is also inherently unstable due to the presence of a free integrator. Because of this, a feedback controller is added in order to solve this problem and enhance the system performance. This study uses two approaches in designing controller: a conventional controller and an intelligent controller. The pitch control scheme consists of proportional, integral and derivatives (PID) for conventional controller and fuzzy logic control (FLC) for intelligent controller. Throughout the paper, the performance of the presented controllers are investigated and compared based on the common criteria of step response. Simulation results have been obtained and analysed by using Matlab and Simulink software. The study shows that FLC controller has higher ability to control and stabilize the aircraft's pitch angle as compared to PID controller.

An optimization-based approach for solving a time-harmonic multiphysical wave problem with higher-order schemes

NASA Astrophysics Data System (ADS)

Mönkölä, Sanna

2013-06-01

This study considers developing numerical solution techniques for the computer simulations of time-harmonic fluid-structure interaction between acoustic and elastic waves. The focus is on the efficiency of an iterative solution method based on a controllability approach and spectral elements. We concentrate on the model, in which the acoustic waves in the fluid domain are modeled by using the velocity potential and the elastic waves in the structure domain are modeled by using displacement. Traditionally, the complex-valued time-harmonic equations are used for solving the time-harmonic problems. Instead of that, we focus on finding periodic solutions without solving the time-harmonic problems directly. The time-dependent equations can be simulated with respect to time until a time-harmonic solution is reached, but the approach suffers from poor convergence. To overcome this challenge, we follow the approach first suggested and developed for the acoustic wave equations by Bristeau, Glowinski, and Périaux. Thus, we accelerate the convergence rate by employing a controllability method. The problem is formulated as a least-squares optimization problem, which is solved with the conjugate gradient (CG) algorithm. Computation of the gradient of the functional is done directly for the discretized problem. A graph-based multigrid method is used for preconditioning the CG algorithm.

Optogenetic Light Crafting Tools for the Control of Cardiac Arrhythmias.

PubMed

Richter, Claudia; Christoph, Jan; Lehnart, Stephan E; Luther, Stefan

2016-01-01

The control of spatiotemporal dynamics in biological systems is a fundamental problem in nonlinear sciences and has important applications in engineering and medicine. Optogenetic tools combined with advanced optical technologies provide unique opportunities to develop and validate novel approaches to control spatiotemporal complexity in neuronal and cardiac systems. Understanding of the mechanisms and instabilities underlying the onset, perpetuation, and control of cardiac arrhythmias will enable the development and translation of novel therapeutic approaches. Here we describe in detail the preparation and optical mapping of transgenic channelrhodopsin-2 (ChR2) mouse hearts, cardiac cell cultures, and the optical setup for photostimulation using digital light processing.

Decentralized stochastic control

NASA Technical Reports Server (NTRS)

Speyer, J. L.

1980-01-01

Decentralized stochastic control is characterized by being decentralized in that the information to one controller is not the same as information to another controller. The system including the information has a stochastic or uncertain component. This complicates the development of decision rules which one determines under the assumption that the system is deterministic. The system is dynamic which means the present decisions affect future system responses and the information in the system. This circumstance presents a complex problem where tools like dynamic programming are no longer applicable. These difficulties are discussed from an intuitive viewpoint. Particular assumptions are introduced which allow a limited theory which produces mechanizable affine decision rules.

The complexities of malaria disease manifestations with a focus on asymptomatic malaria

PubMed Central

2012-01-01

Malaria is a serious parasitic disease in the developing world, causing high morbidity and mortality. The pathogenesis of malaria is complex, and the clinical presentation of disease ranges from severe and complicated, to mild and uncomplicated, to asymptomatic malaria. Despite a wealth of studies on the clinical severity of disease, asymptomatic malaria infections are still poorly understood. Asymptomatic malaria remains a challenge for malaria control programs as it significantly influences transmission dynamics. A thorough understanding of the interaction between hosts and parasites in the development of different clinical outcomes is required. In this review, the problems and obstacles to the study and control of asymptomatic malaria are discussed. The human and parasite factors associated with differential clinical outcomes are described and the management and treatment strategies for the control of the disease are outlined. Further, the crucial gaps in the knowledge of asymptomatic malaria that should be the focus of future research towards development of more effective malaria control strategies are highlighted. PMID:22289302

Microgravity isolation system design: A modern control analysis framework

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Knospe, C. R.; Allaire, P. E.; Grodsinsky, C. M.

1994-01-01

Many acceleration-sensitive, microgravity science experiments will require active vibration isolation from the manned orbiters on which they will be mounted. The isolation problem, especially in the case of a tethered payload, is a complex three-dimensional one that is best suited to modern-control design methods. These methods, although more powerful than their classical counterparts, can nonetheless go only so far in meeting the design requirements for practical systems. Once a tentative controller design is available, it must still be evaluated to determine whether or not it is fully acceptable, and to compare it with other possible design candidates. Realistically, such evaluation will be an inherent part of a necessary iterative design process. In this paper, an approach is presented for applying complex mu-analysis methods to a closed-loop vibration isolation system (experiment plus controller). An analysis framework is presented for evaluating nominal stability, nominal performance, robust stability, and robust performance of active microgravity isolation systems, with emphasis on the effective use of mu-analysis methods.

Complex motion measurement using genetic algorithm

NASA Astrophysics Data System (ADS)

Shen, Jianjun; Tu, Dan; Shen, Zhenkang

1997-12-01

Genetic algorithm (GA) is an optimization technique that provides an untraditional approach to deal with many nonlinear, complicated problems. The notion of motion measurement using genetic algorithm arises from the fact that the motion measurement is virtually an optimization process based on some criterions. In the paper, we propose a complex motion measurement method using genetic algorithm based on block-matching criterion. The following three problems are mainly discussed and solved in the paper: (1) apply an adaptive method to modify the control parameters of GA that are critical to itself, and offer an elitism strategy at the same time (2) derive an evaluate function of motion measurement for GA based on block-matching technique (3) employ hill-climbing (HC) method hybridly to assist GA's search for the global optimal solution. Some other related problems are also discussed. At the end of paper, experiments result is listed. We employ six motion parameters for measurement in our experiments. Experiments result shows that the performance of our GA is good. The GA can find the object motion accurately and rapidly.

The solution of the problem of oil spill risk control in the Baltic Sea taking into account the processes of oil propagation and degradation

NASA Astrophysics Data System (ADS)

Aseev, Nikita; Agoshkov, Valery

2015-04-01

The report is devoted to the one approach to the problem of oil spill risk control of protected areas in the Baltic Sea (Aseev et al., 2014). By the problem of risk control is meant a problem of determination of optimal resources quantity which are necessary for decreasing the risk to some acceptable value. It is supposed that only moment of accident is a random variable. Mass of oil slick is chosen as a function of control. For the realization of the random variable the quadratic 'functional of cost' is introduced. It comprises cleaning costs and deviation of damage of oil pollution from its acceptable value. The problem of minimization of this functional is solved based on the methods of optimal control and the theory of adjoint equations (Agoshkov, 2003, Agoshkov et al., 2012). The solution of this problem is explicitly found. In order to solve the realistic problem of oil spill risk control in the Baltic Sea the 2d model of oil spill propagation on the sea surface based on the Seatrack Web model (Liungman, Mattson, 2011) is developed. The model takes into account such processes as oil transportation by sea currents and wind, turbulent diffusion, spreading, evaporation from sea surface, dispersion and formation of emulsion 'water-in-oil'. The model allows to calculate basic oil slick parameters: localization, mass, volume, thickness, density of oil, water content and viscosity of emulsion. The results of several numerical experiments in the Baltic Sea using the model and the methodology of oil spill risk control are presented. Along with moment of accident other parameters of oil spill and environment could be chosen as a random variables. The methodology of solution of oil spill risk control problem will remain the same but the computational complexity will increase. Conversion of the function of control to quantity of resources with a glance to methods of pollution removal should be processed. As a result, the developed 2d model of oil spill propagation combined with the methodology of solution of oil spill risk control problem could provide the basis for oil spill simulation systems, systems of evaluation and control of oil spill risk and damage in seas or decision support systems. References V.I. Agoshkov. The methods of optimal control and adjoint equations in problems of mathematical physics. // Moscow: INM RAS, 2003, 256 p. (in Russian). V.I. Agoshkov, N.A. Aseev, I.S. Novikov. The methods of investigation and solution of the problems of local sources and local or integral observations. // Moscow: INM RAS, 2012. 151 p. (in Russian). N.A. Aseev, V.I. Agoshkov, V.B. Zalesny, R. Aps, P. Kujala, and J. Rytkonen. The problem of control of oil pollution risk in the Baltic Sea // Russ. J. Numer. Analysis and Math. Modelling, 2014, V 29, No. 2, 93-105. O. Liungman, J. Mattson. Scientific documentation of Seatrack Web; physical processes, algorithms and references, 2011. // https://stw-helcom.smhi.se/

Probabilistic structural mechanics research for parallel processing computers

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Martin, William R.

1991-01-01

Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical.

Satellite-borne active phased array techniques for mobile communications

NASA Astrophysics Data System (ADS)

Sheehan, P. G.; Forrest, J. R.

1986-07-01

This paper investigates the design of active phased arrays for communications satellites. In particular, consideration is given to the problems occurring when active arrays are required to produce multiple beams. There is a real need to keep the complexity of the array electronics to a minimum, but this conflicts with the desire to obtain the greatest possible freedom of control of the radiation pattern produced. The paper demonstrates a method of coping with the problem. Low-gain elements are used to provide design freedom and they are grouped into subarrays to limit the complexity of the rest of the system. With appropriate configurations of subarrays, greatly improved radiation pattern characteristics can be obtained and frequency reuse between multiple beams becomes feasible. A demonstration model of 108 microstrip patches grouped into 32 subarrays, operating at 12 GHz, has been constructed and verifies that the technique is effective.

Complex Langevin simulation of QCD at finite density and low temperature using the deformation technique

NASA Astrophysics Data System (ADS)

Nagata, Keitro; Nishimura, Jun; Shimasaki, Shinji

2018-03-01

We study QCD at finite density and low temperature by using the complex Langevin method. We employ the gauge cooling to control the unitarity norm and intro-duce a deformation parameter in the Dirac operator to avoid the singular-drift problem. The reliability of the obtained results are judged by the probability distribution of the magnitude of the drift term. By making extrapolations with respect to the deformation parameter using only the reliable results, we obtain results for the original system. We perform simulations on a 43 × 8 lattice and show that our method works well even in the region where the reweighing method fails due to the severe sign problem. As a result we observe a delayed onset of the baryon number density as compared with the phase-quenched model, which is a clear sign of the Silver Blaze phenomenon.

Architecture of autonomous systems

NASA Technical Reports Server (NTRS)

Dikshit, Piyush; Guimaraes, Katia; Ramamurthy, Maya; Agrawala, Ashok; Larsen, Ronald L.

1986-01-01

Automation of Space Station functions and activities, particularly those involving robotic capabilities with interactive or supervisory human control, is a complex, multi-disciplinary systems design problem. A wide variety of applications using autonomous control can be found in the literature, but none of them seem to address the problem in general. All of them are designed with a specific application in mind. In this report, an abstract model is described which unifies the key concepts underlying the design of automated systems such as those studied by the aerospace contractors. The model has been kept as general as possible. The attempt is to capture all the key components of autonomous systems. With a little effort, it should be possible to map the functions of any specific autonomous system application to the model presented here.

Energy dissipation in a friction-controlled slide of a body excited by random motions of the foundation

NASA Astrophysics Data System (ADS)

Berezin, Sergey; Zayats, Oleg

2018-01-01

We study a friction-controlled slide of a body excited by random motions of the foundation it is placed on. Specifically, we are interested in such quantities as displacement, traveled distance, and energy loss due to friction. We assume that the random excitation is switched off at some time (possibly infinite) and show that the problem can be treated in an analytic, explicit, manner. Particularly, we derive formulas for the moments of the displacement and distance, and also for the average energy loss. To accomplish that we use the Pugachev-Sveshnikov equation for the characteristic function of a continuous random process given by a system of SDEs. This equation is solved by reduction to a parametric Riemann boundary value problem of complex analysis.

Architecture of autonomous systems

NASA Technical Reports Server (NTRS)

Dikshit, Piyush; Guimaraes, Katia; Ramamurthy, Maya; Agrawala, Ashok; Larsen, Ronald L.

1989-01-01

Automation of Space Station functions and activities, particularly those involving robotic capabilities with interactive or supervisory human control, is a complex, multi-disciplinary systems design problem. A wide variety of applications using autonomous control can be found in the literature, but none of them seem to address the problem in general. All of them are designed with a specific application in mind. In this report, an abstract model is described which unifies the key concepts underlying the design of automated systems such as those studied by the aerospace contractors. The model has been kept as general as possible. The attempt is to capture all the key components of autonomous systems. With a little effort, it should be possible to map the functions of any specific autonomous system application to the model presented here.

Robust intelligent flight control for hypersonic vehicles. Ph.D. Thesis - Massachusetts Inst. of Technology

NASA Technical Reports Server (NTRS)

Chamitoff, Gregory Errol

1992-01-01

Intelligent optimization methods are applied to the problem of real-time flight control for a class of airbreathing hypersonic vehicles (AHSV). The extreme flight conditions that will be encountered by single-stage-to-orbit vehicles, such as the National Aerospace Plane, present a tremendous challenge to the entire spectrum of aerospace technologies. Flight control for these vehicles is particularly difficult due to the combination of nonlinear dynamics, complex constraints, and parametric uncertainty. An approach that utilizes all available a priori and in-flight information to perform robust, real time, short-term trajectory planning is presented.

Information Handling is the Problem

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2001-01-01

This slide presentation reviews the concerns surrounding the automation of information handling. There are two types of decision support software that supports most Space Station Flight Controllers. one is very simple, and the other is very complex. A middle ground is sought. This is the reason for the Human Centered Autonomous and Assistant Systems Testbed (HCAAST) Project. The aim is to study flight controllers at work, and in the bigger picture, with particular attention to how they handle information and how coordination of multiple teams is performed. The focus of the project is on intelligent assistants to assist in handling information for the flight controllers.

The Bright Side of Being Blue: Depression as an Adaptation for Analyzing Complex Problems

ERIC Educational Resources Information Center

Andrews, Paul W.; Thomson, J. Anderson, Jr.

2009-01-01

Depression is the primary emotional condition for which help is sought. Depressed people often report persistent rumination, which involves analysis, and complex social problems in their lives. Analysis is often a useful approach for solving complex problems, but it requires slow, sustained processing, so disruption would interfere with problem…

A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system

NASA Technical Reports Server (NTRS)

Hein, C.; Meystel, A.

1994-01-01

There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.

Stochastic optimal control as non-equilibrium statistical mechanics: calculus of variations over density and current

NASA Astrophysics Data System (ADS)

Chernyak, Vladimir Y.; Chertkov, Michael; Bierkens, Joris; Kappen, Hilbert J.

2014-01-01

In stochastic optimal control (SOC) one minimizes the average cost-to-go, that consists of the cost-of-control (amount of efforts), cost-of-space (where one wants the system to be) and the target cost (where one wants the system to arrive), for a system participating in forced and controlled Langevin dynamics. We extend the SOC problem by introducing an additional cost-of-dynamics, characterized by a vector potential. We propose derivation of the generalized gauge-invariant Hamilton-Jacobi-Bellman equation as a variation over density and current, suggest hydrodynamic interpretation and discuss examples, e.g., ergodic control of a particle-within-a-circle, illustrating non-equilibrium space-time complexity.

A study on special test stand of automatic and manual descent control in presence of simulated g-load effect

NASA Astrophysics Data System (ADS)

Glazkov, Yury; Artjuchin, Yury; Astakhov, Alexander; Vas'kov, Alexander; Malyshev, Veniamin; Mitroshin, Edward; Glinsky, Valery; Moiseenko, Vasily; Makovlev, Vyacheslav

The development of aircraft-type reusable space vehicles (RSV) involves the problem of complete compatibility of automatic, director and manual control. Task decision is complicated, in particular, due to considerable quantitative and qualitative changes of vehicle dynamic characteristics, little stability margins (and even of unstability) of the RSV, and stringent requirements to control accuracy at some flight phases. Besides, during control a pilot is affected by g-loads which hamper motor activity and deteriorate its accuracy, alter the functional status of the visual analyser, and influence higher nervous activity. A study of g-load effects on the control efficiency, especially in manual and director modes, is of primary importance. The main tools for study of a rational selection of manual and director vehicle control systems and as an aid in formulating recommendations for optimum crew-automatic control system interactions are special complex and functional flight simulator test stands. The proposed simulator stand includes a powerful digital computer complex combined with the control system of the centrifuge. The interior of a pilot's vehicle cabin is imitated. A situation image system, pyscho-physical monitoring system, physician, centrifuge operator, and instructor stations are linked with the test stand.

Modeling of the Human - Operator in a Complex System Functioning Under Extreme Conditions

NASA Astrophysics Data System (ADS)

Getzov, Peter; Hubenova, Zoia; Yordanov, Dimitar; Popov, Wiliam

2013-12-01

Problems, related to the explication of sophisticated control systems of objects, operating under extreme conditions, have been examined and the impact of the effectiveness of the operator's activity on the systems as a whole. The necessity of creation of complex simulation models, reflecting operator's activity, is discussed. Organizational and technical system of an unmanned aviation complex is described as a sophisticated ergatic system. Computer realization of main subsystems of algorithmic system of the man as a controlling system is implemented and specialized software for data processing and analysis is developed. An original computer model of a Man as a tracking system has been implemented. Model of unmanned complex for operators training and formation of a mental model in emergency situation, implemented in "matlab-simulink" environment, has been synthesized. As a unit of the control loop, the pilot (operator) is simplified viewed as an autocontrol system consisting of three main interconnected subsystems: sensitive organs (perception sensors); central nervous system; executive organs (muscles of the arms, legs, back). Theoretical-data model of prediction the level of operator's information load in ergatic systems is proposed. It allows the assessment and prediction of the effectiveness of a real working operator. Simulation model of operator's activity in takeoff based on the Petri nets has been synthesized.

Multi Objective Controller Design for Linear System via Optimal Interpolation

NASA Technical Reports Server (NTRS)

Ozbay, Hitay

1996-01-01

We propose a methodology for the design of a controller which satisfies a set of closed-loop objectives simultaneously. The set of objectives consists of: (1) pole placement, (2) decoupled command tracking of step inputs at steady-state, and (3) minimization of step response transients with respect to envelope specifications. We first obtain a characterization of all controllers placing the closed-loop poles in a prescribed region of the complex plane. In this characterization, the free parameter matrix Q(s) is to be determined to attain objectives (2) and (3). Objective (2) is expressed as determining a Pareto optimal solution to a vector valued optimization problem. The solution of this problem is obtained by transforming it to a scalar convex optimization problem. This solution determines Q(O) and the remaining freedom in choosing Q(s) is used to satisfy objective (3). We write Q(s) = (l/v(s))bar-Q(s) for a prescribed polynomial v(s). Bar-Q(s) is a polynomial matrix which is arbitrary except that Q(O) and the order of bar-Q(s) are fixed. Obeying these constraints bar-Q(s) is now to be 'shaped' to minimize the step response characteristics of specific input/output pairs according to the maximum envelope violations. This problem is expressed as a vector valued optimization problem using the concept of Pareto optimality. We then investigate a scalar optimization problem associated with this vector valued problem and show that it is convex. The organization of the report is as follows. The next section includes some definitions and preliminary lemmas. We then give the problem statement which is followed by a section including a detailed development of the design procedure. We then consider an aircraft control example. The last section gives some concluding remarks. The Appendix includes the proofs of technical lemmas, printouts of computer programs, and figures.

Modeling human target acquisition in ground-to-air weapon systems

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Mohr, R. L.; Vikmanis, M.; Wei, K. C.

1982-01-01

The problems associated with formulating and validating mathematical models for describing and predicting human target acquisition response are considered. In particular, the extension of the human observer model to include the acquisition phase as well as the tracking segment is presented. Relationship of the Observer model structure to the more complex Standard Optimal Control model formulation and to the simpler Transfer Function/Noise representation is discussed. Problems pertinent to structural identifiability and the form of the parameterization are elucidated. A systematic approach toward the identification of the observer acquisition model parameters from ensemble tracking error data is presented.

Space Shuttle Plume and Plume Impingement Study

NASA Technical Reports Server (NTRS)

Tevepaugh, J. A.; Penny, M. M.

1977-01-01

The extent of the influence of the propulsion system exhaust plumes on the vehicle performance and control characteristics is a complex function of vehicle geometry, propulsion system geometry, engine operating conditions and vehicle flight trajectory were investigated. Analytical support of the plume technology test program was directed at the two latter problem areas: (1) definition of the full-scale exhaust plume characteristics, (2) application of appropriate similarity parameters; and (3) analysis of wind tunnel test data. Verification of the two-phase plume and plume impingement models was directed toward the definition of the full-scale exhaust plume characteristics and the separation motor impingement problem.

Understanding Wicked Problems: A Key to Advancing Environmental Health Promotion

ERIC Educational Resources Information Center

Kreuter, Marshall W.; De Rosa, Christopher; Howze, Elizabeth H.; Baldwin, Grant T.

2004-01-01

Complex environmental health problems--like air and water pollution, hazardous waste sites, and lead poisoning--are in reality a constellation of linked problems embedded in the fabric of the communities in which they occur. These kinds of complex problems have been characterized by some as "wicked problems" wherein stakeholders may have…

Does the nervous system use equilibrium-point control to guide single and multiple joint movements?

PubMed

Bizzi, E; Hogan, N; Mussa-Ivaldi, F A; Giszter, S

1992-12-01

The hypothesis that the central nervous system (CNS) generates movement as a shift of the limb's equilibrium posture has been corroborated experimentally in studies involving single- and multijoint motions. Posture may be controlled through the choice of muscle length-tension curve that set agonist-antagonist torque-angle curves determining an equilibrium position for the limb and the stiffness about the joints. Arm trajectories seem to be generated through a control signal defining a series of equilibrium postures. The equilibrium-point hypothesis drastically simplifies the requisite computations for multijoint movements and mechanical interactions with complex dynamic objects in the environment. Because the neuromuscular system is springlike, the instantaneous difference between the arm's actual position and the equilibrium position specified by the neural activity can generate the requisite torques, avoiding the complex "inverse dynamic" problem of computing the torques at the joints. The hypothesis provides a simple, unified description of posture and movement as well as contact control task performance, in which the limb must exert force stably and do work on objects in the environment. The latter is a surprisingly difficult problem, as robotic experience has shown. The prior evidence for the hypothesis came mainly from psychophysical and behavioral experiments. Our recent work has shown that microstimulation of the frog spinal cord's premotoneural network produces leg movements to various positions in the frog's motor space. The hypothesis can now be investigated in the neurophysiological machinery of the spinal cord.

Straight from the Field: Reflections on the Director's Job

ERIC Educational Resources Information Center

Spence, Jo-Ann

2004-01-01

The first and perhaps most important thing for a director to remember is that THINGS WILL HAPPEN! The mix of parents, teachers, children, regulations, building problems, and so on is so complex and filled with so many elements out of control that things happening--good and/or bad--is a given. In this article, the author shares some skills from…

Nonlinear analysis of dynamic signature

NASA Astrophysics Data System (ADS)

Rashidi, S.; Fallah, A.; Towhidkhah, F.

2013-12-01

Signature is a long trained motor skill resulting in well combination of segments like strokes and loops. It is a physical manifestation of complex motor processes. The problem, generally stated, is that how relative simplicity in behavior emerges from considerable complexity of perception-action system that produces behavior within an infinitely variable biomechanical and environmental context. To solve this problem, we present evidences which indicate that motor control dynamic in signing process is a chaotic process. This chaotic dynamic may explain a richer array of time series behavior in motor skill of signature. Nonlinear analysis is a powerful approach and suitable tool which seeks for characterizing dynamical systems through concepts such as fractal dimension and Lyapunov exponent. As a result, they can be analyzed in both horizontal and vertical for time series of position and velocity. We observed from the results that noninteger values for the correlation dimension indicates low dimensional deterministic dynamics. This result could be confirmed by using surrogate data tests. We have also used time series to calculate the largest Lyapunov exponent and obtain a positive value. These results constitute significant evidence that signature data are outcome of chaos in a nonlinear dynamical system of motor control.

Dynamic Harmony Search with Polynomial Mutation Algorithm for Valve-Point Economic Load Dispatch

PubMed Central

Karthikeyan, M.; Sree Ranga Raja, T.

2015-01-01

Economic load dispatch (ELD) problem is an important issue in the operation and control of modern control system. The ELD problem is complex and nonlinear with equality and inequality constraints which makes it hard to be efficiently solved. This paper presents a new modification of harmony search (HS) algorithm named as dynamic harmony search with polynomial mutation (DHSPM) algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR) and pitch adjusting rate (PAR) are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods. PMID:26491710

Dynamic Harmony Search with Polynomial Mutation Algorithm for Valve-Point Economic Load Dispatch.

PubMed

Karthikeyan, M; Raja, T Sree Ranga

2015-01-01

Economic load dispatch (ELD) problem is an important issue in the operation and control of modern control system. The ELD problem is complex and nonlinear with equality and inequality constraints which makes it hard to be efficiently solved. This paper presents a new modification of harmony search (HS) algorithm named as dynamic harmony search with polynomial mutation (DHSPM) algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR) and pitch adjusting rate (PAR) are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods.

Multi-Objective Hybrid Optimal Control for Multiple-Flyby Interplanetary Mission Design Using Chemical Propulsion

NASA Technical Reports Server (NTRS)

Englander, Jacob A.; Vavrina, Matthew A.

2015-01-01

Preliminary design of high-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys and the bodies at which those flybys are performed. For some missions, such as surveys of small bodies, the mission designer also contributes to target selection. In addition, real-valued decision variables, such as launch epoch, flight times, maneuver and flyby epochs, and flyby altitudes must be chosen. There are often many thousands of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the impulsive mission design problem as a multiobjective hybrid optimal control problem. The method is demonstrated on several real-world problems.

Methodology and Results of Mathematical Modelling of Complex Technological Processes

NASA Astrophysics Data System (ADS)

Mokrova, Nataliya V.

2018-03-01

The methodology of system analysis allows us to draw a mathematical model of the complex technological process. The mathematical description of the plasma-chemical process was proposed. The importance the quenching rate and initial temperature decrease time was confirmed for producing the maximum amount of the target product. The results of numerical integration of the system of differential equations can be used to describe reagent concentrations, plasma jet rate and temperature in order to achieve optimal mode of hardening. Such models are applicable both for solving control problems and predicting future states of sophisticated technological systems.

Quantitative and qualitative approaches in educational research — problems and examples of controlled understanding through interpretive methods

NASA Astrophysics Data System (ADS)

Neumann, Karl

1987-06-01

In the methodological discussion of recent years it has become apparent that many research problems, including problems relating to the theory of educational science, cannot be solved by using quantitative methods. The multifaceted aspects of human behaviour and all its environment-bound subtle nuances, especially the process of education or the development of identity, cannot fully be taken into account within a rigid neopositivist approach. In employing the paradigm of symbolic interactionism as a suitable model for the analysis of processes of education and formation, the research has generally to start out from complex reciprocal social interactions instead of unambigious connections of causes. In analysing several particular methodological problems, the article demonstrates some weaknesses of quantitative approaches and then shows the advantages in and the necessity for using qualitative research tools.

'Oh my God, I can't handle this!': trainees' emotional responses to complex situations.

PubMed

Helmich, Esther; Diachun, Laura; Joseph, Radha; LaDonna, Kori; Noeverman-Poel, Nelleke; Lingard, Lorelei; Cristancho, Sayra

2018-02-01

Dealing with emotions is critical for medical trainees' professional development. Taking a sociocultural and narrative approach to understanding emotions, we studied complex clinical situations as a specific context in which emotions are evoked and influenced by the social environment. We sought to understand how medical trainees respond to emotions that arise in those situations. In an international constructivist grounded theory study, 29 trainees drew two rich pictures of complex clinical situations, one exciting and one frustrating. Rich pictures are visual representations that capture participants' perceptions about the people, situations and factors that create clinical complexity. These pictures were used to guide semi-structured, individual interviews. We analysed visual materials and interviews in an integrated way, starting with looking at the drawings, doing a 'gallery walk', and using the interviews to inform the aesthetic analysis. Participants' drawings depicted a range of personal emotions in response to complexity, and disclosed unsettling feelings and behaviours that might be considered unprofessional. When trainees felt confident, they were actively participating, engaged in creative problem-solving strategies, and emphasised their personal involvement. When trainees felt the situation was beyond their control, they described how they were running away from the situation, hiding themselves behind others or distancing themselves from patients or families. A sense of control seems to be a key factor influencing trainees' emotional and behavioural responses to complexity. This is problematic, as complex situations are by their nature emergent and dynamic, which limits possibilities for control. Following a social performative approach to emotions, we should help students understand that feeling out of control is an inherent property of participating in complex clinical situations, and, by extension, that it is not something they will 'grow out of' with expertise. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Nonlinear dynamical systems for theory and research in ergonomics.

PubMed

Guastello, Stephen J

2017-02-01

Nonlinear dynamical systems (NDS) theory offers new constructs, methods and explanations for phenomena that have in turn produced new paradigms of thinking within several disciplines of the behavioural sciences. This article explores the recent developments of NDS as a paradigm in ergonomics. The exposition includes its basic axioms, the primary constructs from elementary dynamics and so-called complexity theory, an overview of its methods, and growing areas of application within ergonomics. The applications considered here include: psychophysics, iconic displays, control theory, cognitive workload and fatigue, occupational accidents, resilience of systems, team coordination and synchronisation in systems. Although these applications make use of different subsets of NDS constructs, several of them share the general principles of the complex adaptive system. Practitioner Summary: Nonlinear dynamical systems theory reframes problems in ergonomics that involve complex systems as they change over time. The leading applications to date include psychophysics, control theory, cognitive workload and fatigue, biomechanics, occupational accidents, resilience of systems, team coordination and synchronisation of system components.

Distributed Cooperation Solution Method of Complex System Based on MAS

NASA Astrophysics Data System (ADS)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

Hybrid Systems Diagnosis

NASA Technical Reports Server (NTRS)

McIlraith, Sheila; Biswas, Gautam; Clancy, Dan; Gupta, Vineet

2005-01-01

This paper reports on an on-going Project to investigate techniques to diagnose complex dynamical systems that are modeled as hybrid systems. In particular, we examine continuous systems with embedded supervisory controllers that experience abrupt, partial or full failure of component devices. We cast the diagnosis problem as a model selection problem. To reduce the space of potential models under consideration, we exploit techniques from qualitative reasoning to conjecture an initial set of qualitative candidate diagnoses, which induce a smaller set of models. We refine these diagnoses using parameter estimation and model fitting techniques. As a motivating case study, we have examined the problem of diagnosing NASA's Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.

Decision-Theoretic Control of Planetary Rovers

NASA Technical Reports Server (NTRS)

Zilberstein, Shlomo; Washington, Richard; Bernstein, Daniel S.; Mouaddib, Abdel-Illah; Morris, Robert (Technical Monitor)

2003-01-01

Planetary rovers are small unmanned vehicles equipped with cameras and a variety of sensors used for scientific experiments. They must operate under tight constraints over such resources as operation time, power, storage capacity, and communication bandwidth. Moreover, the limited computational resources of the rover limit the complexity of on-line planning and scheduling. We describe two decision-theoretic approaches to maximize the productivity of planetary rovers: one based on adaptive planning and the other on hierarchical reinforcement learning. Both approaches map the problem into a Markov decision problem and attempt to solve a large part of the problem off-line, exploiting the structure of the plan and independence between plan components. We examine the advantages and limitations of these techniques and their scalability.

Social cognition in borderline personality disorder: evidence for dichotomous thinking but no evidence for less complex attributions.

PubMed

Arntz, Arnoud; ten Haaf, José

2012-11-01

This experiment investigated social cognition in borderline personality disorder (BPD). We tested whether BPD-patients' evaluations of others were characterized by splitting, dichotomous thinking, or negativity; and whether they showed less complex understanding of others. Participants discussed a problem with three alleged mental health worker trainees, performing three interpersonal roles (rejecting, accepting and neutral). Participants evaluated trainees in a structured response format and in a semi-structured interview. BPD-patients (n = 18) were compared to Cluster-C personality disorder patients (n = 18) and nonpatients (n = 18). From visual analog scales with opposite trait descriptions (structured response format) negativity, dichotomous thinking, and splitting scores were derived. The interviews were scored by an independent rater on affect tone, differentiation, and complexity of attributions. BPD-patients showed, in all conditions, and in both response formats, more dichotomous thinking than control groups. Evidence for splitting as specific BPD-characteristic was not convincing, and more negativity in BPD was only found with the rejecting role and structured responses. The interview-based evaluations by BPD-patients could not be discriminated from nonpatients in cognitive complexity. Results indicate that dichotomous thinking, and not so much splitting, negativity, or less complexity, is central in the interpretation of others by BPD-patients. Treatment might address dichotomous thinking to reduce BPD-patients' interpersonal problems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Preparing for Complexity and Wicked Problems through Transformational Learning Approaches

ERIC Educational Resources Information Center

Yukawa, Joyce

2015-01-01

As the information environment becomes increasingly complex and challenging, Library and Information Studies (LIS) education is called upon to nurture innovative leaders capable of managing complex situations and "wicked problems." While disciplinary expertise remains essential, higher levels of mental complexity and adaptive…

Complexity in Nature and Society: Complexity Management in the Age of Globalization

NASA Astrophysics Data System (ADS)

Mainzer, Klaus

The theory of nonlinear complex systems has become a proven problem-solving approach in the natural sciences from cosmic and quantum systems to cellular organisms and the brain. Even in modern engineering science self-organizing systems are developed to manage complex networks and processes. It is now recognized that many of our ecological, social, economic, and political problems are also of a global, complex, and nonlinear nature. What are the laws of sociodynamics? Is there a socio-engineering of nonlinear problem solving? What can we learn from nonlinear dynamics for complexity management in social, economic, financial and political systems? Is self-organization an acceptable strategy to handle the challenges of complexity in firms, institutions and other organizations? It is a main thesis of the talk that nature and society are basically governed by nonlinear and complex information dynamics. How computational is sociodynamics? What can we hope for social, economic and political problem solving in the age of globalization?.

Controle du vol longitudinal d'un avion civil avec satisfaction de qualiies de manoeuvrabilite

NASA Astrophysics Data System (ADS)

Saussie, David Alexandre

2010-03-01

Fulfilling handling qualities still remains a challenging problem during flight control design. These criteria of different nature are derived from a wide experience based upon flight tests and data analysis, and they have to be considered if one expects a good behaviour of the aircraft. The goal of this thesis is to develop synthesis methods able to satisfy these criteria with fixed classical architectures imposed by the manufacturer or with a new flight control architecture. This is applied to the longitudinal flight model of a Bombardier Inc. business jet aircraft, namely the Challenger 604. A first step of our work consists in compiling the most commonly used handling qualities in order to compare them. A special attention is devoted to the dropback criterion for which theoretical analysis leads us to establish a practical formulation for synthesis purpose. Moreover, the comparison of the criteria through a reference model highlighted dominant criteria that, once satisfied, ensure that other ones are satisfied too. Consequently, we are able to consider the fulfillment of these criteria in the fixed control architecture framework. Guardian maps (Saydy et al., 1990) are then considered to handle the problem. Initially for robustness study, they are integrated in various algorithms for controller synthesis. Incidently, this fixed architecture problem is similar to the static output feedback stabilization problem and reduced-order controller synthesis. Algorithms performing stabilization and pole assignment in a specific region of the complex plane are then proposed. Afterwards, they are extended to handle the gain-scheduling problem. The controller is then scheduled through the entire flight envelope with respect to scheduling parameters. Thereafter, the fixed architecture is put aside while only conserving the same output signals. The main idea is to use Hinfinity synthesis to obtain an initial controller satisfying handling qualities thanks to reference model pairing and robust versus mass and center of gravity variations. Using robust modal control (Magni, 2002), we are able to reduce substantially the controller order and to structure it in order to come close to a classical architecture. An auto-scheduling method finally allows us to schedule the controller with respect to scheduling parameters. Two different paths are used to solve the same problem; each one exhibits its own advantages and disadvantages.

Identifying partial topology of complex dynamical networks via a pinning mechanism

NASA Astrophysics Data System (ADS)

Zhu, Shuaibing; Zhou, Jin; Lu, Jun-an

2018-04-01

In this paper, we study the problem of identifying the partial topology of complex dynamical networks via a pinning mechanism. By using the network synchronization theory and the adaptive feedback controlling method, we propose a method which can greatly reduce the number of nodes and observers in the response network. Particularly, this method can also identify the whole topology of complex networks. A theorem is established rigorously, from which some corollaries are also derived in order to make our method more cost-effective. Several numerical examples are provided to verify the effectiveness of the proposed method. In the simulation, an approach is also given to avoid possible identification failure caused by inner synchronization of the drive network.

Enhancing chemistry problem-solving achievement using problem categorization

NASA Astrophysics Data System (ADS)

Bunce, Diane M.; Gabel, Dorothy L.; Samuel, John V.

The enhancement of chemistry students' skill in problem solving through problem categorization is the focus of this study. Twenty-four students in a freshman chemistry course for health professionals are taught how to solve problems using the explicit method of problem solving (EMPS) (Bunce & Heikkinen, 1986). The EMPS is an organized approach to problem analysis which includes encoding the information given in a problem (Given, Asked For), relating this to what is already in long-term memory (Recall), and planning a solution (Overall Plan) before a mathematical solution is attempted. In addition to the EMPS training, treatment students receive three 40-minute sessions following achievement tests in which they are taught how to categorize problems. Control students use this time to review the EMPS solutions of test questions. Although problem categorization is involved in one section of the EMPS (Recall), treatment students who received specific training in problem categorization demonstrate significantly higher achievement on combination problems (those problems requiring the use of more than one chemical topic for their solution) at (p = 0.01) than their counterparts. Significantly higher achievement for treatment students is also measured on an unannounced test (p = 0.02). Analysis of interview transcripts of both treatment and control students illustrates a Rolodex approach to problem solving employed by all students in this study. The Rolodex approach involves organizing equations used to solve problems on mental index cards and flipping through them, matching units given when a new problem is to be solved. A second phenomenon observed during student interviews is the absence of a link in the conceptual understanding of the chemical concepts involved in a problem and the problem-solving skills employed to correctly solve problems. This study shows that explicit training in categorization skills and the EMPS can lead to higher achievement in complex problem-solving situations (combination problems and unannounced test). However, such achievement may be limited by the lack of linkages between students' conceptual understanding and improved problem-solving skill.

How Cognitive Style and Problem Complexity Affect Preservice Agricultural Education Teachers' Abilities to Solve Problems in Agricultural Mechanics

ERIC Educational Resources Information Center

Blackburn, J. Joey; Robinson, J. Shane; Lamm, Alexa J.

2014-01-01

The purpose of this experimental study was to determine the effects of cognitive style and problem complexity on Oklahoma State University preservice agriculture teachers' (N = 56) ability to solve problems in small gasoline engines. Time to solution was operationalized as problem solving ability. Kirton's Adaption-Innovation Inventory was…

On the Complexity of Delaying an Adversary’s Project

DTIC Science & Technology

2005-01-01

interdiction models for such problems and show that the resulting problem com- plexities run the gamut : polynomially solvable, weakly NP-complete, strongly...problems and show that the resulting problem complexities run the gamut : polynomially solvable, weakly NP-complete, strongly NP-complete or NP-hard. We

Using Agent-Based Modeling to Enhance System-Level Real-time Control of Urban Stormwater Systems

NASA Astrophysics Data System (ADS)

Rimer, S.; Mullapudi, A. M.; Kerkez, B.

2017-12-01

The ability to reduce combined-sewer overflow (CSO) events is an issue that challenges over 800 U.S. municipalities. When the volume of a combined sewer system or wastewater treatment plant is exceeded, untreated wastewater then overflows (a CSO event) into nearby streams, rivers, or other water bodies causing localized urban flooding and pollution. The likelihood and impact of CSO events has only exacerbated due to urbanization, population growth, climate change, aging infrastructure, and system complexity. Thus, there is an urgent need for urban areas to manage CSO events. Traditionally, mitigating CSO events has been carried out via time-intensive and expensive structural interventions such as retention basins or sewer separation, which are able to reduce CSO events, but are costly, arduous, and only provide a fixed solution to a dynamic problem. Real-time control (RTC) of urban drainage systems using sensor and actuator networks has served as an inexpensive and versatile alternative to traditional CSO intervention. In particular, retrofitting individual stormwater elements for sensing and automated active distributed control has been shown to significantly reduce the volume of discharge during CSO events, with some RTC models demonstrating a reduction upwards of 90% when compared to traditional passive systems. As more stormwater elements become retrofitted for RTC, system-level RTC across complete watersheds is an attainable possibility. However, when considering the diverse set of control needs of each of these individual stormwater elements, such system-level RTC becomes a far more complex problem. To address such diverse control needs, agent-based modeling is employed such that each individual stormwater element is treated as an autonomous agent with a diverse decision making capabilities. We present preliminary results and limitations of utilizing the agent-based modeling computational framework for the system-level control of diverse, interacting stormwater elements.

Entrepreneurial proliferation: Russia`s nuclear industry suits the buyers market. Master`s thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whalen, T.D.; Williams, A.R.

1995-06-01

The Soviet Union collapsed in December 1991, bringing an end to four decades of the Cold War. A system of tight centralized controls has given way to chaotic freedom and un-managed, entrepreneurial capitalism. Of immediate concern to most world leaders has been the control and safety of over 30,000 Soviet nuclear weapons. After 1991, the Soviet, centralized system of management lost one key structural element: a reliable `human factor` for nuclear material control. The Soviet systems for physical security and material control are still in place in the nuclear inheritor states - Russia, Ukraine, Khazakhnstan, and Belarus - but theymore » do not restrain or regulate their nuclear industry. In the chaos created by the Soviet collapse, the nonproliferation regime may not adequately temper the supply of the nuclear materials of the new inheritor states. This could permit organizations or states seeking nuclear weapons easier access to fissile materials. New initiatives such as the United States Cooperative Threat Reduction program, which draws upon U.S. technology and expertise to help the NIS solve these complex problems, are short-tern tactics. At present there are no strategies which address the long-tern root problems caused by the Soviet collapse.This thesis demonstrates the extent of the nuclear control problems in Russia. Specifically, we examine physical security, material control and accounting regulation and enforcement, and criminal actions. It reveals that the current lack of internal controls make access to nuclear materials easier for aspiring nuclear weapons States.« less

Associating quantitative behavioral traits with gene expression in the brain: searching for diamonds in the hay.

PubMed

Reiner-Benaim, Anat; Yekutieli, Daniel; Letwin, Noah E; Elmer, Gregory I; Lee, Norman H; Kafkafi, Neri; Benjamini, Yoav

2007-09-01

Gene expression and phenotypic functionality can best be associated when they are measured quantitatively within the same experiment. The analysis of such a complex experiment is presented, searching for associations between measures of exploratory behavior in mice and gene expression in brain regions. The analysis of such experiments raises several methodological problems. First and foremost, the size of the pool of potential discoveries being screened is enormous yet only few biologically relevant findings are expected, making the problem of multiple testing especially severe. We present solutions based on screening by testing related hypotheses, then testing the hypotheses of interest. In one variant the subset is selected directly, in the other one a tree of hypotheses is tested hierarchical; both variants control the False Discovery Rate (FDR). Other problems in such experiments are in the fact that the level of data aggregation may be different for the quantitative traits (one per animal) and gene expression measurements (pooled across animals); in that the association may not be linear; and in the resolution of interest only few replications exist. We offer solutions to these problems as well. The hierarchical FDR testing strategies presented here can serve beyond the structure of our motivating example study to any complex microarray study. Supplementary data are available at Bioinformatics online.

Air pollution engineering

NASA Astrophysics Data System (ADS)

Maduna, Karolina; Tomašić, Vesna

2017-11-01

Air pollution is an environmental and a social problem which leads to a multitude of adverse effects on human health and standard of human life, state of the ecosystems and global change of climate. Air pollutants are emitted from natural, but mostly from anthropogenic sources and may be transported over long distances. Some air pollutants are extremely stable in the atmosphere and may accumulate in the environment and in the food chain, affecting human beings, animals and natural biodiversity. Obviously, air pollution is a complex problem that poses multiple challenges in terms of management and abatements of the pollutants emission. Effective approach to the problems of air pollution requires a good understanding of the sources that cause it, knowledge of air quality status and future trends as well as its impact on humans and ecosystems. This chapter deals with the complexities of the air pollution and presents an overview of different technical processes and equipment for air pollution control, as well as basic principles of their work. The problems of air protection as well as protection of other ecosystems can be solved only by the coordinated endeavors of various scientific and engineering disciplines, such as chemistry, physics, biology, medicine, chemical engineering and social sciences. The most important engineering contribution is mostly focused on development, design and operation of equipment for the abatement of harmful emissions into environment.

Solving the Inverse-Square Problem with Complex Variables

ERIC Educational Resources Information Center

Gauthier, N.

2005-01-01

The equation of motion for a mass that moves under the influence of a central, inverse-square force is formulated and solved as a problem in complex variables. To find the solution, the constancy of angular momentum is first established using complex variables. Next, the complex position coordinate and complex velocity of the particle are assumed…

Hybrid Nanomaterials with Single-Site Catalysts by Spatially Controllable Immobilization of Nickel Complexes via Photoclick Chemistry for Alkene Epoxidation.

PubMed

Ghosh, Dwaipayan; Febriansyah, Benny; Gupta, Disha; Ng, Leonard Kia-Sheun; Xi, Shibo; Du, Yonghua; Baikie, Tom; Dong, ZhiLi; Soo, Han Sen

2018-05-22

Catalyst deactivation is a persistent problem not only for the scientific community but also in industry. Isolated single-site heterogeneous catalysts have shown great promise to overcome these problems. Here, a versatile anchoring strategy for molecular complex immobilization on a broad range of semiconducting or insulating metal oxide ( e. g., titanium dioxide, mesoporous silica, cerium oxide, and tungsten oxide) nanoparticles to synthesize isolated single-site catalysts has been studied systematically. An oxidatively stable anchoring group, maleimide, is shown to form covalent linkages with surface hydroxyl functionalities of metal oxide nanoparticles by photoclick chemistry. The nanocomposites have been thoroughly characterized by techniques including UV-visible diffuse reflectance spectroscopy, high-resolution transmission electron microscopy, X-ray photoelectron spectroscopy, infrared spectroscopy, and X-ray absorption spectroscopy (XAS). The IR spectroscopic studies confirm the covalent linkages between the maleimide group and surface hydroxyl functionalities of the oxide nanoparticles. The hybrid nanomaterials function as highly efficient catalysts for essentially quantitative oxidations of terminal and internal alkenes and show molecular catalyst product selectivities even in more eco-friendly solvents. XAS studies verify the robustness of the catalysts after several catalytic cycles. We have applied the photoclick anchoring methodology to precisely control the deposition of a luminescent variant of our catalyst on the metal oxide nanoparticles. Overall, we demonstrate a general approach to use irradiation to anchor molecular complexes on oxide nanoparticles to create recyclable, hybrid, single-site catalysts that function with high selectivity in a broad range of solvents. We have achieved a facile, spatially and temporally controllable photoclick method that can potentially be extended to other ligands, catalysts, functional molecules, and surfaces.

Carbohydrate-Based Host-Guest Complexation of Hydrophobic Antibiotics for the Enhancement of Antibacterial Activity.

PubMed

Jeong, Daham; Joo, Sang-Woo; Shinde, Vijay Vilas; Cho, Eunae; Jung, Seunho

2017-08-08

Host-guest complexation with various hydrophobic drugs has been used to enhance the solubility, permeability, and stability of guest drugs. Physical changes in hydrophobic drugs by complexation have been related to corresponding increases in the bioavailability of these drugs. Carbohydrates, including various derivatives of cyclodextrins, cyclosophoraoses, and some linear oligosaccharides, are generally used as host complexation agents in drug delivery systems. Many antibiotics with low bioavailability have some limitations to their clinical use due to their intrinsically poor aqueous solubility. Bioavailability enhancement is therefore an important step to achieve the desired concentration of antibiotics in the treatment of bacterial infections. Antibiotics encapsulated in a complexation-based drug delivery system will display improved antibacterial activity making it possible to reduce dosages and overcome the serious global problem of antibiotic resistance. Here, we review the present research trends in carbohydrate-based host-guest complexation of various hydrophobic antibiotics as an efficient delivery system to improve solubility, permeability, stability, and controlled release.

How do precision medicine and system biology response to human body's complex adaptability?

PubMed

Yuan, Bing

2016-12-01

In the field of life sciences, although system biology and "precision medicine" introduce some complex scientifific methods and techniques, it is still based on the "analysis-reconstruction" of reductionist theory as a whole. Adaptability of complex system increase system behaviour uncertainty as well as the difficulties of precise identifification and control. It also put systems biology research into trouble. To grasp the behaviour and characteristics of organism fundamentally, systems biology has to abandon the "analysis-reconstruction" concept. In accordance with the guidelines of complexity science, systems biology should build organism model from holistic level, just like the Chinese medicine did in dealing with human body and disease. When we study the living body from the holistic level, we will fifind the adaptability of complex system is not the obstacle that increases the diffificulty of problem solving. It is the "exceptional", "right-hand man" that helping us to deal with the complexity of life more effectively.

Control-oriented modeling and adaptive backstepping control for a nonminimum phase hypersonic vehicle.

PubMed

Ye, Linqi; Zong, Qun; Tian, Bailing; Zhang, Xiuyun; Wang, Fang

2017-09-01

In this paper, the nonminimum phase problem of a flexible hypersonic vehicle is investigated. The main challenge of nonminimum phase is the prevention of dynamic inversion methods to nonlinear control design. To solve this problem, we make research on the relationship between nonminimum phase and backstepping control, finding that a stable nonlinear controller can be obtained by changing the control loop on the basis of backstepping control. By extending the control loop to cover the internal dynamics in it, the internal states are directly controlled by the inputs and simultaneously serve as virtual control for the external states, making it possible to guarantee output tracking as well as internal stability. Then, based on the extended control loop, a simplified control-oriented model is developed to enable the applicability of adaptive backstepping method. It simplifies the design process and releases some limitations caused by direct use of the no simplified control-oriented model. Next, under proper assumptions, asymptotic stability is proved for constant commands, while bounded stability is proved for varying commands. The proposed method is compared with approximate backstepping control and dynamic surface control and is shown to have superior tracking accuracy as well as robustness from the simulation results. This paper may also provide a beneficial guidance for control design of other complex systems. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Dynamic Modeling as a Cognitive Regulation Scaffold for Developing Complex Problem-Solving Skills in an Educational Massively Multiplayer Online Game Environment

ERIC Educational Resources Information Center

Eseryel, Deniz; Ge, Xun; Ifenthaler, Dirk; Law, Victor

2011-01-01

Following a design-based research framework, this article reports two empirical studies with an educational MMOG, called "McLarin's Adventures," on facilitating 9th-grade students' complex problem-solving skill acquisition in interdisciplinary STEM education. The article discusses the nature of complex and ill-structured problem solving…

Pre-Service Teachers' Free and Structured Mathematical Problem Posing

ERIC Educational Resources Information Center

Silber, Steven; Cai, Jinfa

2017-01-01

This exploratory study examined how pre-service teachers (PSTs) pose mathematical problems for free and structured mathematical problem-posing conditions. It was hypothesized that PSTs would pose more complex mathematical problems under structured posing conditions, with increasing levels of complexity, than PSTs would pose under free posing…

A low-complexity attitude control method for large-angle agile maneuvers of a spacecraft with control moment gyros

NASA Astrophysics Data System (ADS)

Kawajiri, Shota; Matunaga, Saburo

2017-10-01

This study examines a low-complexity control method that satisfies mechanical constraints by using control moment gyros for an agile maneuver. The method is designed based on the fact that a simple rotation around an Euler's principal axis corresponds to a well-approximated solution of a time-optimal rest-to-rest maneuver. With respect to an agile large-angle maneuver using CMGs, it is suggested that there exists a coasting period in which all gimbal angles are constant, and a constant body angular velocity is almost along the Euler's principal axis. The gimbals are driven such that the coasting period is generated in the proposed method. This allows the problem to be converted into obtaining only a coasting time and gimbal angles such that their combination maximizes body angular velocity along the rotational axis of the maneuver. The effectiveness of the proposed method is demonstrated by using numerical simulations. The results indicate that the proposed method shortens the settling time by 20-70% when compared to that of a traditional feedback method. Additionally, a comparison with an existing path planning method shows that the proposed method achieves a low computational complexity (that is approximately 150 times faster) and a certain level of shortness in the settling time.

Global dynamic optimization approach to predict activation in metabolic pathways.

PubMed

de Hijas-Liste, Gundián M; Klipp, Edda; Balsa-Canto, Eva; Banga, Julio R

2014-01-06

During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been successfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework. In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results. The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints.

A restricted Steiner tree problem is solved by Geometric Method II

NASA Astrophysics Data System (ADS)

Lin, Dazhi; Zhang, Youlin; Lu, Xiaoxu

2013-03-01

The minimum Steiner tree problem has wide application background, such as transportation system, communication network, pipeline design and VISL, etc. It is unfortunately that the computational complexity of the problem is NP-hard. People are common to find some special problems to consider. In this paper, we first put forward a restricted Steiner tree problem, which the fixed vertices are in the same side of one line L and we find a vertex on L such the length of the tree is minimal. By the definition and the complexity of the Steiner tree problem, we know that the complexity of this problem is also Np-complete. In the part one, we have considered there are two fixed vertices to find the restricted Steiner tree problem. Naturally, we consider there are three fixed vertices to find the restricted Steiner tree problem. And we also use the geometric method to solve such the problem.

A study of the performance of patients with frontal lobe lesions in a financial planning task.

PubMed

Goel, V; Grafman, J; Tajik, J; Gana, S; Danto, D

1997-10-01

It has long been argued that patients with lesions in the prefrontal cortex have difficulties in decision making and problem solving in real-world, ill-structured situations, particularly problem types involving planning and look-ahead components. Recently, several researchers have questioned our ability to capture and characterize these deficits adequately using just the standard neuropsychological test batteries, and have called for tests that reflect real-world task requirements more accurately. We present data from 10 patients with focal lesions to the prefrontal cortex and 10 normal control subjects engaged in a real-world financial planning task. We also introduce a theoretical framework and methodology developed in the cognitive science literature for quantifying and analysing the complex data generated by problem-solving tasks. Our findings indicate that patient performance is impoverished at a global level but not at the local level. Patients have difficulty in organizing and structuring their problem space. Once they begin problem solving, they have difficulty in allocating adequate effort to each problem-solving phase. Patients also have difficulty dealing with the fact that there are no right or wrong answers nor official termination points in real-world planning problems. They also find it problematic to generate their own feedback. They invariably terminate the session before the details are fleshed out and all the goals satisfied. Finally, patients do not take full advantage of the fact that constraints on real-world problems are negotiable. However, it is not necessary to postulate a 'planning' deficit. It is possible to understand the patients' difficulties in real world planning tasks in terms of the following four accepted deficits: inadequate access to 'structured event complexes', difficulty in generalizing from particulars, failure to shift between 'mental sets', and poor judgment regarding adequacy and completeness of a plan.

Optimal aeroassisted orbital transfer with plane change using collocation and nonlinear programming

NASA Technical Reports Server (NTRS)

Shi, Yun. Y.; Nelson, R. L.; Young, D. H.

1990-01-01

The fuel optimal control problem arising in the non-planar orbital transfer employing aeroassisted technology is addressed. The mission involves the transfer from high energy orbit (HEO) to low energy orbit (LEO) with orbital plane change. The basic strategy here is to employ a combination of propulsive maneuvers in space and aerodynamic maneuvers in the atmosphere. The basic sequence of events for the aeroassisted HEO to LEO transfer consists of three phases. In the first phase, the orbital transfer begins with a deorbit impulse at HEO which injects the vehicle into an elliptic transfer orbit with perigee inside the atmosphere. In the second phase, the vehicle is optimally controlled by lift and bank angle modulations to perform the desired orbital plane change and to satisfy heating constraints. Because of the energy loss during the turn, an impulse is required to initiate the third phase to boost the vehicle back to the desired LEO orbital altitude. The third impulse is then used to circularize the orbit at LEO. The problem is solved by a direct optimization technique which uses piecewise polynomial representation for the state and control variables and collocation to satisfy the differential equations. This technique converts the optimal control problem into a nonlinear programming problem which is solved numerically. Solutions were obtained for cases with and without heat constraints and for cases of different orbital inclination changes. The method appears to be more powerful and robust than other optimization methods. In addition, the method can handle complex dynamical constraints.

Self-Control, Daily Negative Affect and Blood Glucose Control in Adolescents with Type 1 Diabetes

PubMed Central

Lansing, Amy Hughes; Berg, Cynthia A.; Butner, Jonathan; Wiebe, Deborah J.

2016-01-01

Objective For adolescents with type 1 diabetes, maintaining optimal daily blood glucose control is a complex self-regulatory process that likely requires self-control. This study examined whether higher self-control was associated with lower daily negative affect about diabetes and, in turn, better daily blood glucose control, i.e., lower mean daily blood glucose (MBG) and smaller standard deviations of daily blood glucose (SDBG), through two paths: 1) self-control maintaining lower mean level of negative affect and 2) self-control buffering the association of the number of daily diabetes problems with daily negative affect. Methods Adolescents (M age=12.87 years) with type 1 diabetes (n=180) completed an initial survey containing a self-report measure of self-control. Nightly electronic diaries were completed for 14 days where adolescents reported daily problems with and negative affect about diabetes, and used a study-provided blood glucose meter. Results Hypotheses were examined through multilevel modeling. Lower mean levels of daily negative affect partially mediated the relation between higher adolescent self-control and lower MBG. Adolescent self-control also buffered the association of the number of daily problems with daily negative affect, and smaller fluctuations in daily negative affect were associated with lower SDBG. Conclusions Adolescent self-control is associated with daily affect regulatory processes that may influence MBG. However, fluctuations in daily negative affect about diabetes may represent a unique within-person daily process associated with SDBG. These findings suggest that studies examining daily disease processes and interventions targeting daily affect regulation may be important to improving health in adolescents with type 1 diabetes. PMID:26914647

Synthesis for Structure Rewriting Systems

NASA Astrophysics Data System (ADS)

Kaiser, Łukasz

The description of a single state of a modelled system is often complex in practice, but few procedures for synthesis address this problem in depth. We study systems in which a state is described by an arbitrary finite structure, and changes of the state are represented by structure rewriting rules, a generalisation of term and graph rewriting. Both the environment and the controller are allowed to change the structure in this way, and the question we ask is how a strategy for the controller that ensures a given property can be synthesised.

Aquatic Plant Control Research Program. Large-Scale Operations Management Test of Use of the White Amur for Control of Problem Aquatic Plants. The Herpetofauna of Lake Conway: Species Accounts.

DTIC Science & Technology

1983-07-01

complex suite of physiological and 39 respiratory adaptations (Ultch 1976) enable this species to occupy both open water and littoral zone environments...be an adaptation to avoid fish predation on juveniles in open water and may explain the spring peak in funnel trap captures near shore (Fig. 10). 79...population of C. picta probably is not established on Lake Conway. The one collected individual 103 defecated gastropod (Viviparous sp.) shells and

Can Genetics Predict Response to Complex Behavioral Interventions? Evidence from a Genetic Analysis of the Fast Track Randomized Control Trial

PubMed Central

Albert, Dustin; Belsky, Daniel W.; Crowley, D. Max; Latendresse, Shawn J.; Aliev, Fazil; Riley, Brien; Sun, Cuie; Dick, Danielle M.; Dodge, Kenneth R.

2014-01-01

Early interventions are a preferred method for addressing behavioral problems in high-risk children, but often have only modest effects. Identifying sources of variation in intervention effects can suggest means to improve efficiency. One potential source of such variation is the genome. We conducted a genetic analysis of the Fast Track Randomized Control Trial, a 10-year-long intervention to prevent high-risk kindergarteners from developing adult externalizing problems including substance abuse and antisocial behavior. We tested whether variants of the glucocorticoid receptor gene NR3C1 were associated with differences in response to the Fast Track intervention. We found that in European-American children, a variant of NR3C1 identified by the single-nucleotide polymorphism rs10482672 was associated with increased risk for externalizing psychopathology in control group children and decreased risk for externalizing psychopathology in intervention group children. Variation in NR3C1 measured in this study was not associated with differential intervention response in African-American children. We discuss implications for efforts to prevent externalizing problems in high-risk children and for public policy in the genomic era. PMID:26106668

Factors of Problem-Solving Competency in a Virtual Chemistry Environment: The Role of Metacognitive Knowledge about Strategies

ERIC Educational Resources Information Center

Scherer, Ronny; Tiemann, Rudiger

2012-01-01

The ability to solve complex scientific problems is regarded as one of the key competencies in science education. Until now, research on problem solving focused on the relationship between analytical and complex problem solving, but rarely took into account the structure of problem-solving processes and metacognitive aspects. This paper,…

Determining the Effects of Cognitive Style, Problem Complexity, and Hypothesis Generation on the Problem Solving Ability of School-Based Agricultural Education Students

ERIC Educational Resources Information Center

Blackburn, J. Joey; Robinson, J. Shane

2016-01-01

The purpose of this experimental study was to assess the effects of cognitive style, problem complexity, and hypothesis generation on the problem solving ability of school-based agricultural education students. Problem solving ability was defined as time to solution. Kirton's Adaption-Innovation Inventory was employed to assess students' cognitive…

Multichromosomal median and halving problems under different genomic distances

PubMed Central

Tannier, Eric; Zheng, Chunfang; Sankoff, David

2009-01-01

Background Genome median and genome halving are combinatorial optimization problems that aim at reconstructing ancestral genomes as well as the evolutionary events leading from the ancestor to extant species. Exploring complexity issues is a first step towards devising efficient algorithms. The complexity of the median problem for unichromosomal genomes (permutations) has been settled for both the breakpoint distance and the reversal distance. Although the multichromosomal case has often been assumed to be a simple generalization of the unichromosomal case, it is also a relaxation so that complexity in this context does not follow from existing results, and is open for all distances. Results We settle here the complexity of several genome median and halving problems, including a surprising polynomial result for the breakpoint median and guided halving problems in genomes with circular and linear chromosomes, showing that the multichromosomal problem is actually easier than the unichromosomal problem. Still other variants of these problems are NP-complete, including the DCJ double distance problem, previously mentioned as an open question. We list the remaining open problems. Conclusion This theoretical study clears up a wide swathe of the algorithmical study of genome rearrangements with multiple multichromosomal genomes. PMID:19386099

General algebraic method applied to control analysis of complex engine types

NASA Technical Reports Server (NTRS)

Boksenbom, Aaron S; Hood, Richard

1950-01-01

A general algebraic method of attack on the problem of controlling gas-turbine engines having any number of independent variables was utilized employing operational functions to describe the assumed linear characteristics for the engine, the control, and the other units in the system. Matrices were used to describe the various units of the system, to form a combined system showing all effects, and to form a single condensed matrix showing the principal effects. This method directly led to the conditions on the control system for noninteraction so that any setting disturbance would affect only its corresponding controlled variable. The response-action characteristics were expressed in terms of the control system and the engine characteristics. The ideal control-system characteristics were explicitly determined in terms of any desired response action.

A novel robust speed controller scheme for PMBLDC motor.

PubMed

Thirusakthimurugan, P; Dananjayan, P

2007-10-01

The design of speed and position controllers for permanent magnet brushless DC motor (PMBLDC) drive remains as an open problem in the field of motor drives. A precise speed control of PMBLDC motor is complex due to nonlinear coupling between winding currents and rotor speed. In addition, the nonlinearity present in the developed torque due to magnetic saturation of the rotor further complicates this issue. This paper presents a novel control scheme to the conventional PMBLDC motor drive, which aims at improving the robustness by complete decoupling of the design besides minimizing the mutual influence among the speed and current control loops. The interesting feature of this robust control scheme is its suitability for both static and dynamic aspects. The effectiveness of the proposed robust speed control scheme is verified through simulations.

Boundary control of bidomain equations with state-dependent switching source functions in the ionic model

NASA Astrophysics Data System (ADS)

Chamakuri, Nagaiah; Engwer, Christian; Kunisch, Karl

2014-09-01

Optimal control for cardiac electrophysiology based on the bidomain equations in conjunction with the Fenton-Karma ionic model is considered. This generic ventricular model approximates well the restitution properties and spiral wave behavior of more complex ionic models of cardiac action potentials. However, it is challenging due to the appearance of state-dependent discontinuities in the source terms. A computational framework for the numerical realization of optimal control problems is presented. Essential ingredients are a shape calculus based treatment of the sensitivities of the discontinuous source terms and a marching cubes algorithm to track iso-surface of excitation wavefronts. Numerical results exhibit successful defibrillation by applying an optimally controlled extracellular stimulus.

Artificial Intelligence Based Control Power Optimization on Tailless Aircraft. [ARMD Seedling Fund Phase I

NASA Technical Reports Server (NTRS)

Gern, Frank; Vicroy, Dan D.; Mulani, Sameer B.; Chhabra, Rupanshi; Kapania, Rakesh K.; Schetz, Joseph A.; Brown, Derrell; Princen, Norman H.

2014-01-01

Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

Adaptive Fault-Resistant Systems

DTIC Science & Technology

1994-10-01

An Architectural Overview of the Alpha Real-Time Distributed Kernel . In Proceeding., of the USEN[X Workshop on Microkernels and Other Kernel ...system and the controller are monolithic . We have noted earlier some of the problems of distributed systems-for exam- ple, the need to bound the...are monolithic . In practice, designers employ a layered structuring for their systems in order to manage complexity, and we expect that practical

SSC San Diego Biennial Review 2003. Command and Control

DTIC Science & Technology

2003-01-01

systems. IMAT systems use scientific visualizations, three- dimensional graphics, and animations to illustrate com- plex physical interactions in mission...Again, interactive animations are used to explain underlying concepts. For exam- ple, for principles of beamforming using a phased array, a three...solve complex problems. Experts type natural language text, use mouse clicks to provide hints for explanation generation, and use mouse clicks to

Stress in hospital medicine: a problem for key hospital staff.

PubMed

Allen, I

2001-08-01

Many factors which contribute to stress in the workplace apply to both consultants and ward sisters. Both groups find that their roles have become more complex while they have increasingly lost control of their own clinical and professional territory in a managerial culture. The erosion of the key relationship between consultants and ward sisters is of concern and the need for teamworking is insufficiently recognized.

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

Why the Lack of Academic Literature on Export Controls?

NASA Technical Reports Server (NTRS)

Kremic, Tibor

2001-01-01

Export controls is currently a relevant and dynamic topic. Given the growth of global operations and the high-tech nature of many products, an increase in awareness and understanding of the impacts of export controls are necessary. A structured approach to export controls has been in existence since 1949. Despite over 50 years of history, surprisingly little academic research and literature exists on the topic. This paper explores the current export control environment and explores possible reasons for the limited academic interest. Five possible reasons are discussed: (1) dynamic nature of the topic; (2) difficulty in ensuring accurate data; (3) Complexity of the problem; (4) relatively small economic impact; and (5) sensitive information. A research approach is recommended that considers these potential obstacles.

Human vs autonomous control of planetary roving vehicles

NASA Technical Reports Server (NTRS)

Whitney, W. M.

1974-01-01

Supervisory or semiautonomous control has some compelling advantages over step-by-step human command and verification for the operation of roving vehicles on remote planetary surfaces. There are also disadvantages in relation to the complex system that must be mobilized and the chain of events that must be enacted to conduct a mission. Which of the two control methods is better on technical grounds may not be the deciding factor in its acceptance or rejection. Some of the issues that affect changes in spacecraft design and operation are summarized. To accelerate the movement toward more autonomous machines, it will be necessary to understand and to address the problems that such autonomy will create for other elements of the control system and for the control process.

Automated control of hierarchical systems using value-driven methods

NASA Technical Reports Server (NTRS)

Pugh, George E.; Burke, Thomas E.

1990-01-01

An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.

Low speed hybrid generalized predictive control of a gasoline-propelled car.

PubMed

Romero, M; de Madrid, A P; Mañoso, C; Milanés, V

2015-07-01

Low-speed driving in traffic jams causes significant pollution and wasted time for commuters. Additionally, from the passengers׳ standpoint, this is an uncomfortable, stressful and tedious scene that is suitable to be automated. The highly nonlinear dynamics of car engines at low-speed turn its automation in a complex problem that still remains as unsolved. Considering the hybrid nature of the vehicle longitudinal control at low-speed, constantly switching between throttle and brake pedal actions, hybrid control is a good candidate to solve this problem. This work presents the analytical formulation of a hybrid predictive controller for automated low-speed driving. It takes advantage of valuable characteristics supplied by predictive control strategies both for compensating un-modeled dynamics and for keeping passengers security and comfort analytically by means of the treatment of constraints. The proposed controller was implemented in a gas-propelled vehicle to experimentally validate the adopted solution. To this end, different scenarios were analyzed varying road layouts and vehicle speeds within a private test track. The production vehicle is a commercial Citroën C3 Pluriel which has been modified to automatically act over its throttle and brake pedals. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Complexity of GPs' explanations about mental health problems: development, reliability, and validity of a measure

PubMed Central

Cape, John; Morris, Elena; Burd, Mary; Buszewicz, Marta

2008-01-01

Background How GPs understand mental health problems determines their treatment choices; however, measures describing GPs' thinking about such problems are not currently available. Aim To develop a measure of the complexity of GP explanations of common mental health problems and to pilot its reliability and validity. Design of study A qualitative development of the measure, followed by inter-rater reliability and validation pilot studies. Setting General practices in North London. Method Vignettes of simulated consultations with patients with mental health problems were videotaped, and an anchored measure of complexity of psychosocial explanation in response to these vignettes was developed. Six GPs, four psychologists, and two lay people viewed the vignettes. Their responses were rated for complexity, both using the anchored measure and independently by two experts in primary care mental health. In a second reliability and revalidation study, responses of 50 GPs to two vignettes were rated for complexity. The GPs also completed a questionnaire to determine their interest and training in mental health, and they completed the Depression Attitudes Questionnaire. Results Inter-rater reliability of the measure of complexity of explanation in both pilot studies was satisfactory (intraclass correlation coefficient = 0.78 and 0.72). The measure correlated with expert opinion as to what constitutes a complex explanation, and the responses of psychologists, GPs, and lay people differed in measured complexity. GPs with higher complexity scores had greater interest, more training in mental health, and more positive attitudes to depression. Conclusion Results suggest that the complexity of GPs' psychosocial explanations about common mental health problems can be reliably and validly assessed by this new standardised measure. PMID:18505616

Clinical Problem Analysis (CPA): A Systematic Approach To Teaching Complex Medical Problem Solving.

ERIC Educational Resources Information Center

Custers, Eugene J. F. M.; Robbe, Peter F. De Vries; Stuyt, Paul M. J.

2000-01-01

Discusses clinical problem analysis (CPA) in medical education, an approach to solving complex clinical problems. Outlines the five step CPA model and examines the value of CPA's content-independent (methodical) approach. Argues that teaching students to use CPA will enable them to avoid common diagnostic reasoning errors and pitfalls. Compares…

Adding control to arbitrary unknown quantum operations

PubMed Central

Zhou, Xiao-Qi; Ralph, Timothy C.; Kalasuwan, Pruet; Zhang, Mian; Peruzzo, Alberto; Lanyon, Benjamin P.; O'Brien, Jeremy L.

2011-01-01

Although quantum computers promise significant advantages, the complexity of quantum algorithms remains a major technological obstacle. We have developed and demonstrated an architecture-independent technique that simplifies adding control qubits to arbitrary quantum operations—a requirement in many quantum algorithms, simulations and metrology. The technique, which is independent of how the operation is done, does not require knowledge of what the operation is, and largely separates the problems of how to implement a quantum operation in the laboratory and how to add a control. Here, we demonstrate an entanglement-based version in a photonic system, realizing a range of different two-qubit gates with high fidelity. PMID:21811242

Reliability-Based Control Design for Uncertain Systems

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.

2005-01-01

This paper presents a robust control design methodology for systems with probabilistic parametric uncertainty. Control design is carried out by solving a reliability-based multi-objective optimization problem where the probability of violating design requirements is minimized. Simultaneously, failure domains are optimally enlarged to enable global improvements in the closed-loop performance. To enable an efficient numerical implementation, a hybrid approach for estimating reliability metrics is developed. This approach, which integrates deterministic sampling and asymptotic approximations, greatly reduces the numerical burden associated with complex probabilistic computations without compromising the accuracy of the results. Examples using output-feedback and full-state feedback with state estimation are used to demonstrate the ideas proposed.