WorldWideScience

Sample records for generalized predictive control

  1. Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems

    Science.gov (United States)

    Kelkar, Atul G.

    2000-01-01

    The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.

  2. General predictive control using the delta operator

    DEFF Research Database (Denmark)

    Jensen, Morten Rostgaard; Poulsen, Niels Kjølstad; Ravn, Ole

    1993-01-01

    This paper deals with two-discrete-time operators, the conventional forward shift-operator and the δ-operator. Both operators are treated in view of construction of suitable solutions to the Diophantine equation for the purpose of prediction. A general step-recursive scheme is presented. Finally...... a general predictive control (GPC) is formulated and applied adaptively to a continuous-time plant...

  3. Adaptive Generalized Predictive Control for Mechatronic Systems

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Böhm, Josef

    2006-01-01

    Roč. 5, č. 8 (2006), s. 1830-1837 ISSN 1109-2777 R&D Projects: GA ČR GP102/06/P275; GA ČR GA102/05/0271 Institutional research plan: CEZ:AV0Z10750506 Keywords : on-line identification * predictive control * input/output equations of predictions * real-time control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0040149.pdf

  4. Real-time Adaptive Control Using Neural Generalized Predictive Control

    Science.gov (United States)

    Haley, Pam; Soloway, Don; Gold, Brian

    1999-01-01

    The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

  5. Generalized ESO and Predictive Control Based Robust Autopilot Design

    Directory of Open Access Journals (Sweden)

    Bhavnesh Panchal

    2016-01-01

    Full Text Available A novel continuous time predictive control and generalized extended state observer (GESO based acceleration tracking pitch autopilot design is proposed for a tail controlled, skid-to-turn tactical missile. As the dynamics of missile are significantly uncertain with mismatched uncertainty, GESO is employed to estimate the state and uncertainty in an integrated manner. The estimates are used to meet the requirement of state and to robustify the output tracking predictive controller designed for nominal system. Closed loop stability for the controller-observer structure is established. An important feature of the proposed design is that it does not require any specific information about the uncertainty. Also the predictive control design yields the feedback control gain and disturbance compensation gain simultaneously. Effectiveness of GESO in estimation of the states and uncertainties and in robustifying the predictive controller in the presence of parametric uncertainties, external disturbances, unmodeled dynamics, and measurement noise is illustrated by simulation.

  6. Neural Generalized Predictive Control of a non-linear Process

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1998-01-01

    qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial......The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem....

  7. Pilots Rate Augmented Generalized Predictive Control for Reconfiguration

    Science.gov (United States)

    Soloway, Don; Haley, Pam

    2004-01-01

    The objective of this paper is to report the results from the research being conducted in reconfigurable fight controls at NASA Ames. A study was conducted with three NASA Dryden test pilots to evaluate two approaches of reconfiguring an aircraft's control system when failures occur in the control surfaces and engine. NASA Ames is investigating both a Neural Generalized Predictive Control scheme and a Neural Network based Dynamic Inverse controller. This paper highlights the Predictive Control scheme where a simple augmentation to reduce zero steady-state error led to the neural network predictor model becoming redundant for the task. Instead of using a neural network predictor model, a nominal single point linear model was used and then augmented with an error corrector. This paper shows that the Generalized Predictive Controller and the Dynamic Inverse Neural Network controller perform equally well at reconfiguration, but with less rate requirements from the actuators. Also presented are the pilot ratings for each controller for various failure scenarios and two samples of the required control actuation during reconfiguration. Finally, the paper concludes by stepping through the Generalized Predictive Control's reconfiguration process for an elevator failure.

  8. Generalized Predictive Control for Non-Stationary Systems

    DEFF Research Database (Denmark)

    Palsson, Olafur Petur; Madsen, Henrik; Søgaard, Henning Tangen

    1994-01-01

    This paper shows how the generalized predictive control (GPC) can be extended to non-stationary (time-varying) systems. If the time-variation is slow, then the classical GPC can be used in context with an adaptive estimation procedure of a time-invariant ARIMAX model. However, in this paper prior...... knowledge concerning the nature of the parameter variations is assumed available. The GPC is based on the assumption that the prediction of the system output can be expressed as a linear combination of present and future controls. Since the Diophantine equation cannot be used due to the time......-variation of the parameters, the optimal prediction is found as the general conditional expectation of the system output. The underlying model is of an ARMAX-type instead of an ARIMAX-type as in the original version of the GPC (Clarke, D. W., C. Mohtadi and P. S. Tuffs (1987). Automatica, 23, 137-148) and almost all later...

  9. Effective and Robust Generalized Predictive Speed Control of Induction Motor

    Directory of Open Access Journals (Sweden)

    Patxi Alkorta

    2013-01-01

    Full Text Available This paper presents and validates a new proposal for effective speed vector control of induction motors based on linear Generalized Predictive Control (GPC law. The presented GPC-PI cascade configuration simplifies the design with regard to GPC-GPC cascade configuration, maintaining the advantages of the predictive control algorithm. The robust stability of the closed loop system is demonstrated by the poles placement method for several typical cases of uncertainties in induction motors. The controller has been tested using several simulations and experiments and has been compared with Proportional Integral Derivative (PID and Sliding Mode (SM control schemes, obtaining outstanding results in speed tracking even in the presence of parameter uncertainties, unknown load disturbance, and measurement noise in the loop signals, suggesting its use in industrial applications.

  10. Stability analysis of embedded nonlinear predictor neural generalized predictive controller

    Directory of Open Access Journals (Sweden)

    Hesham F. Abdel Ghaffar

    2014-03-01

    Full Text Available Nonlinear Predictor-Neural Generalized Predictive Controller (NGPC is one of the most advanced control techniques that are used with severe nonlinear processes. In this paper, a hybrid solution from NGPC and Internal Model Principle (IMP is implemented to stabilize nonlinear, non-minimum phase, variable dead time processes under high disturbance values over wide range of operation. Also, the superiority of NGPC over linear predictive controllers, like GPC, is proved for severe nonlinear processes over wide range of operation. The necessary conditions required to stabilize NGPC is derived using Lyapunov stability analysis for nonlinear processes. The NGPC stability conditions and improvement in disturbance suppression are verified by both simulation using Duffing’s nonlinear equation and real-time using continuous stirred tank reactor. Up to our knowledge, the paper offers the first hardware embedded Neural GPC which has been utilized to verify NGPC–IMP improvement in realtime.

  11. Generalized predictive control in the delta-domain

    DEFF Research Database (Denmark)

    Lauritsen, Morten Bach; Jensen, Morten Rostgaard; Poulsen, Niels Kjølstad

    1995-01-01

    This paper describes new approaches to generalized predictive control formulated in the delta (δ) domain. A new δ-domain version of the continuous-time emulator-based predictor is presented. It produces the optimal estimate in the deterministic case whenever the predictor order is chosen greater...... than or equal to the number of future predicted samples, however a “good” estimate is usually obtained in a much longer range of samples. This is particularly advantageous at fast sampling rates where a “conventional” predictor is bound to become very computationally demanding. Two controllers...... are considered: one having a well-defined limit as the sampling period tends to zero, the other being a close approximation to the conventional discrete-time GPC. Both algorithms are discrete in nature and well-suited for adaptive control. The fact, that δ-domain model are used does not introduce...

  12. Experimental Investigations of Generalized Predictive Control for Tiltrotor Stability Augmentation

    Science.gov (United States)

    Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Piatak, David J.; Kvaternik, Raymond G.; Bennett, Richard L.; Brown, Ross K.

    2001-01-01

    A team of researchers from the Army Research Laboratory, NASA Langley Research Center (LaRC), and Bell Helicopter-Textron, Inc. have completed hover-cell and wind-tunnel testing of a 1/5-size aeroelastically-scaled tiltrotor model using a new active control system for stability augmentation. The active system is based on a generalized predictive control (GPC) algorithm originally developed at NASA LaRC in 1997 for un-known disturbance rejection. Results of these investigations show that GPC combined with an active swashplate can significantly augment the damping and stability of tiltrotors in both hover and high-speed flight.

  13. Self-Tuning of Design Variables for Generalized Predictive Control

    Science.gov (United States)

    Lin, Chaung; Juang, Jer-Nan

    2000-01-01

    Three techniques are introduced to determine the order and control weighting for the design of a generalized predictive controller. These techniques are based on the application of fuzzy logic, genetic algorithms, and simulated annealing to conduct an optimal search on specific performance indexes or objective functions. Fuzzy logic is found to be feasible for real-time and on-line implementation due to its smooth and quick convergence. On the other hand, genetic algorithms and simulated annealing are applicable for initial estimation of the model order and control weighting, and final fine-tuning within a small region of the solution space, Several numerical simulations for a multiple-input and multiple-output system are given to illustrate the techniques developed in this paper.

  14. Comparison of H-infinity control and generalized predictive control for a laser scanner system

    DEFF Research Database (Denmark)

    Ordys, A.W.; Stoustrup, Jakob; Smillie, I.

    2000-01-01

    This paper describes tests performed on a laser scanner system to assess the feasibility of H-infinity control and generalized predictive control design techniques in achieving a required performance in a trajectory folowing problem. The two methods are compared with respect to achieved scan time...

  15. Exploratory Studies in Generalized Predictive Control for Active Aeroelastic Control of Tiltrotor Aircraft

    Science.gov (United States)

    Kvaternik, Raymond G.; Juang, Jer-Nan; Bennett, Richard L.

    2000-01-01

    The Aeroelasticity Branch at NASA Langley Research Center has a long and substantive history of tiltrotor aeroelastic research. That research has included a broad range of experimental investigations in the Langley Transonic Dynamics Tunnel (TDT) using a variety of scale models and the development of essential analyses. Since 1994, the tiltrotor research program has been using a 1/5-scale, semispan aeroelastic model of the V-22 designed and built by Bell Helicopter Textron Inc. (BHTI) in 1981. That model has been refurbished to form a tiltrotor research testbed called the Wing and Rotor Aeroelastic Test System (WRATS) for use in the TDT. In collaboration with BHTI, studies under the current tiltrotor research program are focused on aeroelastic technology areas having the potential for enhancing the commercial and military viability of tiltrotor aircraft. Among the areas being addressed, considerable emphasis is being directed to the evaluation of modern adaptive multi-input multi- output (MIMO) control techniques for active stability augmentation and vibration control of tiltrotor aircraft. As part of this investigation, a predictive control technique known as Generalized Predictive Control (GPC) is being studied to assess its potential for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in both helicopter and airplane modes of flight. This paper summarizes the exploratory numerical and experimental studies that were conducted as part of that investigation.

  16. Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer.

    Science.gov (United States)

    Ouari, Kamel; Rekioua, Toufik; Ouhrouche, Mohand

    2014-01-01

    In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Fractional-Order Generalized Predictive Control: Application for Low-Speed Control of Gasoline-Propelled Cars

    Directory of Open Access Journals (Sweden)

    M. Romero

    2013-01-01

    Full Text Available There is an increasing interest in using fractional calculus applied to control theory generalizing classical control strategies as the PID controller and developing new ones with the intention of taking advantage of characteristics supplied by this mathematical tool for the controller definition. In this work, the fractional generalization of the successful and spread control strategy known as model predictive control is applied to drive autonomously a gasoline-propelled vehicle at low speeds. The vehicle is a Citroën C3 Pluriel that was modified to act over the throttle and brake pedals. Its highly nonlinear dynamics are an excellent test bed for applying beneficial characteristics of fractional predictive formulation to compensate unmodeled dynamics and external disturbances.

  18. Efficient Multivariable Generalized Predictive Control for Autonomous Underwater Vehicle in Vertical Plane

    Directory of Open Access Journals (Sweden)

    Xuliang Yao

    2016-01-01

    Full Text Available This paper presents the design and simulation validation of a multivariable GPC (generalized predictive control for AUV (autonomous underwater vehicle in vertical plane. This control approach has been designed in the case of AUV navigating with low speed near water surface, in order to restrain wave disturbance effectively and improve pitch and heave motion stability. The proposed controller guarantees compliance with rudder manipulation, AUV output constraints, and driving energy consumption. Performance index based on pitch stabilizing performance, energy consumption, and system constraints is used to derive the control action applied for each time step. In order to deal with constrained optimization problems, a Hildreth’s QP procedure is adopted. Simulation results of AUV longitudinal control show better stabilizing performance and minimized energy consumption improved by multivariable GPC.

  19. Design of a generalized predictive controller for a biological wastewater treatment plant.

    Science.gov (United States)

    Sadeghassadi, M; Macnab, C J B; Westwick, D

    2016-01-01

    This paper presents a generalized predictive control (GPC) technique to regulate the activated sludge process found in a bioreactor used in wastewater treatment. The control strategy can track dissolved oxygen setpoint changes quickly, adapting to the system uncertainties and disturbances. Tests occur on an Activated Sludge Model No. 1 benchmark of an activated sludge process. A T filter added to the GPC framework results in an effective control strategy in the presence of coloured measurement noise. This work also suggests how a constraint on the measured variable can be added as a penalty term to the GPC framework which leads to improved control of the dissolved oxygen concentration in the presence of dynamic input disturbance.

  20. A swarm intelligence-based tuning method for the Sliding Mode Generalized Predictive Control.

    Science.gov (United States)

    Oliveira, J B; Boaventura-Cunha, J; Moura Oliveira, P B; Freire, H

    2014-09-01

    This work presents an automatic tuning method for the discontinuous component of the Sliding Mode Generalized Predictive Controller (SMGPC) subject to constraints. The strategy employs Particle Swarm Optimization (PSO) to minimize a second aggregated cost function. The continuous component is obtained by the standard procedure, by Quadratic Programming (QP), thus yielding an online dual optimization scheme. Simulations and performance indexes for common process models in industry, such as nonminimum phase and time delayed systems, result in a better performance, improving robustness and tracking accuracy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Generalized Predictive Control of Dynamic Systems with Rigid-Body Modes

    Science.gov (United States)

    Kvaternik, Raymond G.

    2013-01-01

    Numerical simulations to assess the effectiveness of Generalized Predictive Control (GPC) for active control of dynamic systems having rigid-body modes are presented. GPC is a linear, time-invariant, multi-input/multi-output predictive control method that uses an ARX model to characterize the system and to design the controller. Although the method can accommodate both embedded (implicit) and explicit feedforward paths for incorporation of disturbance effects, only the case of embedded feedforward in which the disturbances are assumed to be unknown is considered here. Results from numerical simulations using mathematical models of both a free-free three-degree-of-freedom mass-spring-dashpot system and the XV-15 tiltrotor research aircraft are presented. In regulation mode operation, which calls for zero system response in the presence of disturbances, the simulations showed reductions of nearly 100%. In tracking mode operations, where the system is commanded to follow a specified path, the GPC controllers produced the desired responses, even in the presence of disturbances.

  2. Explicit Generalized Predictive Control of Speed and Position of PMSM Drives

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Vošmik, D.

    2016-01-01

    Roč. 63, č. 6 (2016), s. 3889-3896 ISSN 0278-0046 Institutional support: RVO:67985556 Keywords : current limitation * field weakening * motion control * permanent magnet synchronous motors * position control * predictive control * speed control Subject RIV: BC - Control Systems Theory Impact factor: 7.168, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/belda-0457259.pdf

  3. Low speed hybrid generalized predictive control of a gasoline-propelled car.

    Science.gov (United States)

    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.

  4. An Experimental Evaluation of Generalized Predictive Control for Tiltrotor Aeroelastic Stability Augmentation in Airplane Mode of Flight

    Science.gov (United States)

    Kvaternik, Raymond G.; Piatak, David J.; Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Bennett, Richard L.; Brown, Ross K.

    2001-01-01

    The results of a joint NASA/Army/Bell Helicopter Textron wind-tunnel test to assess the potential of Generalized Predictive Control (GPC) for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in the airplane mode of flight are presented. GPC is an adaptive time-domain predictive control method that uses a linear difference equation to describe the input-output relationship of the system and to design the controller. The test was conducted in the Langley Transonic Dynamics Tunnel using an unpowered 1/5-scale semispan aeroelastic model of the V-22 that was modified to incorporate a GPC-based multi-input multi-output control algorithm to individually control each of the three swashplate actuators. Wing responses were used for feedback. The GPC-based control system was highly effective in increasing the stability of the critical wing mode for all of the conditions tested, without measurable degradation of the damping in the other modes. The algorithm was also robust with respect to its performance in adjusting to rapid changes in both the rotor speed and the tunnel airspeed.

  5. Neural response during attentional control and emotion processing predicts improvement after cognitive behavioral therapy in generalized social anxiety disorder.

    Science.gov (United States)

    Klumpp, H; Fitzgerald, D A; Angstadt, M; Post, D; Phan, K L

    2014-10-01

    Individuals with generalized social anxiety disorder (gSAD) exhibit attentional bias to salient stimuli, which is reduced in patients whose symptoms improve after treatment, indicating that mechanisms of bias mediate treatment success. Therefore, pre-treatment activity in regions implicated in attentional control over socio-emotional signals (e.g. anterior cingulate cortex, dorsolateral prefrontal cortex) may predict response to cognitive behavioral therapy (CBT), evidence-based psychotherapy for gSAD. During functional magnetic resonance imaging, 21 participants with gSAD viewed images comprising a trio of geometric shapes (circles, rectangles or triangles) alongside a trio of faces (angry, fearful or happy) within the same field of view. Attentional control was evaluated with the instruction to 'match shapes', directing attention away from faces, which was contrasted with 'match faces', whereby attention was directed to emotional faces. Whole-brain voxel-wise analyses showed that symptom improvement was predicted by enhanced pre-treatment activity in the presence of emotional face distractors in the dorsal anterior cingulate cortex and dorsal medial prefrontal cortex. Additionally, CBT success was foretold by less activity in the amygdala and/or increased activity in the medial orbitofrontal gyrus during emotion processing. CBT response was predicted by pre-treatment activity in prefrontal regions and the amygdala. The direction of activity suggests that individuals with intact attentional control in the presence of emotional distractors, regulatory capacity over emotional faces and/or less reactivity to such faces are more likely to benefit from CBT. Findings indicate that baseline neural activity in the context of attentional control and emotion processing may serve as a step towards delineating mechanisms by which CBT exerts its effects.

  6. Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2015-03-01

    Full Text Available In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G technique, electric vehicles (EVs can act as mobile energy storage units, which could be a solution for load frequency control (LFC in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances.

  7. On identified predictive control

    Science.gov (United States)

    Bialasiewicz, Jan T.

    1993-01-01

    Self-tuning control algorithms are potential successors to manually tuned PID controllers traditionally used in process control applications. A very attractive design method for self-tuning controllers, which has been developed over recent years, is the long-range predictive control (LRPC). The success of LRPC is due to its effectiveness with plants of unknown order and dead-time which may be simultaneously nonminimum phase and unstable or have multiple lightly damped poles (as in the case of flexible structures or flexible robot arms). LRPC is a receding horizon strategy and can be, in general terms, summarized as follows. Using assumed long-range (or multi-step) cost function the optimal control law is found in terms of unknown parameters of the predictor model of the process, current input-output sequence, and future reference signal sequence. The common approach is to assume that the input-output process model is known or separately identified and then to find the parameters of the predictor model. Once these are known, the optimal control law determines control signal at the current time t which is applied at the process input and the whole procedure is repeated at the next time instant. Most of the recent research in this field is apparently centered around the LRPC formulation developed by Clarke et al., known as generalized predictive control (GPC). GPC uses ARIMAX/CARIMA model of the process in its input-output formulation. In this paper, the GPC formulation is used but the process predictor model is derived from the state space formulation of the ARIMAX model and is directly identified over the receding horizon, i.e., using current input-output sequence. The underlying technique in the design of identified predictive control (IPC) algorithm is the identification algorithm of observer/Kalman filter Markov parameters developed by Juang et al. at NASA Langley Research Center and successfully applied to identification of flexible structures.

  8. Applied predictive control

    CERN Document Server

    Sunan, Huang; Heng, Lee Tong

    2002-01-01

    The presence of considerable time delays in the dynamics of many industrial processes, leading to difficult problems in the associated closed-loop control systems, is a well-recognized phenomenon. The performance achievable in conventional feedback control systems can be significantly degraded if an industrial process has a relatively large time delay compared with the dominant time constant. Under these circumstances, advanced predictive control is necessary to improve the performance of the control system significantly. The book is a focused treatment of the subject matter, including the fundamentals and some state-of-the-art developments in the field of predictive control. Three main schemes for advanced predictive control are addressed in this book: • Smith Predictive Control; • Generalised Predictive Control; • a form of predictive control based on Finite Spectrum Assignment. A substantial part of the book addresses application issues in predictive control, providing several interesting case studie...

  9. State-space predictive control

    Directory of Open Access Journals (Sweden)

    Jens G. Balchen

    1992-04-01

    Full Text Available This paper deals with a predictive control strategy based on state-space models. Important issues concerning inherent model identification and optimal control computation are briefly discussed. Predictive control relies heavily on a model with satisfactory predictive capabilities. An off-line identification procedure must be accomplished to obtain a proper model structure and a parameter set, which is required for on-line adjustment. The control calculation is based on a general performance index and parameterization of the control variables in a nonlinear model, which includes the relevant constraints. This results in a finite-dimensional optimization problem which can be repetitively solved on-line. Simulation studies on two very different, typical industrial processes are presented. The simulations show that this MPC technique offers a major improvement in the control of many industrial processes.

  10. Data-Based Predictive Control with Multirate Prediction Step

    Science.gov (United States)

    Barlow, Jonathan S.

    2010-01-01

    Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

  11. Differential Prediction Generalization in College Admissions Testing

    Science.gov (United States)

    Aguinis, Herman; Culpepper, Steven A.; Pierce, Charles A.

    2016-01-01

    We introduce the concept of "differential prediction generalization" in the context of college admissions testing. Specifically, we assess the extent to which predicted first-year college grade point average (GPA) based on high-school grade point average (HSGPA) and SAT scores depends on a student's ethnicity and gender and whether this…

  12. Intelligent Predictive Control of Nonlienar Processes Using

    DEFF Research Database (Denmark)

    Nørgård, Peter Magnus; Sørensen, Paul Haase; Poulsen, Niels Kjølstad

    1996-01-01

    This paper presents a novel approach to design of generalized predictive controllers (GPC) for nonlinear processes. A neural network is used for modelling the process and a gain-scheduling type of GPC is subsequently designed. The combination of neural network models and predictive control has...

  13. Tapping generalized essentialism to predict outgroup prejudices.

    Science.gov (United States)

    Hodson, Gordon; Skorska, Malvina N

    2015-06-01

    Psychological essentialism, the perception that groups possess inherent properties binding them and differentiating them from others, is theoretically relevant to predicting prejudice. Recent developments isolate two key dimensions: essentialistic entitativity (EE; groups as unitary, whole, entity-like) and essentialistic naturalness (EN; groups as fixed and immutable). We introduce a novel question: does tapping the covariance between EE and EN, rather than pitting them against each other, boost prejudice prediction? In Study 1 (re-analysis of Roets & Van Hiel, 2011b, Samples 1-3, in Belgium) and Study 2 (new Canadian data) their common/shared variance, modelled as generalized essentialism, doubles the predictive power relative to regression-based approaches with regard to racism (but not anti-gay or -schizophrenic prejudices). Theoretical implications are discussed. © 2014 The British Psychological Society.

  14. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C

    2009-01-01

    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  15. Link prediction via generalized coupled tensor factorisation

    DEFF Research Database (Denmark)

    Ermiş, Beyza; Evrim, Acar Ataman; Taylan Cemgil, A.

    2012-01-01

    and higher-order tensors. We propose to use an approach based on probabilistic interpretation of tensor factorisation models, i.e., Generalised Coupled Tensor Factorisation, which can simultaneously fit a large class of tensor models to higher-order tensors/matrices with com- mon latent factors using...... different loss functions. Numerical experiments demonstrate that joint analysis of data from multiple sources via coupled factorisation improves the link prediction performance and the selection of right loss function and tensor model is crucial for accurately predicting missing links....

  16. Generalized synchronization via impulsive control

    International Nuclear Information System (INIS)

    Zhang Rong; Xu Zhenyuan; Yang, Simon X.; He Xueming

    2008-01-01

    This paper demonstrates theoretically that two completely different systems can implement GS via impulsive control, moreover by using impulsive control, for a given manifold y = H(x) we construct a response system to achieve GS with drive system and the synchronization manifold is y = H(x). Our theoretical results are supported by numerical examples

  17. Reduced order modelling and predictive control of multivariable ...

    Indian Academy of Sciences (India)

    Anuj Abraham

    2018-03-16

    Mar 16, 2018 ... The performance of constraint generalized predictive control scheme is found to be superior to that of the conventional PID controller in terms of overshoot, settling time and performance indices, mainly ISE, IAE and MSE. Keywords. Predictive control; distillation column; reduced order model; dominant pole; ...

  18. Predicting metal toxicity revisited: general properties vs. specific effects.

    Science.gov (United States)

    Wolterbeek, H T; Verburg, T G

    2001-11-12

    The present paper addresses the prediction of metal toxicity by evaluation of the relationships between general metal properties and toxic effects. For this, metal toxicity data were taken from 30 literature data sets, which varied largely in exposure times, organisms, effects and effect levels. General metal properties were selected on basis of literature reviewing of basic metal property classifications: used were the electrochemical potential deltaE0; the ionization potential IP; the ratio between atomic radius and atomic weight AR/AW; and the electronegativity Xm. The results suggest that toxicity prediction may be performed on basis of these fixed metal properties without any adoption to specific organisms, without any division of metals into classes, or grouping of toxicity tests. The results further indicate that metal properties contribute to the observed effects in relative importances which depend on specific effects, effect levels, exposure times, selected organisms and ambient conditions. The discussion strongly suggests that prediction should be by interpolation rather than by extrapolation of calibrated toxicity data: the concept here is that unknown metal toxicities are predicted on basis of observed metal toxicities in calibration experiments. Considering the used metal properties, the calibration covers the largest number of metals by the simultanuous use of Ge(IV), Cs(I), Li(I), Mn(VII), Sc and Bi in toxicity studies. Based on the data from the 30 studies considered, metal toxicities could be ordered in a relative way. This ordering indicates that the natural abundance of metals or metal ions in the Earth's crust may be regarded as a general comparative measure of the metal toxicities. The problems encountered in toxicity interpretation and ordering of toxicities indicate that control of the solution acidity, the metal's solubility and the metal's oxidation state may be key problems to overcome in future metal ion toxicity studies.

  19. Predicting student success in General Chemistry

    Science.gov (United States)

    Figueroa, Daphne Elizabeth

    The goal of this research was to determine the predictors of student success in college level General Chemistry. The potential predictors were categorized as cognitive, non-cognitive, affective, or demographic factors. A broader goal of the study was to provide a reference for academic personnel to better judge the prerequisite skills, knowledge and attitudes that students should attain before enrolling in General Chemistry. Therefore, the study is relevant to chemical educators who are attempting to matriculate candidates for the scientific workforce and to chemical education researches who are interested in student success, student retention and curricular reform. The major hypotheses were that several factors from each category would emerge as significant predictors and that these would differ for students enrolled at three different post-secondary institutions: a community college, a private university and a public university. These hypotheses were tested using multiple regression techniques to analyze grade, student survey and post-test data collected from General Chemistry students at the three institutions. Over-all, twelve factors (six demographic, three cognitive and three affective) emerged as strong, significant predictors of student success. In addition, there were marked differences in which factors emerged based on the type of institution and on how student success was defined. Thus, the major hypotheses of the study were supported. Over-all, this study has significant implications for educational policy, theory, and practice. With regard to policy, there is a need for institutions and departments that offer General Chemistry to provide support for a diverse population of students. And, at the community college level, in particular, there is a need for better academic advising and more institutional support for underprepared students. In the classroom, the professor plays a critical role in influencing students' academic self-concept, which in turn

  20. Implementation of neural network based non-linear predictive control

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1999-01-01

    This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...

  1. Model Predictive Controller Combined with LQG Controller and Velocity Feedback to Control the Stewart Platform

    DEFF Research Database (Denmark)

    Nadimi, Esmaeil Sharak; Bak, Thomas; Izadi-Zamanabadi, Roozbeh

    2006-01-01

    The main objective of this paper is to investigate the erformance and applicability of two GPC (generalized predictive control) based control methods on a complete benchmark model of the Stewart platform made in MATLAB V6.5. The first method involves an LQG controller (Linear Quadratic Gaussian...

  2. Model complexity control for hydrologic prediction

    Science.gov (United States)

    Schoups, G.; van de Giesen, N. C.; Savenije, H. H. G.

    2008-12-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore needed. We compare three model complexity control methods for hydrologic prediction, namely, cross validation (CV), Akaike's information criterion (AIC), and structural risk minimization (SRM). Results show that simulation of water flow using non-physically-based models (polynomials in this case) leads to increasingly better calibration fits as the model complexity (polynomial order) increases. However, prediction uncertainty worsens for complex non-physically-based models because of overfitting of noisy data. Incorporation of physically based constraints into the model (e.g., storage-discharge relationship) effectively bounds prediction uncertainty, even as the number of parameters increases. The conclusion is that overparameterization and equifinality do not lead to a continued increase in prediction uncertainty, as long as models are constrained by such physical principles. Complexity control of hydrologic models reduces parameter equifinality and identifies the simplest model that adequately explains the data, thereby providing a means of hydrologic generalization and classification. SRM is a promising technique for this purpose, as it (1) provides analytic upper bounds on prediction uncertainty, hence avoiding the computational burden of CV, and (2) extends the applicability of classic methods such as AIC to finite data. The main hurdle in applying SRM is the need for an a priori estimation of the complexity of the hydrologic model, as measured by its Vapnik-Chernovenkis (VC) dimension. Further research is needed in this area.

  3. Predictive performance of a genetic risk score using 11 susceptibility alleles for the incidence of Type 2 diabetes in a general Japanese population: a nested case-control study.

    Science.gov (United States)

    Goto, A; Noda, M; Goto, M; Yasuda, K; Mizoue, T; Yamaji, T; Sawada, N; Iwasaki, M; Inoue, M; Tsugane, S

    2018-02-14

    To assess the predictive ability of a genetic risk score for the incidence of Type 2 diabetes in a general Japanese population. This prospective case-control study, nested within a Japan Public Health Centre-based prospective study, included 466 participants with incident Type 2 diabetes over a 5-year period (cases) and 1361 control participants, as well as 1463 participants with existing diabetes and 1463 control participants. Eleven susceptibility single nucleotide polymorphisms, identified through genome-wide association studies and replicated in Japanese populations, were analysed. Most single nucleotide polymorphism loci showed directionally consistent associations with diabetes. From the combined samples, one single nucleotide polymorphism (rs2206734 at CDKAL1) reached a genome-wide significance level (odds ratio 1.28, 95% CI 1.18-1.40; P = 1.8 × 10 -8 ). Three single nucleotide polymorphisms (rs2206734 in CDKAL1, rs2383208 in CDKN2A/B, and rs2237892 in KCNQ1) were nominally associated with incident diabetes. Compared with the lowest quintile of the total number of risk alleles, the highest quintile had a higher odds of incident diabetes (odds ratio 2.34, 95% CI 1.59-3.46) after adjusting for conventional risk factors such as age, sex and BMI. The addition to the conventional risk factor-based model of a genetic risk score using the 11 single nucleotide polymorphisms significantly improved predictive performance; the c-statistic increased by 0.021, net reclassification improved by 6.2%, and integrated discrimination improved by 0.003. Our prospective findings suggest that the addition of a genetic risk score may provide modest but significant incremental predictive performance beyond that of the conventional risk factor-based model without biochemical markers. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  4. Seasonal predictability of Kiremt rainfall in coupled general circulation models

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

    2017-11-01

    The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

  5. General Theory versus ENA Theory: Comparing Their Predictive Accuracy and Scope.

    Science.gov (United States)

    Ellis, Lee; Hoskin, Anthony; Hartley, Richard; Walsh, Anthony; Widmayer, Alan; Ratnasingam, Malini

    2015-12-01

    General theory attributes criminal behavior primarily to low self-control, whereas evolutionary neuroandrogenic (ENA) theory envisions criminality as being a crude form of status-striving promoted by high brain exposure to androgens. General theory predicts that self-control will be negatively correlated with risk-taking, while ENA theory implies that these two variables should actually be positively correlated. According to ENA theory, traits such as pain tolerance and muscularity will be positively associated with risk-taking and criminality while general theory makes no predictions concerning these relationships. Data from Malaysia and the United States are used to test 10 hypotheses derived from one or both of these theories. As predicted by both theories, risk-taking was positively correlated with criminality in both countries. However, contrary to general theory and consistent with ENA theory, the correlation between self-control and risk-taking was positive in both countries. General theory's prediction of an inverse correlation between low self-control and criminality was largely supported by the U.S. data but only weakly supported by the Malaysian data. ENA theory's predictions of positive correlations between pain tolerance, muscularity, and offending were largely confirmed. For the 10 hypotheses tested, ENA theory surpassed general theory in predictive scope and accuracy. © The Author(s) 2014.

  6. Model Predictive Control Fundamentals | Orukpe | Nigerian Journal ...

    African Journals Online (AJOL)

    Model Predictive Control (MPC) has developed considerably over the last two decades, both within the research control community and in industries. MPC strategy involves the optimization of a performance index with respect to some future control sequence, using predictions of the output signal based on a process model, ...

  7. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optim...

  8. Towards a generalized energy prediction model for machine tools.

    Science.gov (United States)

    Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H; Dornfeld, David A; Helu, Moneer; Rachuri, Sudarsan

    2017-04-01

    Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process.

  9. State-space Generalized Predicitve Control for redundant parallel robots

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Böhm, Josef; Valášek, M.

    2003-01-01

    Roč. 31, č. 3 (2003), s. 413-432 ISSN 1539-7734 R&D Projects: GA ČR GA101/03/0620 Grant - others:CTU(CZ) 0204512 Institutional research plan: CEZ:AV0Z1075907 Keywords : parallel robot construction * generalized predictive control * drive redundancy Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0411126.pdf

  10. Metacognition Beliefs and General Health in Predicting Alexithymia in Students.

    Science.gov (United States)

    Babaei, Samaneh; Ranjbar Varandi, Shahryar; Hatami, Zohre; Gharechahi, Maryam

    2015-06-12

    The present study was conducted to investigate the role of metacognition beliefs and general health in alexithymia in Iranian students. This descriptive and correlational study included 200 participants of high schools students, selected randomly from students of two cities (Sari and Dargaz), Iran. Metacognitive Strategies Questionnaire (MCQ-30); the General Health Questionnaire (GHQ) and Farsi Version of the Toronto Alexithymia Scale (TAS-20) were used for gathering the data. Using the Pearson's correlation method and regression, the data were analyzed. The findings indicated significant positive relationships between alexithymia and all subscales of general health. The highest correlation was between alexithymia and anxiety subscale (r=0.36, Pmetacognitive strategies. The highest significant negative relationship was seen between alexithymia and the sub-scale of risk uncontrollability (r=-0.359, P Metacognition beliefs predicted about 8% of the variance of alexithymia (β=-0.028, Pmetacognition beliefs and general health had important role in predicting of alexithymia in students.

  11. Hybrid Predictive Control for Dynamic Transport Problems

    CERN Document Server

    Núñez, Alfredo A; Cortés, Cristián E

    2013-01-01

    Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

  12. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  13. Wind turbine control and model predictive control for uncertain systems

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz

    as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

  14. Predicting and Controlling Complex Networks

    Science.gov (United States)

    2015-06-22

    ubiquitous in nature and fundamental to evolution in ecosystems. However, a significant chal- lenge remains in understanding biodiversity since, by the...networks and control . . . . . . . . . . . . . . . . . . . 7 3.4 Pattern formation, synchronization and outbreak of biodiversity in cyclically...Ni, Y.-C. Lai, and C. Grebogi, “Pattern formation, synchronization and outbreak of biodiversity in cyclically competing games,” Physical Review E 83

  15. A Robustly Stabilizing Model Predictive Control Algorithm

    Science.gov (United States)

    Ackmece, A. Behcet; Carson, John M., III

    2007-01-01

    A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

  16. Dynamic Algorithm for LQGPC Predictive Control

    DEFF Research Database (Denmark)

    Hangstrup, M.; Ordys, A.W.; Grimble, M.J.

    1998-01-01

    into the controller design and the solution is derived using the method of Lagrange multipliers. It is shown how well-known GPC controller can be obtained as a special case of the LQGPC controller design. The important advantage of using the LQGPC framework for designing predictive, e.g. GPS is that LQGPC enables...

  17. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...

  18. Evaluating Prediction Markets for Internal Control Applications

    Science.gov (United States)

    2016-05-01

    would influence the survey indicators, the prediction market prices, and their sensitivity to misinformation. Finally, this study reveal s the results...realized in an academ ic setting. With a controll able number of influencing factors, the prediction markets were installed in several uni versity courses...of acceptance and the limited number of influencing factors in an academic setting, it is expected that the prediction market will perform

  19. General Purpose Crate (GPC) for control applications

    International Nuclear Information System (INIS)

    Singh, Kundan; Munda, Deepak K.; Jain, Mamta; Archunan, M.; Barua, P.; Ajith Kumar, B.P.

    2011-01-01

    A General Purpose Crate (GPC) capable of handling digital and analog Inputs/Outputs signals has been developed at Inter University Accelerator Centre (IUAC), New Delhi, for accelerator control system applications. The system includes back-plane bus with on board plugged-in single board computer with PC104 and Ethernet interface, running Linux operating system. The bus control logic is designed on the back-plane pcb itself, making the system more rugged. The various types of digital and analog input/output modules can be plugged into the back plane bus randomly with standard euro connectors, which provides highly reliable and dust free contacts. Maximum eight modules can be inserted into the crate. The total power consumption for various types of modules and back-plane controller is approximately 50 watts. The multi-output DC power supply from COSEL has been used in the crate. The general purpose crate is software compatible with the CAMAC crates used in the accelerator control system. (author)

  20. Delta-Domain Predictive Control and Identification for Control

    DEFF Research Database (Denmark)

    Lauritsen, Morten Bach

    1997-01-01

    -time and continuous-time theory. In addition these parametrizations possess certain numerical advantages compared to shift-operator representations. A new prediction method is developed. It is based on ideas from continuous-time but derived from discrete-time delta-operator models. It is shown to include the optimal...... minimum-variance predictor as a special case and to have a well-defined continuous-time limit. By means of this new prediction method a unified framework for discrete-time and continuous-time predictive control algorithms is developed. This contains a continuous-time like discrete-time predictive...... controller which is insensitive to the choice of sampling period and has a well-defined limit in the continuous-time case. Also more conventional discrete-time predictive control methods may be described within the unified approach. The predictive control algorithms are extended to frequency weighted...

  1. Predicting Melting Points of Organic Molecules: Applications to Aqueous Solubility Prediction Using the General Solubility Equation.

    Science.gov (United States)

    McDonagh, J L; van Mourik, T; Mitchell, J B O

    2015-11-01

    In this work we make predictions of several important molecular properties of academic and industrial importance to seek answers to two questions: 1) Can we apply efficient machine learning techniques, using inexpensive descriptors, to predict melting points to a reasonable level of accuracy? 2) Can values of this level of accuracy be usefully applied to predicting aqueous solubility? We present predictions of melting points made by several novel machine learning models, previously applied to solubility prediction. Additionally, we make predictions of solubility via the General Solubility Equation (GSE) and monitor the impact of varying the logP prediction model (AlogP and XlogP) on the GSE. We note that the machine learning models presented, using a modest number of 2D descriptors, can make melting point predictions in line with the current state of the art prediction methods (RMSE≥40 °C). We also find that predicted melting points, with an RMSE of tens of degrees Celsius, can be usefully applied to the GSE to yield accurate solubility predictions (log10 S RMSE<1) over a small dataset of drug-like molecules. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  3. Improved fuzzy PID controller design using predictive functional control structure.

    Science.gov (United States)

    Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

    2017-11-01

    In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Nonlinear Model Predictive Control for Cooperative Control and Estimation

    Science.gov (United States)

    Ru, Pengkai

    Recent advances in computational power have made it possible to do expensive online computations for control systems. It is becoming more realistic to perform computationally intensive optimization schemes online on systems that are not intrinsically stable and/or have very small time constants. Being one of the most important optimization based control approaches, model predictive control (MPC) has attracted a lot of interest from the research community due to its natural ability to incorporate constraints into its control formulation. Linear MPC has been well researched and its stability can be guaranteed in the majority of its application scenarios. However, one issue that still remains with linear MPC is that it completely ignores the system's inherent nonlinearities thus giving a sub-optimal solution. On the other hand, if achievable, nonlinear MPC, would naturally yield a globally optimal solution and take into account all the innate nonlinear characteristics. While an exact solution to a nonlinear MPC problem remains extremely computationally intensive, if not impossible, one might wonder if there is a middle ground between the two. We tried to strike a balance in this dissertation by employing a state representation technique, namely, the state dependent coefficient (SDC) representation. This new technique would render an improved performance in terms of optimality compared to linear MPC while still keeping the problem tractable. In fact, the computational power required is bounded only by a constant factor of the completely linearized MPC. The purpose of this research is to provide a theoretical framework for the design of a specific kind of nonlinear MPC controller and its extension into a general cooperative scheme. The controller is designed and implemented on quadcopter systems.

  5. Model predictive control of smart microgrids

    DEFF Research Database (Denmark)

    Hu, Jiefeng; Zhu, Jianguo; Guerrero, Josep M.

    2014-01-01

    required to realise high-performance of distributed generations and will realise innovative control techniques utilising model predictive control (MPC) to assist in coordinating the plethora of generation and load combinations, thus enable the effective exploitation of the clean renewable energy sources...

  6. [Predictive ocular motor control in Parkinson's disease].

    Science.gov (United States)

    Ying, Li; Liu, Zhen-Guo; Chen, Wei; Gan, Jing; Wang, Wen-An

    2008-02-19

    To investigate the changes of predictive ocular motor function in the patients with Parkinson's disease (PD), and to discuss its clinical value. Videonystagmography (VNG) was used to examine 24 patients with idiopathic Parkinson's disease, 15 males and 9 females, aged 61 +/- 6 (50-69), and 24 sex and age-matched healthy control subjects on random ocular saccade (with the target moving at random intervals to random positions) and predictive ocular saccade (with the 1.25-second light target moving 10 degrees right or left from the center). In the random ocular saccade program, the latency of saccade of the PD patients was 284 ms +/- 58 ms, significantly longer than that of the healthy controls (236 ms +/- 37 ms, P = 0.003). In the predictive ocular saccade pattern, the latency of saccades the PD patients was 150 ms +/- 138 ms, significantly longer than that of the healthy controls (59 ms +/- 102 ms, P = 0.002). The appearance rate of predictive saccades (with the latency of saccade <80 ms) in the PD group was 21%, significantly lower than that in the control group (31%, P = 0.003). There is dysfunction of predictive ocular motor control in the PD patients, and the cognitive function may be impaired at the early stage of PD.

  7. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  8. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2014-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  9. Neural predictive control for active buffet alleviation

    Science.gov (United States)

    Pado, Lawrence E.; Lichtenwalner, Peter F.; Liguore, Salvatore L.; Drouin, Donald

    1998-06-01

    The adaptive neural control of aeroelastic response (ANCAR) and the affordable loads and dynamics independent research and development (IRAD) programs at the Boeing Company jointly examined using neural network based active control technology for alleviating undesirable vibration and aeroelastic response in a scale model aircraft vertical tail. The potential benefits of adaptive control includes reducing aeroelastic response associated with buffet and atmospheric turbulence, increasing flutter margins, and reducing response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and thus loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Wind tunnel tests were undertaken on a rigid 15% scale aircraft in Boeing's mini-speed wind tunnel, which is used for testing at very low air speeds up to 80 mph. The model included a dynamically scaled flexible fail consisting of an aluminum spar with balsa wood cross sections with a hydraulically powered rudder. Neural predictive control was used to actuate the vertical tail rudder in response to strain gauge feedback to alleviate buffeting effects. First mode RMS strain reduction of 50% was achieved. The neural predictive control system was developed and implemented by the Boeing Company to provide an intelligent, adaptive control architecture for smart structures applications with automated synthesis, self-optimization, real-time adaptation, nonlinear control, and fault tolerance capabilities. It is designed to solve complex control problems though a process of automated synthesis, eliminating costly control design and surpassing it in many instances by accounting for real world non-linearities.

  10. Feedback model predictive control by randomized algorithms

    NARCIS (Netherlands)

    Batina, Ivo; Stoorvogel, Antonie Arij; Weiland, Siep

    2001-01-01

    In this paper we present a further development of an algorithm for stochastic disturbance rejection in model predictive control with input constraints based on randomized algorithms. The algorithm presented in our work can solve the problem of stochastic disturbance rejection approximately but with

  11. Predictive access control for distributed computation

    DEFF Research Database (Denmark)

    Yang, Fan; Hankin, Chris; Nielson, Flemming

    2013-01-01

    We show how to use aspect-oriented programming to separate security and trust issues from the logical design of mobile, distributed systems. The main challenge is how to enforce various types of security policies, in particular predictive access control policies — policies based on the future...

  12. Model predictive control for cooperative control of space robots

    Science.gov (United States)

    Kannan, Somasundar; Alamdari, Seyed Amin Sajadi; Dentler, Jan; Olivares-Mendez, Miguel A.; Voos, Holger

    2017-01-01

    The problem of Orbital Manipulation of Passive body is discussed here. Two scenarios including passive object rigidly attached to robotic servicers and passive body attached to servicers through manipulators are discussed. The Model Predictive Control (MPC) technique is briefly presented and successfully tested through simulations on two cases of position control of passive body in the orbit.

  13. Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances

    Science.gov (United States)

    Juang, Jer-Nan; Eure, Kenneth W.

    1998-01-01

    Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

  14. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....... and controlled have thus become essential factors for efficient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona...

  15. Fault Predictive Control of Compact Disk Players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Wickerhauser, Mladen Victor

    2006-01-01

    Optical disc players such as CD-players have problems playing certain discs with surface faults like scratches and fingerprints. The problem is to be found in the servo controller which positions the optical pick-up, such that the laser beam is focused on the information track. A scheme handling ...... of the feature based control scheme, such that a prediction step is included. The proposed scheme is compared with the feature based control scheme, in the perspective of handling surface faults, by simulations. These simulations show the improvements given by the proposed algorithm....

  16. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  17. Fault Tolerant Control Using Gaussian Processes and Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Yang Xiaoke

    2015-03-01

    Full Text Available Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.

  18. Model predictive control for a thermostatic controlled system

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Rasmussen, Henrik; Stoustrup, Jakob

    2013-01-01

    This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff...... temperatures are estimated by reduced order observers and evaporation temperature is regulated by an algorithmic suction pressure control scheme. The method is applied to a validated simulation benchmark. The results show that even with the thermostatic control valves, there exists significant potential...

  19. Multi-year predictability in a coupled general circulation model

    Energy Technology Data Exchange (ETDEWEB)

    Power, Scott; Colman, Rob [Bureau of Meteorology Research Centre, Melbourne, VIC (Australia)

    2006-02-01

    Multi-year to decadal variability in a 100-year integration of a BMRC coupled atmosphere-ocean general circulation model (CGCM) is examined. The fractional contribution made by the decadal component generally increases with depth and latitude away from surface waters in the equatorial Indo-Pacific Ocean. The relative importance of decadal variability is enhanced in off-equatorial ''wings'' in the subtropical eastern Pacific. The model and observations exhibit ''ENSO-like'' decadal patterns. Analytic results are derived, which show that the patterns can, in theory, occur in the absence of any predictability beyond ENSO time-scales. In practice, however, modification to this stochastic view is needed to account for robust differences between ENSO-like decadal patterns and their interannual counterparts. An analysis of variability in the CGCM, a wind-forced shallow water model, and a simple mixed layer model together with existing and new theoretical results are used to improve upon this stochastic paradigm and to provide a new theory for the origin of decadal ENSO-like patterns like the Interdecadal Pacific Oscillation and Pacific Decadal Oscillation. In this theory, ENSO-driven wind-stress variability forces internal equatorially-trapped Kelvin waves that propagate towards the eastern boundary. Kelvin waves can excite reflected internal westward propagating equatorially-trapped Rossby waves (RWs) and coastally-trapped waves (CTWs). CTWs have no impact on the off-equatorial sub-surface ocean outside the coastal wave guide, whereas the RWs do. If the frequency of the incident wave is too high, then only CTWs are excited. At lower frequencies, both CTWs and RWs can be excited. The lower the frequency, the greater the fraction of energy transmitted to RWs. This lowers the characteristic frequency of variability off the equator relative to its equatorial counterpart. Both the eastern boundary interactions and the accumulation of

  20. Predictive congestion control mechanism for MANET

    OpenAIRE

    S. Subburam; P. Sheik Abdul Khader

    2012-01-01

    In adhoc networks connection failure between source and destination often occurs, due to mobility of nodes. After every failure the connection between source and destination gets disconnected.The problem is while sending data packets from source to destination, there is a possibility of occurring congestion at any node incurring high packet loss and long delay, which cause the performance degradation of a network. This paper presents predictive congestion control routing protocol for wireless...

  1. Recent and past musical activity predicts cognitive aging variability: direct comparison with general lifestyle activities.

    Science.gov (United States)

    Hanna-Pladdy, Brenda; Gajewski, Byron

    2012-01-01

    Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years) on preserved cognitive functioning in advanced age. These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to non-musical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in general lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study controlled for general activity level in evaluating cognition between musicians and nomusicians. Also, the timing of engagement (age of acquisition, past versus recent) was assessed in predictive models of successful cognitive aging. Seventy age and education matched older musicians (>10 years) and non-musicians (ages 59-80) were evaluated on neuropsychological tests and general lifestyle activities. Musicians scored higher on tests of phonemic fluency, verbal working memory, verbal immediate recall, visuospatial judgment, and motor dexterity, but did not differ in other general leisure activities. Partition analyses were conducted on significant cognitive measures to determine aspects of musical training predictive of enhanced cognition. The first partition analysis revealed education best predicted visuospatial functions in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (memory in musicians, while analyses for other measures were not predictive. Recent and past musical activity, but not general lifestyle activities, predicted variability

  2. Fault Predictive Control of Compact Disk Players

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Wickerhauser, Mladen Victor

    2006-01-01

    Optical disc players such as CD-players have problems playing certain discs with surface faults like scratches and fingerprints. The problem is to be found in the servo controller which positions the optical pick-up, such that the laser beam is focused on the information track. A scheme handling...... this problem, called feature based control, has been presented in an other publications of the first author. This scheme is based on an assumption that the surface faults do not change from encounter to encounter. This assumption is unfortunately not entirely true. This paper proposes an improvement...... of the feature based control scheme, such that a prediction step is included. The proposed scheme is compared with the feature based control scheme, in the perspective of handling surface faults, by simulations. These simulations show the improvements given by the proposed algorithm....

  3. 33 CFR 6.12-1 - General supervision and control.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 1 2010-07-01 2010-07-01 false General supervision and control... GENERAL PROTECTION AND SECURITY OF VESSELS, HARBORS, AND WATERFRONT FACILITIES Supervision and Control of Explosives or Other Dangerous Cargo § 6.12-1 General supervision and control. The Captain of the Port may...

  4. Generalized Joint Hypermobility Is Predictive of Hip Capsular Thickness.

    Science.gov (United States)

    Devitt, Brian M; Smith, Bjorn N; Stapf, Robert; Tacey, Mark; O'Donnell, John M

    2017-04-01

    The pathomechanics of hip microinstability are not clearly defined but are thought to involve anatomical abnormalities, repetitive forces across the hip, and ligamentous laxity. The purpose of this study was to explore the relationship between generalized joint hypermobility (GJH) and hip capsular thickness. The hypothesis was that GJH would be predictive of a thin hip capsule. Cross-sectional study; Level of evidence, 3. A prospective study was performed on 100 consecutive patients undergoing primary hip arthroscopy for the treatment of hip pain. A Beighton test score (BTS) was obtained prior to each procedure. The maximum score was 9, and a score of ≥4 was defined as hypermobile. Capsular thickness at the level of the anterior portal, corresponding to the location of the iliofemoral ligament, was measured arthroscopically using a calibrated probe. The presence of ligamentum teres (LT) pathology was also recorded. Fifty-five women and 45 men were included in the study. The mean age was 32 years (range, 18-45 years). The median hip capsule thickness was statistically greater in men than women (12.5 and 7.5 mm, respectively). The median BTS for men was 1 compared with 4 for women ( P BTS and capsular thickness; a BTS of BTS ≥4 correlates with a capsular thickness of BTS of ≥4 ( P BTS of BTS ≥4 correlates significantly with a thickness of <10 mm.

  5. Generalized Joint Hypermobility Is Predictive of Hip Capsular Thickness

    Science.gov (United States)

    Devitt, Brian M.; Smith, Bjorn N.; Stapf, Robert; Tacey, Mark; O’Donnell, John M.

    2017-01-01

    Background: The pathomechanics of hip microinstability are not clearly defined but are thought to involve anatomical abnormalities, repetitive forces across the hip, and ligamentous laxity. Purpose/Hypothesis: The purpose of this study was to explore the relationship between generalized joint hypermobility (GJH) and hip capsular thickness. The hypothesis was that GJH would be predictive of a thin hip capsule. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A prospective study was performed on 100 consecutive patients undergoing primary hip arthroscopy for the treatment of hip pain. A Beighton test score (BTS) was obtained prior to each procedure. The maximum score was 9, and a score of ≥4 was defined as hypermobile. Capsular thickness at the level of the anterior portal, corresponding to the location of the iliofemoral ligament, was measured arthroscopically using a calibrated probe. The presence of ligamentum teres (LT) pathology was also recorded. Results: Fifty-five women and 45 men were included in the study. The mean age was 32 years (range, 18-45 years). The median hip capsule thickness was statistically greater in men than women (12.5 and 7.5 mm, respectively). The median BTS for men was 1 compared with 4 for women (P hip capsular thickness. A BTS of <4 correlates significantly with a capsular thickness of ≥10 mm, while a BTS ≥4 correlates significantly with a thickness of <10 mm. PMID:28451620

  6. Explicit prediction of ice clouds in general circulation models

    Science.gov (United States)

    Kohler, Martin

    1999-11-01

    Although clouds play extremely important roles in the radiation budget and hydrological cycle of the Earth, there are large quantitative uncertainties in our understanding of their generation, maintenance and decay mechanisms, representing major obstacles in the development of reliable prognostic cloud water schemes for General Circulation Models (GCMs). Recognizing their relative neglect in the past, both observationally and theoretically, this work places special focus on ice clouds. A recent version of the UCLA - University of Utah Cloud Resolving Model (CRM) that includes interactive radiation is used to perform idealized experiments to study ice cloud maintenance and decay mechanisms under various conditions in term of: (1) background static stability, (2) background relative humidity, (3) rate of cloud ice addition over a fixed initial time-period and (4) radiation: daytime, nighttime and no-radiation. Radiation is found to have major effects on the life-time of layer-clouds. Optically thick ice clouds decay significantly slower than expected from pure microphysical crystal fall-out (taucld = 0.9--1.4 h as opposed to no-motion taumicro = 0.5--0.7 h). This is explained by the upward turbulent fluxes of water induced by IR destabilization, which partially balance the downward transport of water by snowfall. Solar radiation further slows the ice-water decay by destruction of the inversion above cloud-top and the resulting upward transport of water. Optically thin ice clouds, on the other hand, may exhibit even longer life-times (>1 day) in the presence of radiational cooling. The resulting saturation mixing ratio reduction provides for a constant cloud ice source. These CRM results are used to develop a prognostic cloud water scheme for the UCLA-GCM. The framework is based on the bulk water phase model of Ose (1993). The model predicts cloud liquid water and cloud ice separately, and which is extended to split the ice phase into suspended cloud ice (predicted

  7. Economic model predictive control theory, formulations and chemical process applications

    CERN Document Server

    Ellis, Matthew; Christofides, Panagiotis D

    2017-01-01

    This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes. In addition to being...

  8. 33 CFR 154.808 - Vapor control system, general.

    Science.gov (United States)

    2010-07-01

    ... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false Vapor control system, general... (CONTINUED) POLLUTION FACILITIES TRANSFERRING OIL OR HAZARDOUS MATERIAL IN BULK Vapor Control Systems § 154.808 Vapor control system, general. (a) A vapor control system design and installation must eliminate...

  9. Sparse Packetized Predictive Control for Networked Control over Erasure Channels

    DEFF Research Database (Denmark)

    Nagahara, Masaaki; Quevedo, Daniel E.; Østergaard, Jan

    2014-01-01

    We study feedback control over erasure channels with packet-dropouts. To achieve robustness with respect to packet-dropouts, the controller transmits data packets containing plant input predictions, which minimize a finite horizon cost function. To reduce the data size of packets, we propose...... to adopt sparsity-promoting optimizations, namely, l1 - l2 and l2-constrained l0 optimizations, for which efficient algorithms exist. We show how to design the tuning parameters to ensure (practical) stability of the resulting feedback control systems when the number of consecutive packet...

  10. Endogenous Generalized Weights under DEA Control

    DEFF Research Database (Denmark)

    Agrell, Per J.; Bogetoft, Peter

    Non-parametric efficiency analysis, such as Data Envelopment Analysis (DEA) relies so far on endogenous local or exogenous general weights, based on revealed preferences or market prices. However, as DEA is gaining popularity in regulation and normative budgeting, the strategic interest of the ev......Non-parametric efficiency analysis, such as Data Envelopment Analysis (DEA) relies so far on endogenous local or exogenous general weights, based on revealed preferences or market prices. However, as DEA is gaining popularity in regulation and normative budgeting, the strategic interest...... of the evaluated industry calls for attention. We offer endogenous general prices based on a reformulation of DEA where the units collectively propose the set of weights that maximize their efficiency. Thus, the sector-wide efficiency is then a result of compromising the scores of more specialized smaller units...

  11. Model predictive control of room temperature with disturbance compensation

    Science.gov (United States)

    Kurilla, Jozef; Hubinský, Peter

    2017-08-01

    This paper deals with temperature control of multivariable system of office building. The system is simplified to several single input-single output systems by decoupling their mutual linkages, which are separately controlled by regulator based on generalized model predictive control. Main part of this paper focuses on the accuracy of the office temperature with respect to occupancy profile and effect of disturbance. Shifting of desired temperature and changing of weighting coefficients are used to achieve the desired accuracy of regulation. The final structure of regulation joins advantages of distributed computing power and possibility to use network communication between individual controllers to consider the constraints. The advantage of using decoupled MPC controllers compared to conventional PID regulators is demonstrated in a simulation study.

  12. 49 CFR 192.475 - Internal corrosion control: General.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 3 2010-10-01 2010-10-01 false Internal corrosion control: General. 192.475... Control § 192.475 Internal corrosion control: General. (a) Corrosive gas may not be transported by... taken to minimize internal corrosion. (b) Whenever any pipe is removed from a pipeline for any reason...

  13. A controllability test for general first-order representations

    NARCIS (Netherlands)

    U. Helmke; J. Rosenthal; J.M. Schumacher (Hans)

    1995-01-01

    textabstractIn this paper we derive a new controllability rank test for general first-order representations. The criterion generalizes the well-known controllability rank test for linear input-state systems as well as a controllability rank test by Mertzios et al. for descriptor systems.

  14. Circuit-wide structural and functional measures predict ventromedial prefrontal cortex fear generalization: implications for generalized anxiety disorder.

    Science.gov (United States)

    Cha, Jiook; Greenberg, Tsafrir; Carlson, Joshua M; Dedora, Daniel J; Hajcak, Greg; Mujica-Parodi, Lilianne R

    2014-03-12

    The ventromedial prefrontal cortex (vmPFC) plays a critical role in a number of evaluative processes, including risk assessment. Impaired discrimination between threat and safety is considered a hallmark of clinical anxiety. Here, we investigated the circuit-wide structural and functional mechanisms underlying vmPFC threat-safety assessment in humans. We tested patients with generalized anxiety disorder (GAD; n = 32, female) and healthy controls (n = 25, age-matched female) on a task that assessed the generalization of conditioned threat during fMRI scanning. The task consisted of seven rectangles of graded widths presented on a screen; only the midsize one was paired with mild electric shock [conditioned stimulus (CS)], while the others, safety cues, systematically varied in width by ±20, 40, and 60% [generalization stimuli (GS)] compared with the CS. We derived an index reflecting vmPFC functioning from the BOLD reactivity on a continuum of threat (CS) to safety (GS least similar to CS); patients with GAD showed less discrimination between threat and safety cues, compared with healthy controls (Greenberg et al., 2013b). Using structural, functional (i.e., resting-state), and diffusion MRI, we measured vmPFC thickness, vmPFC functional connectivity, and vmPFC structural connectivity within the corticolimbic systems. The results demonstrate that all three factors predict individual variability of vmPFC threat assessment in an independent fashion. Moreover, these neural features are also linked to GAD, most likely via an vmPFC fear generalization. Our results strongly suggest that vmPFC threat processing is closely associated with broader corticolimbic circuit anomalies, which may synergistically contribute to clinical anxiety.

  15. General and religious coping predict drinking outcomes for alcohol dependent adults in treatment.

    Science.gov (United States)

    Martin, Rosemarie A; Ellingsen, Victor J; Tzilos, Golfo K; Rohsenow, Damaris J

    2015-04-01

    Religiosity is associated with improved treatment outcomes among adults with alcohol dependence; however, it is unknown whether religious coping predicts drinking outcomes above and beyond the effects of coping in general, and whether gender differences exist. We assessed 116 alcohol-dependent adults (53% women; mean age = 37, SD = 8.6) for use of religious coping, general coping, and alcohol use within 2 weeks of entering outpatient treatment, and again 6 months after treatment. Religious coping at 6 months predicted fewer heavy alcohol use days and fewer drinks per day. This relationship was no longer significant after controlling for general coping at 6 months. The relationship between the use of religious coping strategies and drinking outcomes is not independent of general coping. Coping skills training that includes religious coping skills, as one of several coping methods, may be useful for a subset of adults early in recovery. This novel, prospective study assessed the relationship between religious coping strategies, general coping, and treatment outcomes for alcohol-dependent adults in treatment with results suggesting that the use of religious coping as one of several coping methods may be useful for a subset of adults early in recovery. © American Academy of Addiction Psychiatry.

  16. Prediction Governors for Input-Affine Nonlinear Systems and Application to Automatic Driving Control

    Directory of Open Access Journals (Sweden)

    Yuki Minami

    2018-04-01

    Full Text Available In recent years, automatic driving control has attracted attention. To achieve a satisfactory driving control performance, the prediction accuracy of the traveling route is important. If a highly accurate prediction method can be used, an accurate traveling route can be obtained. Despite the considerable efforts that have been invested in improving prediction methods, prediction errors do occur in general. Thus, a method to minimize the influence of prediction errors on automatic driving control systems is required. This need motivated us to focus on the design of a mechanism for shaping prediction signals, which is called a prediction governor. In this study, we first extended our previous study to the input-affine nonlinear system case. Then, we analytically derived a solution to an optimal design problem of prediction governors. Finally, we applied the solution to an automatic driving control system, and demonstrated its usefulness through a numerical example and an experiment using a radio controlled car.

  17. Prediction of cloud droplet number in a general circulation model

    Energy Technology Data Exchange (ETDEWEB)

    Ghan, S.J.; Leung, L.R. [Pacific Northwest National Lab., Richland, WA (United States)

    1996-04-01

    We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.

  18. Validation of the mortality prediction equation for damage control ...

    African Journals Online (AJOL)

    , preoperative lowest pH and lowest core body temperature to derive an equation for the purpose of predicting mortality in damage control surgery. It was shown to reliably predict death despite damage control surgery. The equation derivation ...

  19. Prediction of RNA secondary structure using generalized centroid estimators.

    Science.gov (United States)

    Hamada, Michiaki; Kiryu, Hisanori; Sato, Kengo; Mituyama, Toutai; Asai, Kiyoshi

    2009-02-15

    Recent studies have shown that the methods for predicting secondary structures of RNAs on the basis of posterior decoding of the base-pairing probabilities has an advantage with respect to prediction accuracy over the conventionally utilized minimum free energy methods. However, there is room for improvement in the objective functions presented in previous studies, which are maximized in the posterior decoding with respect to the accuracy measures for secondary structures. We propose novel estimators which improve the accuracy of secondary structure prediction of RNAs. The proposed estimators maximize an objective function which is the weighted sum of the expected number of the true positives and that of the true negatives of the base pairs. The proposed estimators are also improved versions of the ones used in previous works, namely CONTRAfold for secondary structure prediction from a single RNA sequence and McCaskill-MEA for common secondary structure prediction from multiple alignments of RNA sequences. We clarify the relations between the proposed estimators and the estimators presented in previous works, and theoretically show that the previous estimators include additional unnecessary terms in the evaluation measures with respect to the accuracy. Furthermore, computational experiments confirm the theoretical analysis by indicating improvement in the empirical accuracy. The proposed estimators represent extensions of the centroid estimators proposed in Ding et al. and Carvalho and Lawrence, and are applicable to a wide variety of problems in bioinformatics. Supporting information and the CentroidFold software are available online at: http://www.ncrna.org/software/centroidfold/.

  20. Generalized model for predicting methane conversion to syngas in ...

    African Journals Online (AJOL)

    International Journal of Engineering, Science and Technology ... Abstract. Present work aims to provide a conceptual framework for predicting methane conversion efficiency and CO selectivity in a membrane reactor which may assist in selecting the type of membrane and minimizing the cost of syngas production.

  1. Distributed predictive control of spiral wave in cardiac excitable media

    International Nuclear Information System (INIS)

    Zheng-Ning, Gan; Xin-Ming, Cheng

    2010-01-01

    In this paper, we propose the distributed predictive control strategies of spiral wave in cardiac excitable media. The modified FitzHugh–Nagumo model was used to express the cardiac excitable media approximately. Based on the control-Lyapunov theory, we obtained the distributed control equation, which consists of a positive control-Lyapunov function and a positive cost function. Using the equation, we investigate two kinds of robust control strategies: the time-dependent distributed control strategy and the space-time dependent distributed control strategy. The feasibility of the strategies was demonstrated via an illustrative example, in which the spiral wave was prevented to occur, and the possibility for inducing ventricular fibrillation was eliminated. The strategies are helpful in designing various cardiac devices. Since the second strategy is more efficient and robust than the first one, and the response time in the second strategy is far less than that in the first one, the former is suitable for the quick-response control systems. In addition, our spatiotemporal control strategies, especially the second strategy, can be applied to other cardiac models, even to other reaction-diffusion systems. (general)

  2. Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Fengxiang Wang

    2018-01-01

    Full Text Available Field oriented control (FOC, direct torque control (DTC and finite set model predictive control (FS-MPC are different strategies for high performance electrical drive systems. FOC uses linear controllers and pulse width modulation (PWM to control the fundamental components of the load voltages. On the other hand, DTC and FS-MPC are nonlinear strategies that generate directly the voltage vectors in the absence of a modulator. This paper presents all three methods starting from theoretic operating principles, control structures and implementation. Experimental assessment is performed to discuss their advantages and limitations in detail. As main conclusions of this work, it is affirmed that different strategies have their own merits and all meet the requirements of modern high performance drives.

  3. Predictive Control of Networked Multiagent Systems via Cloud Computing.

    Science.gov (United States)

    Liu, Guo-Ping

    2017-01-18

    This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

  4. Fuzzy Logic Decoupled Longitudinal Control for General Aviation Airplanes

    Science.gov (United States)

    Duerksen, Noel

    1996-01-01

    It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control difference airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control throttle position and another to control elevator position. These two controllers were used to control flight path angle and airspeed for both a piston powered single engine airplane simulation and a business jet simulation. Overspeed protection and stall protection were incorporated in the form of expert systems supervisors. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic longitudinal controller could be successfully used on two general aviation aircraft types that have very difference characteristics. These controllers worked for both airplanes over their entire flight envelopes including configuration changes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle lever travel, etc.). The controllers also handled configuration changes without mode switching or knowledge of the current configuration. This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.

  5. Predicting Loss-of-Control Boundaries Toward a Piloting Aid

    Science.gov (United States)

    Barlow, Jonathan; Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

  6. Fuzzy Logic Decoupled Lateral Control for General Aviation Airplanes

    Science.gov (United States)

    Duerksen, Noel

    1997-01-01

    It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control different airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control aileron or roll spoiler position. This controller was used to control bank angle for both a piston powered single engine aileron equipped airplane simulation and a business jet simulation which used spoilers for primary roll control. Overspeed, stall and overbank protection were incorporated in the form of expert systems supervisors and weighted fuzzy rules. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic lateral controller could be successfully used on two general aviation aircraft types that have very different characteristics. These controllers worked for both airplanes over their entire flight envelopes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle ]ever travel, etc.). This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.

  7. DEEP: a general computational framework for predicting enhancers

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2014-11-05

    Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer\\'s properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/.

  8. Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.

    Science.gov (United States)

    Lai, Ying-Cheng; Harrison, Mary Ann F; Frei, Mark G; Osorio, Ivan

    2004-09-01

    Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents. Three approaches are employed. (1) We present qualitative arguments suggesting that the Lyapunov exponents generally are not useful for seizure prediction. (2) We construct a two-dimensional, nonstationary chaotic map with a parameter slowly varying in a range containing a crisis, and test whether this critical event can be predicted by monitoring the evolution of finite-time Lyapunov exponents. This can thus be regarded as a "control test" for the claimed predictive power of the exponents for seizure. We find that two major obstacles arise in this application: statistical fluctuations of the Lyapunov exponents due to finite time computation and noise from the time series. We show that increasing the amount of data in a moving window will not improve the exponents' detective power for characteristic system changes, and that the presence of small noise can ruin completely the predictive power of the exponents. (3) We report negative results obtained from ECoG signals recorded from patients with epilepsy. All these indicate firmly that, the use of Lyapunov exponents for seizure prediction is practically impossible as the brain dynamical system generating the ECoG signals is more complicated than low-dimensional chaotic systems, and is noisy. Copyright 2004 American Institute of Physics

  9. Troponin I and cardiovascular risk prediction in the general population

    DEFF Research Database (Denmark)

    Blankenberg, Stefan; Salomaa, Veikko; Makarova, Nataliya

    2016-01-01

    population-based studies including 74 738 participants. We investigated the value of adding troponin I levels to conventional risk factors for prediction of cardiovascular disease by calculating measures of discrimination (C-index) and net reclassification improvement (NRI). We further tested the clinical....... The addition of troponin I information to a prognostic model for cardiovascular death constructed of ESC SCORE variables increased the C-index discrimination measure by 0.007 and yielded an NRI of 0.048, whereas the addition to prognostic models for cardiovascular disease and total mortality led to lesser C......-index discrimination and NRI increment. In individuals above 6 ng/L of troponin I, a concentration near the upper quintile in BiomarCaRE (5.9 ng/L) and JUPITER (5.8 ng/L), rosuvastatin therapy resulted in higher absolute risk reduction compared with individuals

  10. Testing General Relativistic Predictions with the LAGEOS Satellites

    Directory of Open Access Journals (Sweden)

    Roberto Peron

    2014-01-01

    Full Text Available The spacetime around Earth is a good environment in order to perform tests of gravitational theories. According to Einstein’s view of gravitational phenomena, the Earth mass-energy content curves the surrounding spacetime in a peculiar way. This (relatively quiet dynamical environment enables a good reconstruction of geodetic satellites (test masses orbit, provided that high-quality tracking data are available. This is the case of the LAGEOS satellites, built and launched mainly for geodetic and geodynamical purposes, but equally good for fundamental physics studies. A review of these studies is presented, focusing on data, models, and analysis strategies. Some recent and less recent results are presented. All of them indicate general relativity theory as a very good description of gravitational phenomena, at least in the studied environment.

  11. Model-free adaptive sliding mode controller design for generalized ...

    Indian Academy of Sciences (India)

    L M WANG

    2017-08-16

    Aug 16, 2017 ... A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) ... the neural network theory, a model-free adaptive sliding mode controller is designed to guarantee asymptotic stability of the generalized ..... following optimization parameters are needed: ⎧.

  12. Client-Controlled Case Information: A General System Theory Perspective

    Science.gov (United States)

    Fitch, Dale

    2004-01-01

    The author proposes a model for client control of case information via the World Wide Web built on principles of general system theory. It incorporates the client into the design, resulting in an information structure that differs from traditional human services information-sharing practices. Referencing general system theory, the concepts of…

  13. Characterizing and predicting rates of delirium across general hospital settings.

    Science.gov (United States)

    McCoy, Thomas H; Hart, Kamber L; Perlis, Roy H

    2017-05-01

    To better understand variation in reported rates of delirium, this study characterized delirium occurrence rate by department of service and primary admitting diagnosis. Nine consecutive years (2005-2013) of general hospital admissions (N=831,348) were identified across two academic medical centers using electronic health records. The primary admitting diagnosis and the treating clinical department were used to calculate occurrence rates of a previously published delirium definition composed of billing codes and natural language processing of discharge summaries. Delirium rates varied significantly across both admitting diagnosis group (X 2 10 =12786, pdelirium (86/109764; 0.08%) and neurological admissions the greatest (2851/25450; 11.2%). Although the rate of delirium varied across the two hospitals the relative rates within departments (r=0.96, pdelirium varies significantly across admitting diagnosis and hospital department. Both admitting diagnosis and department of care are even stronger predictors of risk than age; as such, simple risk stratification may offer avenues for targeted prevention and treatment efforts. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Assessment of Specific Characteristics of Abnormal General Movements: Does It Enhance the Prediction of Cerebral Palsy?

    Science.gov (United States)

    Hamer, Elisa G.; Bos, Arend F.; Hadders-Algra, Mijna

    2011-01-01

    Aim: Abnormal general movements at around 3 months corrected age indicate a high risk of cerebral palsy (CP). We aimed to determine whether specific movement characteristics can improve the predictive power of definitely abnormal general movements. Method: Video recordings of 46 infants with definitely abnormal general movements at 9 to 13 weeks…

  15. Self-Control, Social Factors, and Delinquency: A Test of the General Theory of Crime among Adolescents in Hong Kong

    Science.gov (United States)

    Cheung, Nicole W. T.; Cheung, Yuet W.

    2008-01-01

    The objectives of this study were to test the predictive power of self-control theory for delinquency in a Chinese context, and to explore if social factors as predicted in social bonding theory, differential association theory, general strain theory, and labeling theory have effects on delinquency in the presence of self-control. Self-report data…

  16. Traffic Predictive Control: Case Study and Evaluation

    Science.gov (United States)

    2017-06-26

    This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficien...

  17. Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space...... model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model...

  18. Generalized projective synchronization of chaotic systems via adaptive learning control

    International Nuclear Information System (INIS)

    Yun-Ping, Sun; Jun-Min, Li; Hui-Lin, Wang; Jiang-An, Wang

    2010-01-01

    In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)

  19. Sparse generalized functional linear model for predicting remission status of depression patients.

    Science.gov (United States)

    Liu, Yashu; Nie, Zhi; Zhou, Jiayu; Farnum, Michael; Narayan, Vaibhav A; Wittenberg, Gayle; Ye, Jieping

    2014-01-01

    Complex diseases such as major depression affect people over time in complicated patterns. Longitudinal data analysis is thus crucial for understanding and prognosis of such diseases and has received considerable attention in the biomedical research community. Traditional classification and regression methods have been commonly applied in a simple (controlled) clinical setting with a small number of time points. However, these methods cannot be easily extended to the more general setting for longitudinal analysis, as they are not inherently built for time-dependent data. Functional regression, in contrast, is capable of identifying the relationship between features and outcomes along with time information by assuming features and/or outcomes as random functions over time rather than independent random variables. In this paper, we propose a novel sparse generalized functional linear model for the prediction of treatment remission status of the depression participants with longitudinal features. Compared to traditional functional regression models, our model enables high-dimensional learning, smoothness of functional coefficients, longitudinal feature selection and interpretable estimation of functional coefficients. Extensive experiments have been conducted on the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) data set and the results show that the proposed sparse functional regression method achieves significantly higher prediction power than existing approaches.

  20. An international risk prediction algorithm for the onset of generalized anxiety and panic syndromes in general practice attendees : predictA

    NARCIS (Netherlands)

    King, M.; Bottomley, C.; Bellon-Saameno, J. A.; Torres-Gonzalez, F.; Svab, I.; Rifel, J.; Maaroos, H. -I.; Aluoja, A.; Geerlings, M. I.; Xavier, M.; Carraca, I.; Vicente, B.; Saldivia, S.; Nazareth, I.

    Background. There are no risk models for the prediction of anxiety that may help in prevention. We aimed to develop a risk algorithm for the onset of generalized anxiety and panic syndromes. Method. Family practice attendees were recruited between April 2003 and February 2005 and followed over 24

  1. Generalized Minimum Variance Control for MDOF Structures under Earthquake Excitation

    Directory of Open Access Journals (Sweden)

    Lakhdar Guenfaf

    2016-01-01

    Full Text Available Control of a multi-degree-of-freedom structural system under earthquake excitation is investigated in this paper. The control approach based on the Generalized Minimum Variance (GMV algorithm is developed and presented. Our approach is a generalization to multivariable systems of the GMV strategy designed initially for single-input-single-output (SISO systems. Kanai-Tajimi and Clough-Penzien models are used to generate the seismic excitations. Those models are calculated using the specific soil parameters. Simulation tests using a 3DOF structure are performed and show the effectiveness of the control method.

  2. Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

    NARCIS (Netherlands)

    Wang, M.

    2014-01-01

    This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

  3. Speed Control of General Purpose Engine with Electronic Governor

    Science.gov (United States)

    Sawut, Umerujan; Tohti, Gheyret; Takigawa, Buso; Tsuji, Teruo

    This paper presents a general purpose engine speed control system with an electronic governor in order to improve the current system with a mechanical governor which shows unstable characteristics by change of mecanical friction or A/F ratio (Air/Fuel ratio). For the control system above, there are problems that the feedback signal is only a crank angle because of cost and the controlled object is a general purpose engine which is strongly nonlinear. In order to overcome these problems, the system model is shown for the dynamic estimation of the amount of air flow and the robust controller is designed. That is, the proposed system includes the robust sliding-mode controller by the feedback signal of only a crank angle where Genetic Algorithm is applied for the controller design. The simulation and the experiments by MATLAB/Simulink are performed to show the effectiveness of our proposal.

  4. DESIGN AND IMPLEMENTATION OF FUZZY PREDICTIVE CONTROLLER FOR DISTILLATION COLUMN

    Directory of Open Access Journals (Sweden)

    SIVAKUMAR. R.

    2016-12-01

    Full Text Available Most of the real systems exhibit non-linear nature; conventional controllers are not always able to provide good and acceptable results. This paper presents a hybrid control strategy of Model Predictive Control (MPC and Fuzzy Logic Control (FLC. The Fuzzy Model Predictive Control (FMPC approach is developed to control various distillation column models. The performance measures like settling time, peak overshoot, Integral Square Error (ISE and Integral Absolute Error (IAE of FMPC is validated with MPC, FLC and conventional multi loop PI controller. The simulation results shows that the FMPC has better performance than other controller on various distillation column models.

  5. Proposed general amendments to the atomic energy control regulations

    International Nuclear Information System (INIS)

    1986-01-01

    Canada's Atomic Energy Control Act defines the powers and responsibilities of the Atomic Energy Control Board (AECB). Among these is to make regulations to control the development, application and use of atomic energy. In these proposed general amendments to the Atomic Energy Control Regulations substantial changes are proposed in the designation of the authority of AECB staff, exemptions from licensing, international safeguards, duties of licensees and atomic radiation workers, security of information, and provision for hearings. The scope of the control of atomic energy has been redefined as relating to matters of health, safety, security, international safeguards, and the protection of the environment

  6. Neural network predictive control of a heat exchanger

    OpenAIRE

    2011-01-01

    Abstract The study attempts to show that using the neural network predictive control (NNPC) structure for control of thermal processes can lead to energy savings. The advantage of the NNPC is that it is not a linear-model-based strategy and the control input constraints are directly included into the synthesis. In the designed approach, the neural network is used as a nonlinear process model to predict the future behaviour of the controlled process with distributed parameters. The ...

  7. Comparison of Predictive Control Methods for High Consumption Industrial Furnace

    Directory of Open Access Journals (Sweden)

    Goran Stojanovski

    2013-01-01

    Full Text Available We describe several predictive control approaches for high consumption industrial furnace control. These furnaces are major consumers in production industries, and reducing their fuel consumption and optimizing the quality of the products is one of the most important engineer tasks. In order to demonstrate the benefits from implementation of the advanced predictive control algorithms, we have compared several major criteria for furnace control. On the basis of the analysis, some important conclusions have been drawn.

  8. Perceived emotional intelligence, general intelligence and early professional success: predictive and incremental validity

    Directory of Open Access Journals (Sweden)

    José-Manuel de Haro

    2014-05-01

    Full Text Available Although the study of factors affecting career success has shown connections between biographical and other aspects related to ability, knowledge and personality, few studies have examined the relationship between emotional intelligence and professional success at the initial career stage. When these studies were carried out, the results showed significant relationships between the dimensions of emotional intelligence (emotional self-awareness, self-regulation, social awareness or social skills and the level of professional competence. In this paper, we analyze the relationship between perceived emotional intelligence, measured by the Trait Meta-Mood Scale (TMMS-24 questionnaire, general intelligence assessed by the Cattell factor "g" test, scale 3, and extrinsic indicators of career success, in a sample of 130 graduates at the beginning of their careers. Results from hierarchical regression analysis indicate that emotional intelligence makes a specific contribution to the prediction of salary, after controlling the general intelligence effect. The perceived emotional intelligence dimensions of TMMS repair, TMMS attention and sex show a higher correlation and make a greater contribution to professional success than general intelligence. The implications of these results for the development of socio-emotional skills among University graduates are discussed.

  9. Why are predictions of general relativity theory for gravitational effects non-unique?

    International Nuclear Information System (INIS)

    Loskutov, Yu.M.

    1990-01-01

    Reasons of non-uniqueness of predictions of the general relativity theory (GRT) for gravitational effects are analyzed in detail. To authors' opinion, the absence of comparison mechanism of curved and plane metrics is the reason of non-uniqueness

  10. Model Predictive Control of Wind Turbines

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian

    Wind turbines play a major role in the transformation from a fossil fuel based energy production to a more sustainable production of energy. Total-cost-of-ownership is an important parameter when investors decide in which energy technology they should place their capital. Modern wind turbines...... are controlled by pitching the blades and by controlling the electro-magnetic torque of the generator, thus slowing the rotation of the blades. Improved control of wind turbines, leading to reduced fatigue loads, can be exploited by using less materials in the construction of the wind turbine or by reducing...... the need for maintenance of the wind turbine. Either way, better total-cost-of-ownership for wind turbine operators can be achieved by improved control of the wind turbines. Wind turbine control can be improved in two ways, by improving the model on which the controller bases its design or by improving...

  11. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations ...

  12. Model predictive control of a 3-DOF helicopter system using ...

    African Journals Online (AJOL)

    ... by simulation, and its performance is compared with that achieved by linear model predictive control (LMPC). Keywords: nonlinear systems, helicopter dynamics, MIMO systems, model predictive control, successive linearization. International Journal of Engineering, Science and Technology, Vol. 2, No. 10, 2010, pp. 9-19 ...

  13. Climate control loads prediction of electric vehicles

    International Nuclear Information System (INIS)

    Zhang, Ziqi; Li, Wanyong; Zhang, Chengquan; Chen, Jiangping

    2017-01-01

    Highlights: • A model of vehicle climate control loads is proposed based on experiments. • Main climate control loads of the modeled vehicle are quantitatively analyzed. • Range reductions of the modeled vehicle under different conditions are simulated. - Abstract: A new model of electric vehicle climate control loads is provided in this paper. The mathematical formulations of the major climate control loads are developed, and the coefficients of the formulations are experimentally determined. Then, the detailed climate control loads are analyzed, and the New European Driving Cycle (NEDC) range reductions due to these loads are calculated under different conditions. It is found that in an electric vehicle, the total climate control loads vary with the vehicle speed, HVAC mode and blower level. The ventilation load is the largest climate control load, followed by the solar radiation load. These two add up to more than 80% of total climate control load in summer. The ventilation load accounts for 70.7–83.9% of total heating load under the winter condition. The climate control loads will cause a 17.2–37.1% reduction of NEDC range in summer, and a 17.1–54.1% reduction in winter, compared to the AC off condition. The heat pump system has an advantage in range extension. A heat pump system with an average heating COP of 1.7 will extend the range by 7.6–21.1% based on the simulation conditions.

  14. Multiplexed Predictive Control of a Large Commercial Turbofan Engine

    Science.gov (United States)

    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.

  15. Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

    Science.gov (United States)

    Barlow, Jonathan Spencer; Acosta, Diana Michelle; Phan, Minh Q.

    2010-01-01

    Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

  16. Quantized Predictive Control over Erasure Channels

    DEFF Research Database (Denmark)

    E. Quevedo, Daniel; Østergaard, Jan

    2009-01-01

    We study a control architecture for linear time-invariant plants which are affected by random disturbances. The distinguishing aspect of the situation at hand is that an unreliable data-rate limited network is placed between controller and the plant input. To achieve robustness with respect to i....

  17. Reducing prediction uncertainty of weather controlled systems

    NARCIS (Netherlands)

    Doeswijk, T.G.

    2007-01-01

    In closed agricultural systems the weather acts both as a disturbance and as a resource. By using weather forecasts in control strategies the effects of disturbances can be minimized whereas the resources can be utilized. In this situation weather forecast uncertainty and model based control are

  18. General movements in early infancy predict neuromotor development at 9 to 12 years of age

    NARCIS (Netherlands)

    Groen, SE; de Blecourt, ACE; Postema, K; Hadders-Algra, M

    2005-01-01

    Assessment of the quality of general movements (GMs) in early infancy is a powerful instrument to predict cerebral palsy (CP). The aim of the present study is to explore the value of GM assessment in predicting minor neurological dysfunction (MND) at 9 to 12 years of age. Two groups of infants were

  19. Predicting glycated hemoglobin levels in the non-diabetic general population

    DEFF Research Database (Denmark)

    Rauh, Simone P; Heymans, Martijn W; Koopman, Anitra D M

    2017-01-01

    AIMS/HYPOTHESIS: To develop a prediction model that can predict HbA1c levels after six years in the non-diabetic general population, including previously used readily available predictors. METHODS: Data from 5,762 initially non-diabetic subjects from three population-based cohorts (Hoorn Study, I...

  20. Fuzzy predictive filtering in nonlinear economic model predictive control for demand response

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    The performance of a model predictive controller (MPC) is highly correlated with the model's accuracy. This paper introduces an economic model predictive control (EMPC) scheme based on a nonlinear model, which uses a branch-and-bound tree search for solving the inherent non-convex optimization...

  1. A General Method for Designing Fractional Order PID Controller

    Directory of Open Access Journals (Sweden)

    Marzieh Safaei

    2013-01-01

    Full Text Available The idea of using fractional order calculus in control became apparent when this kind of calculus was accepted as a powerful tool in many applications. This resulted in a new generation of PID controller called fractional order PID Controller, named as Controller. controller is more flexible and provides a better response with larger stability region as compared with standard PID controller. This paper presents a simple and reliable method for finding the family of controllers. The required calculations are done in frequency domain based on frequency response of the system and the stability region is specified in the parameters space. This method can be used for time-delay systems and, more generally, for any system with no transfer function.

  2. Model Predictive Vibration Control Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Structures

    CERN Document Server

    Takács, Gergely

    2012-01-01

    Real-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: ·         the implementation of ...

  3. Model predictive control of a crude oil distillation column

    Directory of Open Access Journals (Sweden)

    Morten Hovd

    1999-04-01

    Full Text Available The project of designing and implementing model based predictive control on the vacuum distillation column at the Nynäshamn Refinery of Nynäs AB is described in this paper. The paper describes in detail the modeling for the model based control, covers the controller implementation, and documents the benefits gained from the model based controller.

  4. Model Predictive Control of Nonlinear Parameter Varying Systems via Receding Horizon Control Lyapunov Functions

    National Research Council Canada - National Science Library

    Sznaier, Mario

    2001-01-01

    .... In this chapter we propose a suboptimal regulator for nonlinear parameter varying, control affine systems based upon the combination of model predictive and control Lyapunov function techniques...

  5. Comparison Analysis of Model Predictive Controller with Classical PID Controller For pH Control Process

    Directory of Open Access Journals (Sweden)

    V. Balaji

    2016-12-01

    Full Text Available pH control plays a important role in any chemical plant and process industries. For the past four decades the classical PID controller has been occupied by the industries. Due to the faster computing   technology in the industry demands a tighter advanced control strategy. To fulfill the needs and requirements Model Predictive Control (MPC is the best among all the advanced control algorithms available in the present scenario. The study and analysis has been done for First Order plus Delay Time (FOPDT model controlled by Proportional Integral Derivative (PID and MPC using the Matlab software. This paper explores the capability of the MPC strategy, analyze and compare the control effects with conventional control strategy in pH control. A comparison results between the PID and MPC is plotted using the software. The results clearly show that MPC provide better performance than the classical controller.

  6. Dynamic optimization and robust explicit model predictive control of hydrogen storage tank

    KAUST Repository

    Panos, C.

    2010-09-01

    We present a general framework for the optimal design and control of a metal-hydride bed under hydrogen desorption operation. The framework features: (i) a detailed two-dimension dynamic process model, (ii) a design and operational dynamic optimization step, and (iii) an explicit/multi-parametric model predictive controller design step. For the controller design, a reduced order approximate model is obtained, based on which nominal and robust multi-parametric controllers are designed. © 2010 Elsevier Ltd.

  7. Predictive Control Based upon State Space Models

    Directory of Open Access Journals (Sweden)

    Jens G. Balchen

    1989-04-01

    Full Text Available Repetitive online computation of the control vector by solving the optimal control problem of a non-linear multivariable process with arbitrary performance indices is investigated. Two different methods are considered in the search for an optimal, parameterized control vector: Pontryagin's Maximum Principle and optimization by using the performance index and its gradient directly. Unfortunately, solving this optimization problem has turned out to be a rather time-consuming task which has resulted in a time delay that cannot be accepted when the actual process is exposed to rapidly-varying disturbances. However, an instantaneous feedback strategy operating in parallel with the original control aogorithm was found to be able to cope with this problem.

  8. Model Predictive Control with Constraints of a Wind Turbine

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Poulsen, Niels Kjølstad

    2007-01-01

    Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure...... an efficient control of the wind turbine over the entire range of wind speeds. Both onshore and floating offshore wind turbines are tested with the controllers....

  9. Wireless model predictive control: Application to water-level system

    Directory of Open Access Journals (Sweden)

    Ramdane Hedjar

    2016-04-01

    Full Text Available This article deals with wireless model predictive control of a water-level control system. The objective of the model predictive control algorithm is to constrain the control signal inside saturation limits and maintain the water level around the desired level. Linear modeling of any nonlinear plant leads to parameter uncertainties and non-modeled dynamics in the linearized mathematical model. These uncertainties induce a steady-state error in the output response of the water level. To eliminate this steady-state error and increase the robustness of the control algorithm, an integral action is included in the closed loop. To control the water-level system remotely, the communication between the controller and the process is performed using radio channel. To validate the proposed scheme, simulation and real-time implementation of the algorithm have been conducted, and the results show the effectiveness of wireless model predictive control with integral action.

  10. Applying Performance-Controlled Systems, Fuzzy Logic, and Fly-by-Wire Controls to General Aviation

    National Research Council Canada - National Science Library

    Beringer, Dennis

    2002-01-01

    A fuzzy-logic 'performance control' system, providing envelope protection and direct command of airspeed, vertical velocity, and turn rate, was evaluated in a reconfigurable general aviation simulator...

  11. Generalized H2 Control Synthesis for Periodic Systems

    DEFF Research Database (Denmark)

    Wisniewski, Rafal; Stoustrup, Jakob

    2001-01-01

    A control synthesis of periodic processes is addressed in this paper. A class of linear discrete time periodic systems with performance specified by the generalized $H_2$ operator norm, is considered. The paper proposes an LMI solution to this problem, the sufficient and necessary conditions for ...

  12. Mapping automotive like controls to a general aviation aircraft

    Science.gov (United States)

    Carvalho, Christopher G.

    The purpose of this thesis was to develop fly-by-wire control laws enabling a general aviation aircraft to be flown with automotive controls, i.e. a steering wheel and gas/brake pedals. There was a six speed shifter used to change the flight mode of the aircraft. This essentially allows the pilot to have control over different aspects of the flight profile such as climb/descend or cruise. A highway in the sky was used to aid in the navigation since it is not intuitive to people without flight experience how to navigate from the sky or when to climb and descend. Many believe that general aviation could become as widespread as the automobile. Every person could have a personal aircraft at their disposal and it would be as easy to operate as driving an automobile. The goal of this thesis is to fuse the ease of drivability of a car with flight of a small general aviation aircraft. A standard automotive control hardware setup coupled with variably autonomous control laws will allow new pilots to fly a plane as easily as driving a car. The idea is that new pilots will require very little training to become proficient with these controls. Pilots with little time to stay current can maintain their skills simply by driving a car which is typically a daily activity. A human factors study was conducted to determine the feasibility of the applied control techniques. Pilot performance metrics were developed to compare candidates with no aviation background and experienced pilots. After analyzing the relative performance between pilots and non-pilots, it has been determined that the control system is robust and easy to learn. Candidates with no aviation experience whatsoever can learn to fly an aircraft as safely and efficiently as someone with hundreds of hours of flight experience using these controls.

  13. Finite Control Set Model Predictive Control for Multiple Distributed Generators Microgrids

    Science.gov (United States)

    Babqi, Abdulrahman Jamal

    This dissertation proposes two control strategies for AC microgrids that consist of multiple distributed generators (DGs). The control strategies are valid for both grid-connected and islanded modes of operation. In general, microgrid can operate as a stand-alone system (i.e., islanded mode) or while it is connected to the utility grid (i.e., grid connected mode). To enhance the performance of a micrgorid, a sophisticated control scheme should be employed. The control strategies of microgrids can be divided into primary and secondary controls. The primary control regulates the output active and reactive powers of each DG in grid-connected mode as well as the output voltage and frequency of each DG in islanded mode. The secondary control is responsible for regulating the microgrid voltage and frequency in the islanded mode. Moreover, it provides power sharing schemes among the DGs. In other words, the secondary control specifies the set points (i.e. reference values) for the primary controllers. In this dissertation, Finite Control Set Model Predictive Control (FCS-MPC) was proposed for controlling microgrids. FCS-MPC was used as the primary controller to regulate the output power of each DG (in the grid-connected mode) or the voltage of the point of DG coupling (in the islanded mode of operation). In the grid-connected mode, Direct Power Model Predictive Control (DPMPC) was implemented to manage the power flow between each DG and the utility grid. In the islanded mode, Voltage Model Predictive Control (VMPC), as the primary control, and droop control, as the secondary control, were employed to control the output voltage of each DG and system frequency. The controller was equipped with a supplementary current limiting technique in order to limit the output current of each DG in abnormal incidents. The control approach also enabled smooth transition between the two modes. The performance of the control strategy was investigated and verified using PSCAD/EMTDC software

  14. Predictive control strategies for energy saving of hybrid electric vehicles based on traffic light information

    Directory of Open Access Journals (Sweden)

    Kaijiang YU

    2015-10-01

    Full Text Available As the conventional control method for hybrid electric vehicle doesn’t consider the effect of known traffic light information on the vehicle energy management, this paper proposes a model predictive control intelligent optimization strategies based on traffic light information for hybrid electric vehicles. By building the simplified model of the hybrid electric vehicle and adopting the continuation/generalized minimum residual method, the model prediction problem is solved. The simulation is conducted by using MATLAB/Simulink platform. The simulation results show the effectiveness of the proposed model of the traffic light information, and that the proposed model predictive control method can improve fuel economy and the real-time control performance significantly. The research conclusions show that the proposed control strategy can achieve optimal control of the vehicle trajectory, significantly improving fuel economy of the vehicle, and meet the system requirements for the real-time optimal control.

  15. Fuzzy model predictive control algorithm applied in nuclear power plant

    International Nuclear Information System (INIS)

    Zuheir, Ahmad

    2006-01-01

    The aim of this paper is to design a predictive controller based on a fuzzy model. The Takagi-Sugeno fuzzy model with an Adaptive B-splines neuro-fuzzy implementation is used and incorporated as a predictor in a predictive controller. An optimization approach with a simplified gradient technique is used to calculate predictions of the future control actions. In this approach, adaptation of the fuzzy model using dynamic process information is carried out to build the predictive controller. The easy description of the fuzzy model and the easy computation of the gradient sector during the optimization procedure are the main advantages of the computation algorithm. The algorithm is applied to the control of a U-tube steam generation unit (UTSG) used for electricity generation. (author)

  16. Clinical psychology in general practice: a controlled trial evaluation

    Science.gov (United States)

    Earll, Louise; Kincey, John

    1982-01-01

    A controlled trial study is described in which 50 consecutive potential referrals for psychological treatment from one general practice were randomly allocated either to behavioural treatment or no-treatment conditions. Treatment-group patients received treatment from a clinical psychologist working within the practice; the control-group patients continued to be managed by their general practitioner. The patients' use of NHS resources was assessed during the treatment period (or its equivalent for the control group) and at a follow-up comparison point, when the patients' subjective ratings of their progress were also obtained. Between referral and the end of treatment the treated group received significantly less psychotropic medication than the control group. This difference was not, however, maintained at the longer-term follow-up. No differences in general practice consultation rates, in the subjective ratings of psychological distress, in control orientation or life satisfaction were found between the two groups, but the level of patient satisfaction was high. Implications for the design of future studies and for psychological health care delivery systems are discussed. PMID:7086742

  17. A General Theory of Markovian Time Inconsistent Stochastic Control Problems

    DEFF Research Database (Denmark)

    Björk, Tomas; Murgochi, Agatha

    We develop a theory for stochastic control problems which, in various ways, are time inconsistent in the sense that they do not admit a Bellman optimality principle. We attach these problems by viewing them within a game theoretic framework, and we look for Nash subgame perfect equilibrium points....... For a general controlled Markov process and a fairly general objective functional we derive an extension of the standard Hamilton-Jacobi-Bellman equation, in the form of a system of on-linear equations, for the determination for the equilibrium strategy as well as the equilibrium value function. All known...... examples of time inconsistency in the literature are easily seen to be special cases of the present theory. We also prove that for every time inconsistent problem, there exists an associated time consistent problem such that the optimal control and the optimal value function for the consistent problem...

  18. Model predictive control for wind power gradients

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp

    2015-01-01

    We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...

  19. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    In this thesis, we consider control strategies for flexible distributed energy resources in the future intelligent energy system – the Smart Grid. The energy system is a large-scale complex network with many actors and objectives in different hierarchical layers. Specifically the power system must...... significantly. A Smart Grid calls for flexible consumers that can adjust their consumption based on the amount of green energy in the grid. This requires coordination through new large-scale control and optimization algorithms. Trading of flexibility is key to drive power consumption in a sustainable direction....... In Denmark, we expect that distributed energy resources such as heat pumps, and batteries in electric vehicles will mobilize part of the needed flexibility. Our primary objectives in the thesis were threefold: 1.Simulate the components in the power system based on simple models from literature (e.g. heat...

  20. Electric vehicle charge planning using Economic Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels K.; Madsen, Henrik

    2012-01-01

    Economic Model Predictive Control (MPC) is very well suited for controlling smart energy systems since electricity price and demand forecasts are easily integrated in the controller. Electric vehicles (EVs) are expected to play a large role in the future Smart Grid. They are expected to provide...

  1. Supervisory Model Predictive Control of the Heat Integrated Distillation Column

    DEFF Research Database (Denmark)

    Meyer, Kristian; Bisgaard, Thomas; Huusom, Jakob Kjøbsted

    2017-01-01

    This paper benchmarks a centralized control system based on model predictive control for the operation of the heat integrated distillation column (HIDiC) against a fully decentralized control system using the most complete column model currently available in the literature. The centralized contro...

  2. Stress before extinction learning enhances and generalizes extinction memory in a predictive learning task.

    Science.gov (United States)

    Meir Drexler, Shira; Hamacher-Dang, Tanja C; Wolf, Oliver T

    2017-05-01

    In extinction learning, the individual learns that a previously acquired association (e.g. between a threat and its predictor) is no longer valid. This learning is the principle underlying many cognitive-behavioral psychotherapeutic treatments, e.g. 'exposure therapy'. However, extinction is often highly-context dependent, leading to renewal (relapse of extinguished conditioned response following context change). We have previously shown that post-extinction stress leads to a more context-dependent extinction memory in a predictive learning task. Yet as stress prior to learning can impair the integration of contextual cues, here we aim to create a more generalized extinction memory by inducing stress prior to extinction. Forty-nine men and women learned the associations between stimuli and outcomes in a predictive learning task (day 1), extinguished them shortly after an exposure to a stress/control condition (day 2), and were tested for renewal (day 3). No group differences were seen in acquisition and extinction learning, and a renewal effect was present in both groups. However, the groups differed in the strength and context-dependency of the extinction memory. Compared to the control group, the stress group showed an overall reduced recovery of responding to the extinguished stimuli, in particular in the acquisition context. These results, together with our previous findings, demonstrate that the effects of stress exposure on extinction memory depend on its timing. While post-extinction stress makes the memory more context-bound, pre-extinction stress strengthens its consolidation for the acquisition context as well, making it potentially more resistant to relapse. These results have implications for the use of glucocorticoids as extinction-enhancers in exposure therapy. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Generalized space vector control for current source inverters and rectifiers

    Directory of Open Access Journals (Sweden)

    Roseline J. Anitha

    2016-06-01

    Full Text Available Current source inverters (CSI is one of the widely used converter topology in medium voltage drive applications due to its simplicity, motor friendly waveforms and reliable short circuit protection. The current source inverters are usually fed by controlled current source rectifiers (CSR with a large inductor to provide a constant supply current. A generalized control applicable for both CSI and CSR and their extension namely current source multilevel inverters (CSMLI are dealt in this paper. As space vector pulse width modulation (SVPWM features the advantages of flexible control, faster dynamic response, better DC utilization and easy digital implementation it is considered for this work. This paper generalizes SVPWM that could be applied for CSI, CSR and CSMLI. The intense computation involved in framing a generalized space vector control are discussed in detail. The algorithm includes determination of band, region, subregions and vectors. The algorithm is validated by simulation using MATLAB /SIMULINK for CSR 5, 7, 13 level CSMLI and for CSR fed CSI.

  4. Model Predictive Control for an Industrial SAG Mill

    DEFF Research Database (Denmark)

    Ohan, Valeriu; Steinke, Florian; Metzger, Michael

    2012-01-01

    We discuss Model Predictive Control (MPC) based on ARX models and a simple lower order disturbance model. The advantage of this MPC formulation is that it has few tuning parameters and is based on an ARX prediction model that can readily be identied using standard technologies from system identic...

  5. Rate-Based Model Predictive Control of Turbofan Engine Clearance

    Science.gov (United States)

    DeCastro, Jonathan A.

    2006-01-01

    An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

  6. Model Predictive Control for Integrating Traffic Control Measures

    NARCIS (Netherlands)

    Hegyi, A.

    2004-01-01

    Dynamic traffic control measures, such as ramp metering and dynamic speed limits, can be used to better utilize the available road capacity. Due to the increasing traffic volumes and the increasing number of traffic jams the interaction between the control measures has increased such that local

  7. Confusion Control in Generalized Petri Nets Using Synchronized Events

    Directory of Open Access Journals (Sweden)

    Xiaoliang Chen

    2015-01-01

    Full Text Available The loss of conflicting information in a Petri net (PN, usually called confusions, leads to incomplete and faulty system behavior. Confusions, as an unfortunate phenomenon in discrete event systems modeled with Petri nets, are caused by the frequent interlacement of conflicting and concurrent transitions. In this paper, confusions are defined and investigated in bounded generalized PNs. A reasonable control strategy for conflicts and confusions in a PN is formulated by proposing elementary conflict resolution sequences (ECRSs and a class of local synchronized Petri nets (LSPNs. Two control algorithms are reported to control the appeared confusions by generating a series of external events. Finally, an example of confusion analysis and control in an automated manufacturing system is presented.

  8. Selection of References in Wind Turbine Model Predictive Control Design

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Hovgaard, Tobias

    2015-01-01

    a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...

  9. A multicontroller structure for teaching and designing predictive control strategies

    International Nuclear Information System (INIS)

    Hodouin, D.; Desbiens, A.

    1999-01-01

    The paper deals with the unification of the existing linear control algorithms in order to facilitate their transfer to the engineering students and to industry's engineers. The resulting control algorithm is the Global Predictive Control (GlobPC), which is now taught at the graduate and continuing education levels. GlobPC is based on an internal model framework where three independent control criteria are minimized: one for tracking, one for regulation and one for feedforward. This structure allows to obtain desired tracking, regulation and feedforward behaviors in an optimal way while keeping them perfectly separated. It also cleanly separates the deterministic and stochastic predictions of the process model output. (author)

  10. Asthma control in general practice -- GP and patient perspectives compared.

    Science.gov (United States)

    Henderson, Joan; Hancock, Kerry L; Armour, Carol; Harrison, Christopher; Miller, Graeme

    2013-10-01

    How general practitioners (GPs) and patients perceive asthma control, and concordance between these perceptions, may influence asthma management and medication adherence. The aims of this study were to determine asthma prevalence in adult patients, measure patient asthma control and the correlation between GP and patient perceptions of asthma control or impact. A Supplementary Analysis of Nominated Data (SAND) sub-study of the Bettering the Evaluation and Care of Health (BEACH) program surveyed 2563 patients from 103 GPs. Asthma control was measured using the Asthma Control Questionnaire 5-item version (ACQ-5), and medication adherence by patient self-report. Survey procedures in SAS software and Pearson's correlation statistics were used. Asthma prevalence was 12.7% (95% confidence interval: 10.9-14.5), with good correlation between GP and patient perceptions of asthma control/impact, and with raw ACQ-5 scores. Grouped ACQ-5 scores showed higher levels of uncontrolled asthma. Medication adherence was sub-optimal. The ACQ-5 questions are useful for assessing asthma control, for prompting medication reviews, and for reinforcing benefits of medication compliance to improve long-term asthma control.

  11. Higher-Order Generalized Invexity in Control Problems

    Directory of Open Access Journals (Sweden)

    S. K. Padhan

    2011-01-01

    Full Text Available We introduce a higher-order duality (Mangasarian type and Mond-Weir type for the control problem. Under the higher-order generalized invexity assumptions on the functions that compose the primal problems, higher-order duality results (weak duality, strong duality, and converse duality are derived for these pair of problems. Also, we establish few examples in support of our investigation.

  12. Generalized perturbation theory error control within PWR core-loading pattern optimization

    International Nuclear Information System (INIS)

    Imbriani, J.S.; Turinsky, P.J.; Kropaczek, D.J.

    1995-01-01

    The fuel management optimization code FORMOSA-P has been developed to determine the family of near-optimum loading patterns for PWR reactors. The code couples the optimization technique of simulated annealing (SA) with a generalized perturbation theory (GPT) model for evaluating core physics characteristics. To ensure the accuracy of the GPT predictions, as well as to maximize the efficient of the SA search, a GPT error control method has been developed

  13. Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

    DEFF Research Database (Denmark)

    Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon

    2008-01-01

    This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... implementation consisting of a distributed PI controller structure, both in terms of minimising the overall cost but also in terms of the ability to minimise deviation, which is the classical objective....

  14. Multiobjective model predictive control of an industrial laundry

    OpenAIRE

    Peitz, S.; Gräler, M.; Henke, C.; Hessel-von Molo, M.; Dellnitz, M.; Trächtler, A.

    2016-01-01

    In a wide range of applications, it is desirable to optimally control a system with respect to concurrent, potentially competing goals. This gives rise to a multiobjective optimal control problem where, instead of computing a single optimal solution, the set of optimal compromises, the so-called Pareto set, has to be approximated. When it is not possible to compute the entire control trajectory in advance, for instance due to uncertainties or unforeseeable events, model predictive control met...

  15. Gravitational redshift of galaxies in clusters as predicted by general relativity.

    Science.gov (United States)

    Wojtak, Radosław; Hansen, Steen H; Hjorth, Jens

    2011-09-28

    The theoretical framework of cosmology is mainly defined by gravity, of which general relativity is the current model. Recent tests of general relativity within the Lambda Cold Dark Matter (ΛCDM) model have found a concordance between predictions and the observations of the growth rate and clustering of the cosmic web. General relativity has not hitherto been tested on cosmological scales independently of the assumptions of the ΛCDM model. Here we report an observation of the gravitational redshift of light coming from galaxies in clusters at the 99 per cent confidence level, based on archival data. Our measurement agrees with the predictions of general relativity and its modification created to explain cosmic acceleration without the need for dark energy (the f(R) theory), but is inconsistent with alternative models designed to avoid the presence of dark matter. © 2011 Macmillan Publishers Limited. All rights reserved

  16. Relativistic theory of gravitation and nonuniqueness of the predictions of general relativity theory

    International Nuclear Information System (INIS)

    Logunov, A.A.; Loskutov, Yu.M.

    1986-01-01

    It is shown that while the predictions of relativistic theory of gravitation (RTG) for the gravitational effects are unique and consistent with the experimental data available, the relevant predictions of general relativity theory are not unique. Therewith the above nonuniqueness manifests itself in some effects in the first order in the gravitational interaction constant in others in the second one. The absence in GRT of the energy-momentum and angular momentum conservation laws for the matter and gravitational field taken together and its inapplicability to give uniquely determined predictions for the gravitational phenomena compel to reject GRT as a physical theory

  17. Spatially explicit models, generalized reproduction numbers and the prediction of patterns of waterborne disease

    Science.gov (United States)

    Rinaldo, A.; Gatto, M.; Mari, L.; Casagrandi, R.; Righetto, L.; Bertuzzo, E.; Rodriguez-Iturbe, I.

    2012-12-01

    Metacommunity and individual-based theoretical models are studied in the context of the spreading of infections of water-borne diseases along the ecological corridors defined by river basins and networks of human mobility. The overarching claim is that mathematical models can indeed provide predictive insight into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. To support the claim, we examine the ex-post reliability of published predictions of the 2010-2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. For each modeled epidemic trajectory, it is assessed how well predictions reproduced the observed spatial and temporal features of the outbreak to date. The impact of different approaches is considered to the modeling of the spatial spread of V. cholera, the mechanics of cholera transmission and in accounting for the dynamics of susceptible and infected individuals within different local human communities. A generalized model for Haitian epidemic cholera and the related uncertainty is thus constructed and applied to the year-long dataset of reported cases now available. Specific emphasis will be dedicated to models of human mobility, a fundamental infection mechanism. Lessons learned and open issues are discussed and placed in perspective, supporting the conclusion that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control. Although explicit spatial modeling is made routinely possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is

  18. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

    Soltani, Mohsen N.; Sichani, Mahdi T.; Mirzaei, Mahmood

    2014-01-01

    by forcing this condition. In the paper the theoretical framework for this principal is shown. The optimal controller requires information of the sea state for infinite horizon which is not applicable. Model Predictive Controllers (MPC) can have finite horizon which crosses out this requirement....... This approach is then taken into account and an MPC controller is designed for a model wave energy converter and implemented on a numerical example. Further, the power outtake of this controller is compared to the optimal controller as an indicator of the performance of the designed controller....

  19. Economic Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    Model Predictive Control (MPC) can be used to control the energy distribution in a Smart Grid with a high share of stochastic energy production from renewable energy sources like wind. Heat pumps for heating residential buildings can exploit the slow heat dynamics of a building to store heat...

  20. Sparsely-Packetized Predictive Control by Orthogonal Matching Pursuit

    DEFF Research Database (Denmark)

    Nagahara, Masaaki; Quevedo, Daniel; Østergaard, Jan

    2012-01-01

    We study packetized predictive control, known to be robust against packet dropouts in networked systems. To obtain sparse packets for rate-limited networks, we design control packets via an ℓ0 optimization, which can be eectively solved by orthogonal matching pursuit. Our formulation ensures asym...

  1. Predictive control, with restrictions for the climate of a greenhouse

    International Nuclear Information System (INIS)

    Pinon, Sandra; Pena, Miguel; Kuchen, Benjamin

    2002-01-01

    A proposal for controlling nonlinear systems under constraints is presented. a combination of model predictive control and feedback linearization is used. An alternative that uses extended kalman filter as non-measured variable estimator is applied for performing the constrained optimization. Finally, an observability analysis is done in closed loop in order to demonstrate observer convergence

  2. Identification and predictive control of a multistage evaporator

    NARCIS (Netherlands)

    Atuonwu, J.C.; Cao, Y.; Rangaiah, G.P.; Tadé, M.O.

    2010-01-01

    A recurrent neural network-based nonlinear model predictive control (NMPC) scheme in parallel with PI control loops is developed for a simulation model of an industrial-scale five-stage evaporator. Input–output data from system identification experiments are used in training the network using the

  3. Model Predictive Control for Offset-Free Reference Tracking

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav

    2016-01-01

    Roč. 5, č. 1 (2016), s. 8-13 ISSN 1805-3386 Institutional support: RVO:67985556 Keywords : offset-free reference tracking * predictive control * ARX model * state-space model * multi-input multi-output system * robotic system * mechatronic system Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/2016/AS/belda-0458355.pdf

  4. Neural networks for predictive control of the mechanism of ...

    African Journals Online (AJOL)

    In this paper, we are interested in the study of the control of orientation of a wind turbine like means of optimization of his output/input ratio (efficiency). The approach suggested is based on the neural predictive control which is justified by the randomness of the wind on the one hand, and on the other hand by the capacity of ...

  5. Dual arm generalized compliant motion with shared control

    Science.gov (United States)

    Backes, Paul G.

    1993-03-01

    A multiple arm generalized compliant motion robot control system governs dual multi-joint robot arms handling an object with both of the arms in accordance with input parameters governing plural respective behaviors to be exhibited by the robot in respective behavior spaces simultaneously. A move-squeeze decomposition processor computes actual move and squeeze decomposition forces based upon current robot force sensor outputs. A compliant motion processor transforms plural object position perturbations of the plural behaviors from the respective behavior spaces to a common space and computes a relative transformation to a behavior-commanded object position in accordance with the object position perturbations of the plural behaviors. A kinematics processor updates a transformation to a current commanded object position based upon the relative transformation to the behavior-commanded object position. A multiple arm squeeze control processor computes from appropriate squeeze force input parameters and from actual squeeze forces for each of the arms, a squeeze control position perturbation for each of the arms, to provide squeeze control. An inverse kinematics processor computes from the commanded object position transformation and from the squeeze control position perturbation, new robot joint angles, and controls respective joints of the robot arms in accordance with the new robot joint angles.

  6. Dual-arm generalized compliant motion with shared control

    Science.gov (United States)

    Backes, Paul G.

    1993-03-01

    A multiple arm generalized compliant motion robot control system governs dual multi-joint robot arms handling an object with both of the arms in accordance with input parameters governing plural respective behaviors to be exhibited by the robot in respective behavior spaces simultaneously. A move-squeeze decomposition processor computes actual move and squeeze decomposition forces based upon current robot force sensor outputs. A compliant motion processor transforms plural object position perturbations of the plural behaviors from the respective behavior spaces to a common space and computes a relative transformation to a behavior-commanded object position in accordance with the object position perturbations of the plural behaviors. A kinematics processor updates a transformation to a current commanded object position based upon the relative transformation to the behavior-commanded object position. A multiple arm squeeze control processor computes from appropriate squeeze force input parameters and from actual squeeze forces for each of the arms, a squeeze control position perturbation for each of the arms, to provide squeeze control. An inverse kinematics processor computes from the commanded object position transformation and from the squeeze control position perturbation, new robot joint angles, and controls respective joints of the robot arms in accordance with the new robot joint angles.

  7. Weighted Multimodel Predictive Function Control for Automatic Train Operation System

    Directory of Open Access Journals (Sweden)

    Shuhuan Wen

    2014-01-01

    Full Text Available Train operation is a complex nonlinear process; it is difficult to establish accurate mathematical model. In this paper, we design ATO speed controller based on the input and output data of the train operation. The method combines multimodeling with predictive functional control according to complicated nonlinear characteristics of the train operation. Firstly, we cluster the data sample by using fuzzy-c means algorithm. Secondly, we identify parameter of cluster model by using recursive least square algorithm with forgetting factor and then establish the local set of models of the process of train operation. Then at each sample time, we can obtain the global predictive model about the system based on the weighted indicators by designing a kind of weighting algorithm with error compensation. Thus, the predictive functional controller is designed to control the speed of the train. Finally, the simulation results demonstrate the effectiveness of the proposed algorithm.

  8. Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

    Science.gov (United States)

    Mercer, Joey; Hunt-Espinosa, Sarah; Bienert, Nancy; Laraway, Sean

    2016-01-01

    A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

  9. Machine learning and predictive data analytics enabling metrology and process control in IC fabrication

    Science.gov (United States)

    Rana, Narender; Zhang, Yunlin; Wall, Donald; Dirahoui, Bachir; Bailey, Todd C.

    2015-03-01

    Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.

  10. Bayesian prediction of spatial count data using generalized linear mixed models

    DEFF Research Database (Denmark)

    Christensen, Ole Fredslund; Waagepetersen, Rasmus Plenge

    2002-01-01

    Spatial weed count data are modeled and predicted using a generalized linear mixed model combined with a Bayesian approach and Markov chain Monte Carlo. Informative priors for a data set with sparse sampling are elicited using a previously collected data set with extensive sampling. Furthermore, ...

  11. Predictive value of the official cancer alarm symptoms in general practice

    DEFF Research Database (Denmark)

    Krasnik Huggenberger, Ivan; Andersen, John Sahl

    2015-01-01

    Introduction: The objective of this study was to investigate the evidence for positive predictive value (PPV) of alarm symptoms and combinations of symptoms for colorectal cancer, breast cancer, prostate cancer and lung cancer in general practice. Methods: This study is based on a literature search...

  12. Bayesian prediction of spatial count data using generalized linear mixed models

    DEFF Research Database (Denmark)

    Christensen, Ole Fredslund; Waagepetersen, Rasmus Plenge

    2002-01-01

    Spatial weed count data are modeled and predicted using a generalized linear mixed model combined with a Bayesian approach and Markov chain Monte Carlo. Informative priors for a data set with sparse sampling are elicited using a previously collected data set with extensive sampling. Furthermore, we...

  13. Offset Free Tracking Predictive Control Based on Dynamic PLS Framework

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2017-10-01

    Full Text Available This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method.

  14. Model Predictive Control of a Wave Energy Converter

    DEFF Research Database (Denmark)

    Andersen, Palle; Pedersen, Tom Søndergård; Nielsen, Kirsten Mølgaard

    2015-01-01

    In this paper reactive control and Model Predictive Control (MPC) for a Wave Energy Converter (WEC) are compared. The analysis is based on a WEC from Wave Star A/S designed as a point absorber. The model predictive controller uses wave models based on the dominating sea states combined with a model......'s are designed for each sea state using a model assuming a linear loss torque. The mean power results from two controllers are compared using both loss models. Simulation results show that MPC can outperform a reactive controller if a good model of the conversion losses is available....... connecting undisturbed wave sequences to sequences of torque. Losses in the conversion from mechanical to electrical power are taken into account in two ways. Conventional reactive controllers are tuned for each sea state with the assumption that the converter has the same efficiency back and forth. MPC...

  15. Online prediction and control in nonlinear stochastic systems

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov

    2002-01-01

    as well as non-linear models and advances a class of non-linear models which are particularly useful in the context of on-line estimation. The second part considers various aspects of using predictive controllers in connection with control of supply temperature in district heating systems { a class....... In the following chapters the presented papers are brought into their corresponding context with respect to optimal control of supply temperature in district heating systems and prediction of power production from wind turbines located in a given geographical area. The papers A to C focus primarily on issues...... derived using a physical relation and considers the various issues arising when the two controllers are applied in district heating systems with the purpose of controlling the supply temperature. The proposed controllers are mplemented in a software system - PRESS - and installed at the district heating...

  16. Range-Space Predictive Control for Optimal Robot Motion

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Böhm, Josef

    2008-01-01

    Roč. 1, č. 1 (2008), s. 1-7 ISSN 1998-0140 R&D Projects: GA ČR GP102/06/P275 Institutional research plan: CEZ:AV0Z10750506 Keywords : Accurate manipulation * Industrial robot ics * Predictive control * Range-space control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0305644.pdf

  17. Recent Advances in Explicit Multiparametric Nonlinear Model Predictive Control

    KAUST Repository

    Domínguez, Luis F.

    2011-01-19

    In this paper we present recent advances in multiparametric nonlinear programming (mp-NLP) algorithms for explicit nonlinear model predictive control (mp-NMPC). Three mp-NLP algorithms for NMPC are discussed, based on which novel mp-NMPC controllers are derived. The performance of the explicit controllers are then tested and compared in a simulation example involving the operation of a continuous stirred-tank reactor (CSTR). © 2010 American Chemical Society.

  18. Model Predictive Control of Three Phase Inverter for PV Systems

    OpenAIRE

    Irtaza M. Syed; Kaamran Raahemifar

    2015-01-01

    This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize the TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of a boost converter (BC), maximum power point tracking (MPPT) control, and a three-leg voltage source inverter (VSI). The operational model of ...

  19. Model Predictive Control for a Small Scale Unmanned Helicopter

    Directory of Open Access Journals (Sweden)

    Jianfu Du

    2008-11-01

    Full Text Available Kinematical and dynamical equations of a small scale unmanned helicoper are presented in the paper. Based on these equations a model predictive control (MPC method is proposed for controlling the helicopter. This novel method allows the direct accounting for the existing time delays which are used to model the dynamics of actuators and aerodynamics of the main rotor. Also the limits of the actuators are taken into the considerations during the controller design. The proposed control algorithm was verified in real flight experiments where good perfomance was shown in postion control mode.

  20. Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm...... for solving the nonconvex optimization problem is proposed in this paper. A simulation using the nonlinear model-based controller to control the temperature levels of an intelligent office building (PowerFlexHouse) is addressed. Its performance is compared with a linear model-based controller. The nonlinear...

  1. Nonlinear model predictive control of managed pressure drilling.

    Science.gov (United States)

    Nandan, Anirudh; Imtiaz, Syed

    2017-07-01

    A new design of nonlinear model predictive controller (NMPC) is proposed for managed pressure drilling (MPD) system. The NMPC is based on output feedback control architecture and employs offset-free formulation proposed in [1]. NMPC uses active set method for computing control inputs. The controller implements an automatic switching from constant bottom hole pressure (CBHP) regulation to flow control mode in the event of a reservoir kick. In the flow control mode the controller automatically raises the bottom hole pressure setpoint, and thereby keeps the reservoir fluid flow to the surface within a tunable threshold. This is achieved by exploiting constraint handling capability of NMPC. In addition to kick mitigation the controller demonstrated good performance in containing the bottom hole pressure (BHP) during the pipe connection sequence. The controller also delivered satisfactory performance in the presence of measurement noise and uncertainty in the system. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Advanced control room evaluation: General approach and rationale

    International Nuclear Information System (INIS)

    O'Hara, J.M.; Wachtel, J.

    1991-01-01

    Advanced control rooms (ACRs) for future nuclear power plants (NPPs) are being designed utilizing computer-based technologies. The US Nuclear Regulatory Commission reviews the human engineering aspects of such control rooms to ensure that they are designed to good human factors engineering principles and that operator performance and reliability are appropriately supported in order to protect public health and safety. This paper describes the rationale and general approach to the development of a human factors review guideline for ACRs. The factors influencing the guideline development are discussed, including the review environment, the types of advanced technologies being addressed, the human factors issues associated with advanced technology, and the current state-of-the-art of human factors guidelines for advanced human-system interfaces (HSIs). The proposed approach to ACR review would track the design and implementation process through the application of review guidelines reflecting four review modules: planning, design process analysis, human factors engineering review, and dynamic performance evaluation. 21 refs

  3. Enhanced pid vs model predictive control applied to bldc motor

    Science.gov (United States)

    Gaya, M. S.; Muhammad, Auwal; Aliyu Abdulkadir, Rabiu; Salim, S. N. S.; Madugu, I. S.; Tijjani, Aminu; Aminu Yusuf, Lukman; Dauda Umar, Ibrahim; Khairi, M. T. M.

    2018-01-01

    BrushLess Direct Current (BLDC) motor is a multivariable and highly complex nonlinear system. Variation of internal parameter values with environment or reference signal increases the difficulty in controlling the BLDC effectively. Advanced control strategies (like model predictive control) often have to be integrated to satisfy the control desires. Enhancing or proper tuning of a conventional algorithm results in achieving the desired performance. This paper presents a performance comparison of Enhanced PID and Model Predictive Control (MPC) applied to brushless direct current motor. The simulation results demonstrated that the PSO-PID is slightly better than the PID and MPC in tracking the trajectory of the reference signal. The proposed scheme could be useful algorithms for the system.

  4. Proposal of computation chart for general use for diffusion prediction of discharged warm water

    International Nuclear Information System (INIS)

    Wada, Akira; Kadoyu, Masatake

    1976-01-01

    The authors have developed the unique simulation analysis method using the numerical models for the prediction of discharged warm water diffusion. At the present stage, the method is adopted for the precise analysis computation in order to make the prediction of the diffusion of discharged warm water at each survey point, but instead of this method, it is strongly requested that some simple and easy prediction methods should be established. For the purpose of meeting this demand, in this report, the computation chart for general use is given to predict simply the diffusion range of discharged warm water, after classifying the semi-infinite sea region into several flow patterns according to the sea conditions and conducting the systematic simulation analysis with the numerical model of each pattern, respectively. (1) Establishment of the computation conditions: The special sea region was picked up as the area to be investigated, which is semi-infinite facing the outer sea and along the rectilineal coast line from many sea regions surrounding Japan, and from the viewpoint of the flow and the diffusion characteristics, the sea region was classified into three patterns. 51 cases in total various parameters were obtained, and finally the simulation analysis was performed. (2) Drawing up the general use chart: 28 sheets of the computation chart for general use were drawn, which are available for computing the approximate temperature rise caused by the discharged warm water diffusion. The example of Anegasaki Thermal Power Station is given. (Kako, I.)

  5. Prediction-Based Control for Nonlinear Systems with Input Delay

    Directory of Open Access Journals (Sweden)

    I. Estrada-Sánchez

    2017-01-01

    Full Text Available This work has two primary objectives. First, it presents a state prediction strategy for a class of nonlinear Lipschitz systems subject to constant time delay in the input signal. As a result of a suitable change of variable, the state predictor asymptotically provides the value of the state τ units of time ahead. Second, it proposes a solution to the stabilization and trajectory tracking problems for the considered class of systems using predicted states. The predictor-controller convergence is proved by considering a complete Lyapunov functional. The proposed predictor-based controller strategy is evaluated using numerical simulations.

  6. Exponential stability for formation control systems with generalized controllers: A unified approach

    NARCIS (Netherlands)

    Sun, Zhiyong; Mou, Shaoshuai; Anderson, Brian D.O.; Cao, Ming

    2016-01-01

    This paper discusses generalized controllers for distance-based rigid formation shape stabilization and aims to provide a unified approach for the convergence analysis. We consider two types of formation control systems according to different characterizations of target formations: minimally rigid

  7. Predicting Children's Reading and Mathematics Achievement from Early Quantitative Knowledge and Domain-General Cognitive Abilities

    Science.gov (United States)

    Chu, Felicia W.; vanMarle, Kristy; Geary, David C.

    2016-01-01

    One hundred children (44 boys) participated in a 3-year longitudinal study of the development of basic quantitative competencies and the relation between these competencies and later mathematics and reading achievement. The children's preliteracy knowledge, intelligence, executive functions, and parental educational background were also assessed. The quantitative tasks assessed a broad range of symbolic and nonsymbolic knowledge and were administered four times across 2 years of preschool. Mathematics achievement was assessed at the end of each of 2 years of preschool, and mathematics and word reading achievement were assessed at the end of kindergarten. Our goals were to determine how domain-general abilities contribute to growth in children's quantitative knowledge and to determine how domain-general and domain-specific abilities contribute to children's preschool mathematics achievement and kindergarten mathematics and reading achievement. We first identified four core quantitative competencies (e.g., knowledge of the cardinal value of number words) that predict later mathematics achievement. The domain-general abilities were then used to predict growth in these competencies across 2 years of preschool, and the combination of domain-general abilities, preliteracy skills, and core quantitative competencies were used to predict mathematics achievement across preschool and mathematics and word reading achievement at the end of kindergarten. Both intelligence and executive functions predicted growth in the four quantitative competencies, especially across the first year of preschool. A combination of domain-general and domain-specific competencies predicted preschoolers' mathematics achievement, with a trend for domain-specific skills to be more strongly related to achievement at the beginning of preschool than at the end of preschool. Preschool preliteracy skills, sensitivity to the relative quantities of collections of objects, and cardinal knowledge predicted

  8. REALIGNED MODEL PREDICTIVE CONTROL OF A PROPYLENE DISTILLATION COLUMN

    Directory of Open Access Journals (Sweden)

    A. I. Hinojosa

    Full Text Available Abstract In the process industry, advanced controllers usually aim at an economic objective, which usually requires closed-loop stability and constraints satisfaction. In this paper, the application of a MPC in the optimization structure of an industrial Propylene/Propane (PP splitter is tested with a controller based on a state space model, which is suitable for heavily disturbed environments. The simulation platform is based on the integration of the commercial dynamic simulator Dynsim® and the rigorous steady-state optimizer ROMeo® with the real-time facilities of Matlab. The predictive controller is the Infinite Horizon Model Predictive Control (IHMPC, based on a state-space model that that does not require the use of a state observer because the non-minimum state is built with the past inputs and outputs. The controller considers the existence of zone control of the outputs and optimizing targets for the inputs. We verify that the controller is efficient to control the propylene distillation system in a disturbed scenario when compared with a conventional controller based on a state observer. The simulation results show a good performance in terms of stability of the controller and rejection of large disturbances in the composition of the feed of the propylene distillation column.

  9. Real-time feedback control of computer networks based on predicted state estimation

    Directory of Open Access Journals (Sweden)

    N. U. Ahmed

    2005-01-01

    a new control law which predicts the traffic in advance and exercises control based on the predicted traffic. We demonstrate through simulation experiments that the predictive feedback control law substantially improves the system performance.

  10. Nonlinear Model Predictive Control with Constraint Satisfactions for a Quadcopter

    Science.gov (United States)

    Wang, Ye; Ramirez-Jaime, Andres; Xu, Feng; Puig, Vicenç

    2017-01-01

    This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the effectiveness of the proposed strategy.

  11. Use of a Machine-learning Method for Predicting Highly Cited Articles Within General Radiology Journals.

    Science.gov (United States)

    Rosenkrantz, Andrew B; Doshi, Ankur M; Ginocchio, Luke A; Aphinyanaphongs, Yindalon

    2016-12-01

    This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article features. We downloaded from PubMed the title, abstract, and medical subject heading terms for 10,065 articles published in 25 general radiology journals in 2012 and 2013. Three machine-learning models were applied to predict the top 10% of included articles in terms of the number of citations to the article in 2014 (reflecting the 2-year time window in conventional impact factor calculations). The model having the highest area under the curve was selected to derive a list of article features (words) predicting high citation volume, which was iteratively reduced to identify the smallest possible core feature list maintaining predictive power. Overall themes were qualitatively assigned to the core features. The regularized logistic regression (Bayesian binary regression) model had highest performance, achieving an area under the curve of 0.814 in predicting articles in the top 10% of citation volume. We reduced the initial 14,083 features to 210 features that maintain predictivity. These features corresponded with topics relating to various imaging techniques (eg, diffusion-weighted magnetic resonance imaging, hyperpolarized magnetic resonance imaging, dual-energy computed tomography, computed tomography reconstruction algorithms, tomosynthesis, elastography, and computer-aided diagnosis), particular pathologies (prostate cancer; thyroid nodules; hepatic adenoma, hepatocellular carcinoma, non-alcoholic fatty liver disease), and other topics (radiation dose, electroporation, education, general oncology, gadolinium, statistics). Machine learning can be successfully applied to create specific feature-based models for predicting articles likely to achieve high influence within the radiological literature. Copyright © 2016 The Association of University

  12. Distributed Model Predictive Control for Active Power Control of Wind Farm

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

    2014-01-01

    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can......-scale wind farm control....

  13. Multimodel Predictive Control Approach for UAV Formation Flight

    Directory of Open Access Journals (Sweden)

    Chang-jian Ru

    2014-01-01

    Full Text Available Formation flight problem is the most important and interesting problem of multiple UAVs (unmanned aerial vehicles cooperative control. In this paper, a novel approach for UAV formation flight based on multimodel predictive control is designed. Firstly, the state equation of relative motion is obtained and then discretized. By the geometrical method, the characteristic points of state are determined. Afterwards, based on the linearization technique, the standard linear discrete model is obtained at each characteristic state point. Then, weighted model set is proposed using the idea of T-S (Takagi-Sugeno fuzzy control and the predictive control is carried out based on the multimodel method. Finally, to verify the performance of the proposed method, two different simulation scenarios are performed.

  14. Power Admission Control with Predictive Thermal Management in Smart Buildings

    DEFF Research Database (Denmark)

    Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan

    2015-01-01

    This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First......, the power budget with a given thermal comfort constraint is optimized through budget-schedulability analysis which amounts to solving a constrained linear programming problem. Second, the effective peak power demand is reduced by means of the optimal scheduling and cooperative operation of multiple thermal...... appliances. The performance of the proposed control scheme is assessed by simulation based on the thermal dynamics of a real eight-room office building located at Danish Technical University....

  15. Nonlinear underwater robot controller design with adaptive disturbance prediction

    Directory of Open Access Journals (Sweden)

    Xin Songa

    2011-08-01

    Full Text Available A new hybrid adaptive control algorithm is proposed for the nonlinear system controller design of underwater robot. Compared with the previous works in the controller design of underwater robot, the main advantages of this work are: (1 A new disturbance prediction and compensation model is proposed; (2 A new adaptive fuzzy smoother is proposed for the control input; (3 A time-varying flow disturbance is considered for the control design which is always neglected in many previous works and several practical experiments under different environment were implemented to verify the control performance. The Lyapunov stability theory proves the stability and convergence of this new control system. Simulation and experiment results demonstrate the performance and the effectiveness of this new algorithm.

  16. Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

    Directory of Open Access Journals (Sweden)

    Wenbiao Li

    2016-04-01

    Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

  17. Integration of Predictive Display and Aircraft Flight Control System

    Directory of Open Access Journals (Sweden)

    Efremov A.V.

    2017-01-01

    Full Text Available The synthesis of predictive display information and direct lift control system are considered for the path control tracking tasks (in particular landing task. The both solutions are based on pilot-vehicle system analysis and requirements to provide the highest accuracy and lowest pilot workload. The investigation was carried out for cases with and without time delay in aircraft dynamics. The efficiency of the both ways for the flying qualities improvement and their integration is tested by ground based simulation.

  18. Model Predictive Control of the Grain Drying Process

    OpenAIRE

    Feng Han; Chuncheng Zuo; Wenfu Wu; Junxing Li; Zhe Liu

    2012-01-01

    Drying plays an important role in the postharvesting process of grain. To ensure the quality of the dried grain and improve the intelligent level in drying process, a digital simulation of corn drying machine system based on a virtual instrument was established for 5HSZ dryer, automatically control the air temperature, and predict the discharging speed of grain and so forth. Finally, an online measurement and automated control software of grain parameters were developed to provide the changes...

  19. Input-output formulation of multidimensional adaptive predictive control

    Czech Academy of Sciences Publication Activity Database

    Belda, Květoslav; Böhm, Josef

    2007-01-01

    Roč. 7, č. 2 (2007), s. 118-123 ISSN 1336-5010 R&D Projects: GA ČR(CZ) GA102/05/0271; GA ČR GP102/06/P275 Institutional research plan: CEZ:AV0Z10750506 Keywords : ARX model s * on-line identification * state-space predictive control Subject RIV: BC - Control Systems Theory http://library.utia.cas.cz/separaty/historie/belda-0089614.pdf

  20. Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad

    2013-01-01

    The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined......, we simplify state prediction for the MPC. Consequently, the control problem of the nonlinear system is simplified into a quadratic programming. We consider uncertainty in the wind propagation time, which is the traveling time of wind from the LIDAR measurement point to the rotor. An algorithm based...... by the effective wind speed on the rotor disc. We take the wind speed as a scheduling variable. The wind speed is measurable ahead of the turbine using LIDARs, therefore, the scheduling variable is known for the entire prediction horizon. By taking the advantage of having future values of the scheduling variable...

  1. Prediction of Periodontitis Occurrence: Influence of Classification and Sociodemographic and General Health Information

    DEFF Research Database (Denmark)

    Manzolli Leite, Fabio Renato; Peres, Karen Glazer; Do, Loc Giang

    2017-01-01

    BACKGROUND: Prediction of periodontitis development is challenging. Use of oral health-related data alone, especially in a young population, might underestimate disease risk. This study investigates accuracy of oral, systemic, and socioeconomic data on estimating periodontitis development...... in a population-based prospective cohort. METHODS: General health history and sociodemographic information were collected throughout the life-course of individuals. Oral examinations were performed at ages 24 and 31 years in the Pelotas 1982 birth cohort. Periodontitis at age 31 years according to six...... classifications was used as the gold standard to compute area under the receiver operating characteristic curve (AUC). Multivariable binomial regression models were used to evaluate the effects of oral health, general health, and socioeconomic characteristics on accuracy of periodontitis development prediction...

  2. Control and prediction components of movement planning in stuttering vs. nonstuttering adults

    Science.gov (United States)

    Daliri, Ayoub; Prokopenko, Roman A.; Flanagan, J. Randall; Max, Ludo

    2014-01-01

    Purpose Stuttering individuals show speech and nonspeech sensorimotor deficiencies. To perform accurate movements, the sensorimotor system needs to generate appropriate control signals and correctly predict their sensory consequences. Using a reaching task, we examined the integrity of these control and prediction components, separately, for movements unrelated to the speech motor system. Method Nine stuttering and nine nonstuttering adults made fast reaching movements to visual targets while sliding an object under the index finger. To quantify control, we determined initial direction error and end-point error. To quantify prediction, we calculated the correlation between vertical and horizontal forces applied to the object—an index of how well vertical force (preventing slip) anticipated direction-dependent variations in horizontal force (moving the object). Results Directional and end-point error were significantly larger for the stuttering group. Both groups performed similarly in scaling vertical force with horizontal force. Conclusions The stuttering group's reduced reaching accuracy suggests limitations in generating control signals for voluntary movements, even for non-orofacial effectors. Typical scaling of vertical force with horizontal force suggests an intact ability to predict the consequences of planned control signals. Stuttering may be associated with generalized deficiencies in planning control signals rather than predicting the consequences of those signals. PMID:25203459

  3. Nonlinear predictive control for Hammerstein-Wiener systems.

    Science.gov (United States)

    Ławryńczuk, Maciej

    2015-03-01

    This paper discusses a nonlinear Model Predictive Control (MPC) algorithm for multiple-input multiple-output dynamic systems represented by cascade Hammerstein-Wiener models. The block-oriented Hammerstein-Wiener model, which consists of a linear dynamic block embedded between two nonlinear steady-state blocks, may be successfully used to describe numerous processes. A direct application of such a model for prediction in MPC results in a nonlinear optimisation problem which must be solved at each sampling instant on-line. To reduce the computational burden, a linear approximation of the predicted system trajectory linearised along the future control scenario is successively found on-line and used for prediction. Thanks to linearisation, the presented algorithm needs only quadratic optimisation, time-consuming and difficult on-line nonlinear optimisation is not necessary. In contrast to some control approaches for cascade models, the presented algorithm does not need inverse of the steady-state blocks of the model. For two benchmark systems, it is demonstrated that the algorithm gives control accuracy very similar to that obtained in the MPC approach with nonlinear optimisation while performance of linear MPC and MPC with simplified linearisation is much worse. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  4. Stochastic disturbance rejection in model predictive control by randomized algorithms

    NARCIS (Netherlands)

    Batina, Ivo; Stoorvogel, Antonie Arij; Weiland, Siep

    2001-01-01

    In this paper we consider model predictive control with stochastic disturbances and input constraints. We present an algorithm which can solve this problem approximately but with arbitrary high accuracy. The optimization at each time step is a closed loop optimization and therefore takes into

  5. Model Predictive Control for Dynamic Unreliable Resource Allocation

    National Research Council Canada - National Science Library

    Castanon, David

    2002-01-01

    .... The approximation is used in a model predictive control (MPC) algorithm. For single resource problems, the MPC algorithm completes over 98 percent of the task value completed by an optimal dynamic programming algorithm in over 1,000 randomly generated problems. On average, it achieves 99.5 percent of the optimal performance while requiring over 6 orders of magnitude less comnutation.

  6. Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad

    2013-01-01

    The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined...

  7. Real-Time Optimization for Economic Model Predictive Control

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil; Edlund, Kristian; Frison, Gianluca

    2012-01-01

    In this paper, we develop an efficient homogeneous and self-dual interior-point method for the linear programs arising in economic model predictive control. To exploit structure in the optimization problems, the algorithm employs a highly specialized Riccati iteration procedure. Simulations show...

  8. Model Predictive Control of the Hybrid Ventilation for Livestock

    DEFF Research Database (Denmark)

    Wu, Zhuang; Stoustrup, Jakob; Trangbæk, Klaus

    2006-01-01

    In this paper, design and simulation results of Model Predictive Control (MPC) strategy for livestock hybrid ventilation systems and associated indoor climate through variable valve openings and exhaust fans are presented. The design is based on thermal comfort parameters for poultry in barns...

  9. Predictive mechanisms in the control of contour following

    NARCIS (Netherlands)

    Tramper, J.J.; Flanders, M.

    2013-01-01

    In haptic exploration, when running a fingertip along a surface, the control system may attempt to anticipate upcoming changes in curvature in order to maintain a consistent level of contact force. Such predictive mechanisms are well known in the visual system, but have yet to be studied in the

  10. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

    Soltani, Mohsen; Sichani, Mahdi Teimouri; Mirzaei, Mahmood

    2014-01-01

    The paper introduces the Wavestar wave energy converter and presents the implementation of model predictive controller that maximizes the power generation. The ocean wave power is extracted using a hydraulic electric generator which is connected to an oscillating buoy. The power generator is an a...

  11. When predictions take control: The effect of task predictions on task switching performance

    Directory of Open Access Journals (Sweden)

    Wout eDuthoo

    2012-08-01

    Full Text Available In this paper, we aimed to investigate the role of self-generated predictions in the flexible control of behaviour. Therefore, we ran a task switching experiment in which participants were asked to try to predict the upcoming task in three conditions varying in switch rate (30%, 50% and 70%. Irrespective of their predictions, the colour of the target indicated which task participants had to perform. In line with previous studies (Mayr, 2006; Monsell & Mizon, 2006, the switch cost was attenuated as the switch rate increased. Importantly, a clear task repetition bias was found in all conditions, yet the task repetition prediction rate dropped from 78% over 66% to 49% with increasing switch probability in the three conditions. Irrespective of condition, the switch cost was strongly reduced in expectation of a task alternation compared to the cost of an unexpected task alternation following repetition predictions. Hence, our data suggest that the reduction in the switch cost with increasing switch probability is caused by a diminished expectancy for the task to repeat. Taken together, this paper highlights the importance of predictions in the flexible control of behaviour, and suggests a crucial role for task repetition expectancy in the context-sensitive adjusting of task switching performance.

  12. A Generalized Correlation Plot Package for the CEBAF Control System

    International Nuclear Information System (INIS)

    D. Wu; W. Akers; S. Schaffner; H. Shoaee; W. A. Watson; D. Wetherholt

    1996-01-01

    The Correlation Package is a general facility for data acquisition and analysis serving as an online environment for performing a wide variety of machine physics experiments and engineering diagnostics. Typical correlation experiments consist of an initial set of actions followed by stepping one or two accelerator parameters while measuring up to several hundred control system parameters. The package utilizes the CDEV [1] device API to access accelerator systems. A variety of analysis and graphics tools are included through integration with the Matlab math modeling package. A post- acquisition script capability is available to automate the data reduction process. A callable interface allows this facility to serve as the data acquisition and analysis engine for high level applications. A planned interface to archived accelerator data will allow the same analysis and graphics tools to be used for viewing and correlating history data. The object oriented design and C++ implementation details as well as the current status of the Correlation Package will be presented

  13. Development and Validation of a Risk Model for Prediction of Hazardous Alcohol Consumption in General Practice Attendees: The PredictAL Study

    Science.gov (United States)

    King, Michael; Marston, Louise; Švab, Igor; Maaroos, Heidi-Ingrid; Geerlings, Mirjam I.; Xavier, Miguel; Benjamin, Vicente; Torres-Gonzalez, Francisco; Bellon-Saameno, Juan Angel; Rotar, Danica; Aluoja, Anu; Saldivia, Sandra; Correa, Bernardo; Nazareth, Irwin

    2011-01-01

    Background Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score ≥8 in men and ≥5 in women. Results 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse. PMID:21853028

  14. Nonlinear Economic Model Predictive Control Strategy for Active Smart Buildings

    DEFF Research Database (Denmark)

    Santos, Rui Mirra; Zong, Yi; Sousa, Joao M. C.

    2016-01-01

    Nowadays, the development of advanced and innovative intelligent control techniques for energy management in buildings is a key issue within the smart grid topic. A nonlinear economic model predictive control (EMPC) scheme, based on the branch-and-bound tree search used as optimization algorithm...... for solving the nonconvex optimization problem is proposed in this paper. A simulation using the nonlinear model-based controller to control the temperature levels of an intelligent office building (PowerFlexHouse) is addressed. Its performance is compared with a linear model-based controller. The nonlinear...... controller is shown very reliable keeping the comfort levels in the two considered seasons and shifting the load away from peak hours in order to achieve the desired flexible electricity consumption....

  15. APPLICATION OF MODEL PREDICTIVE CONTROL TO BATCH POLYMERIZATION REACTOR

    Directory of Open Access Journals (Sweden)

    N.M. Ghasem

    2006-06-01

    Full Text Available The absence of a stable operational state in polymerization reactors that operates in batches is factor that determine the need of a special control system. In this study, advanced control methodology is implemented for controlling the operation of a batch polymerization reactor for polystyrene production utilizingmodel predictive control. By utilizing a model of the polymerization process, the necessary operational conditions were determined for producing the polymer within the desired characteristics. The maincontrol objective is to bring the reactor temperature to its target temperature as rapidly as possible with minimal temperature overshoot. Control performance for the proposed method is encouraging. It has been observed that temperature overshoot can be minimized by the proposed method with the use of both reactor and jacket energy balance for reactor temperature control.

  16. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  17. System Identification, Prediction, Simulation and Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    a Gauss-Newton search direction is applied. 3) Amongst numerous model types, often met in control applications, only the Non-linear ARMAX (NARMAX) model, representing input/output description, is examined. A simulated example confirms that a neural network has the potential to perform excellent System...... Identification, Prediction, Simulation and Control of a dynamic, non-linear and noisy process. Further, the difficulties to control a practical non-linear laboratory process in a satisfactory way by using a traditional controller are overcomed by using a trained neural network to perform non-linear System......The intention of this paper is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...

  18. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  19. Predictive control and identification: Applications to steering dynamics

    DEFF Research Database (Denmark)

    Hansen, Anca Daniela

    1996-01-01

    the under- standing of the connection between identification and control, analysed in Chapter 7. Chapter 7 focuses on how to make the on-line identification for predictive control more robust towards unmodelled dynamics. The theory is verified via simulation studies on a Mariner Class Vessel. The effects...... and the need of a prefilter in the estimation are analysed and illustrated. Based on the idea that the control criterion must be dual to the estimation criterion, an iterative optimal prefilter is designed. This seems to be an appealing way to tune the model towards the objective for which the model...

  20. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  1. Motivation to control prejudice predicts categorization of multiracials.

    Science.gov (United States)

    Chen, Jacqueline M; Moons, Wesley G; Gaither, Sarah E; Hamilton, David L; Sherman, Jeffrey W

    2014-05-01

    Multiracial individuals often do not easily fit into existing racial categories. Perceivers may adopt a novel racial category to categorize multiracial targets, but their willingness to do so may depend on their motivations. We investigated whether perceivers' levels of internal motivation to control prejudice (IMS) and external motivation to control prejudice (EMS) predicted their likelihood of categorizing Black-White multiracial faces as Multiracial. Across four studies, IMS positively predicted perceivers' categorizations of multiracial faces as Multiracial. The association between IMS and Multiracial categorizations was strongest when faces were most racially ambiguous. Explicit prejudice, implicit prejudice, and interracial contact were ruled out as explanations for the relationship between IMS and Multiracial categorizations. EMS may be negatively associated with the use of the Multiracial category. Therefore, perceivers' motivations to control prejudice have important implications for racial categorization processes.

  2. Does generalized anxiety disorder predict coronary heart disease risk factors independently of major depressive disorder?

    Science.gov (United States)

    Barger, Steven D; Sydeman, Sumner J

    2005-09-01

    Anxiety symptoms are associated with elevated coronary heart disease (CHD) risk, but it is not known whether such associations extend to anxiety disorders or if they are independent of depression. We sought to determine if generalized anxiety disorder is associated with elevated CHD risk, and whether this association is independent of or interacts with major depressive disorder. Generalized anxiety and major depressive disorders were assessed in a cross-sectional survey of a representative sample of U.S. adults aged 25-74 (N=3032). Coronary heart disease risk was determined by self-reported smoking status, body mass index, and recent medication use for hypertension, hypercholesterolemia, and diabetes. Generalized anxiety disorder independently predicted increased CHD risk (F(1,3018)=5.14; b=0.39; 95% confidence interval (0.05-0.72)) and tended to denote the greatest risk in the absence of major depressive disorder. The cross-sectional design cannot determine the causal direction of the association. Generalized anxiety disorder appears to be associated with elevated CHD risk in the general population. It may denote excess CHD risk relative to major depressive disorder, and clinicians should consider CHD risk when treating generalized anxiety disorder.

  3. Offset-Free Direct Power Control of DFIG Under Continuous-Time Model Predictive Control

    DEFF Research Database (Denmark)

    Errouissi, Rachid; Al-Durra, Ahmed; Muyeen, S.M.

    2017-01-01

    This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current...... without encompassing the parameters of the machine itself. Hence, no extra power control loop is required in the control structure to ensure smooth operation of the DFIG. The feasibility of the proposed strategy is verified by the experimental results of the grid-connected DFIG and satisfactory...

  4. Robust predictive control of a gasoline debutanizer column

    Directory of Open Access Journals (Sweden)

    Almeida Neto E.

    2000-01-01

    Full Text Available This paper studies the application of Model Predictive Control to moderately nonlinear processes. The system used in this work is an industrial gasoline debutanizer column. The paper presents two new formulations of MPC: MMPC (Multi-Model Predictive Controller and RSMPC (Robust Stable MPC. The approach is based on the concepts of Linear Matrix Inequalities (LMI, which have been recently introduced in the MPC field. Model uncertainty is considered by assuming that the true process model belongs to a convex set (polytope of possible plants. The controller has guaranteed stability when a Lyapunov type inequality constraint is included in the MPC problem. In the debutanizer column, several nonlinearities are present in the advanced control level when the manipulated inputs are the reflux flow and the reboiler heat duty. In most cases the controlled outputs are the contents of C5+ (pentane and heavier hydrocarbons in the LPG (Liquefied Petroleum Gas and the gasoline vapor pressure (P VR. In this case the QDMC algorithm which is usually applied to the debutanizer column has a poor performance and stability problems reflected in an oscillatory behavior of the process. The new approach considers several process models representing different operating conditions where linear models are identified. The results presented here show that the multimodel controller is capable of controlling the process in the entire operating window while the conventional MPC has a limited operating range.

  5. High level model predictive control for plug-and-play process control with stability guaranty

    DEFF Research Database (Denmark)

    Michelsen, Axel Gottlieb; Stoustrup, Jakob

    2010-01-01

    In this paper a method for designing a stabilizing high level model predictive controller for a hierarchical plug- and-play process is presented. This is achieved by abstracting the lower layers of the controller structure as low order models with uncertainty and by using a robust model predictive...... controller for generating the references for these. A simulation example, in which the actuators in a process control system are changed, is reported to show the potential of this approach for plug and play process control....

  6. Model predictive control for Z-source power converter

    DEFF Research Database (Denmark)

    Mo, W.; Loh, P.C.; Blaabjerg, Frede

    2011-01-01

    This paper presents Model Predictive Control (MPC) of impedance-source (commonly known as Z-source) power converter. Output voltage control and current control for Z-source inverter are analyzed and simulated. With MPC's ability of multi- system variables regulation, load current and voltage...... regulations, impedance network inductor current, capacitor voltage as well as switching frequency fixation, transient reservation and null state penalization are all regulated as subjecting to constraints of this control method. The quality of output waveform, stability of impedance-network, level constraint...... of variable switching frequency as well as robustness of transient response can be obtained at the same time with a formulated Z-source network model. Operating steady state and transient state simulation of MPC are going to be presented, which shows good reference tracking ability of this control method....

  7. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    Science.gov (United States)

    Miller, Christopher J.

    2011-01-01

    A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

  8. Multi-objective optimization framework for networked predictive controller design.

    Science.gov (United States)

    Das, Sourav; Das, Saptarshi; Pan, Indranil

    2013-01-01

    Networked Control Systems (NCSs) often suffer from random packet dropouts which deteriorate overall system's stability and performance. To handle the ill effects of random packet losses in feedback control systems, closed over communication network, a state feedback controller with predictive gains has been designed. To achieve improved performance, an optimization based controller design framework has been proposed in this paper with Linear Matrix Inequality (LMI) constraints, to ensure guaranteed stability. Different conflicting objective functions have been optimized with Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The methodology proposed in this paper not only gives guaranteed closed loop stability in the sense of Lyapunov, even in the presence of random packet losses, but also gives an optimization trade-off between two conflicting time domain control objectives. Copyright © 2012 ISA. All rights reserved.

  9. Data-Driven Predictive Direct Load Control of Refrigeration Systems

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Knudsen, Torben; Wisniewski, Rafal

    2015-01-01

    A predictive control using subspace identification is applied for the smart grid integration of refrigeration systems under a direct load control scheme. A realistic demand response scenario based on regulation of the electrical power consumption is considered. A receding horizon optimal control...... in the control implementation. As an important practical consideration, the control design relies on a cheap solution with available measurements than using the expensive mass flow meters. The results show successful implementation of the method on a large-scale non-linear simulation tool which is validated...... against real data. The performance improvement results in a 22% reduction in the energy consumption. A comparative simulation is accomplished showing the superiority of the method over the existing approaches in terms of the load following performance....

  10. Decentralized robust nonlinear model predictive controller for unmanned aerial systems

    Science.gov (United States)

    Garcia Garreton, Gonzalo A.

    The nonlinear and unsteady nature of aircraft aerodynamics together with limited practical range of controls and state variables make the use of the linear control theory inadequate especially in the presence of external disturbances, such as wind. In the classical approach, aircraft are controlled by multiple inner and outer loops, designed separately and sequentially. For unmanned aerial systems in particular, control technology must evolve to a point where autonomy is extended to the entire mission flight envelope. This requires advanced controllers that have sufficient robustness, track complex trajectories, and use all the vehicles control capabilities at higher levels of accuracy. In this work, a robust nonlinear model predictive controller is designed to command and control an unmanned aerial system to track complex tight trajectories in the presence of internal and external perturbance. The Flight System developed in this work achieves the above performance by using: 1. A nonlinear guidance algorithm that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2. A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3. An artificial neural network, designed to adaptively estimate and provide aerodynamic and propulsive forces in real-time; and 4. A mixed sensitivity approach that enhances the robustness for a nonlinear model predictive controller overcoming the effect of un-modeled dynamics, external disturbances such as wind, and measurement additive perturbations, such as noise and biases. These elements have been integrated and tested in simulation and with previously stored flight test data and shown to be feasible.

  11. Fault Tolerant Flight Control Using Sliding Modes and Subspace Identification-Based Predictive Control

    KAUST Repository

    Siddiqui, Bilal A.

    2016-07-26

    In this work, a cascade structure of a time-scale separated integral sliding mode and model predictive control is proposed as a viable alternative for fault-tolerant control. A multi-variable sliding mode control law is designed as the inner loop of the flight control system. Subspace identification is carried out on the aircraft in closed loop. The identified plant is then used for model predictive controllers in the outer loop. The overall control law demonstrates improved robustness to measurement noise, modeling uncertainties, multiple faults and severe wind turbulence and gusts. In addition, the flight control system employs filters and dead-zone nonlinear elements to reduce chattering and improve handling quality. Simulation results demonstrate the efficiency of the proposed controller using conventional fighter aircraft without control redundancy.

  12. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  13. Chaos control and synchronization for a special generalized Lorenz canonical system - The SM system

    International Nuclear Information System (INIS)

    Liao Xiaoxin; Xu, F.; Wang, P.; Yu Pei

    2009-01-01

    This paper presents some simple feedback control laws to study global stabilization and global synchronization for a special chaotic system described in the generalized Lorenz canonical form (GLCF) when τ = -1 (which, for convenience, we call Shimizu-Morioka system, or simply SM system). For an arbitrarily given equilibrium point, a simple feedback controller is designed to globally, exponentially stabilize the system, and reach globally exponent synchronization for two such systems. Based on the system's coefficients and the structure of the system, simple feedback control laws and corresponding Lyapunov functions are constructed. Because all conditions are obtained explicitly in terms of algebraic expressions, they are easy to be implemented and applied to real problems. Numerical simulation results are presented to verify the theoretical predictions.

  14. What Is Going On Around Here? Intolerance of Uncertainty Predicts Threat Generalization.

    Directory of Open Access Journals (Sweden)

    Jayne Morriss

    Full Text Available Attending to stimuli that share perceptual similarity to learned threats is an adaptive strategy. However, prolonged threat generalization to cues signalling safety is considered a core feature of pathological anxiety. One potential factor that may sustain over-generalization is sensitivity to future threat uncertainty. To assess the extent to which Intolerance of Uncertainty (IU predicts threat generalization, we recorded skin conductance in 54 healthy participants during an associative learning paradigm, where threat and safety cues varied in perceptual similarity. Lower IU was associated with stronger discrimination between threat and safety cues during acquisition and extinction. Higher IU, however, was associated with generalized responding to threat and safety cues during acquisition, and delayed discrimination between threat and safety cues during extinction. These results were specific to IU, over and above other measures of anxious disposition. These findings highlight: (1 a critical role of uncertainty-based mechanisms in threat generalization, and (2 IU as a potential risk factor for anxiety disorder development.

  15. Generalized Concentration Addition Modeling Predicts Mixture Effects of Environmental PPARγ Agonists.

    Science.gov (United States)

    Watt, James; Webster, Thomas F; Schlezinger, Jennifer J

    2016-09-01

    The vast array of potential environmental toxicant combinations necessitates the development of efficient strategies for predicting toxic effects of mixtures. Current practices emphasize the use of concentration addition to predict joint effects of endocrine disrupting chemicals in coexposures. Generalized concentration addition (GCA) is one such method for predicting joint effects of coexposures to chemicals and has the advantage of allowing for mixture components to have differences in efficacy (ie, dose-response curve maxima). Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor that plays a central role in regulating lipid homeostasis, insulin sensitivity, and bone quality and is the target of an increasing number of environmental toxicants. Here, we tested the applicability of GCA in predicting mixture effects of therapeutic (rosiglitazone and nonthiazolidinedione partial agonist) and environmental PPARγ ligands (phthalate compounds identified using EPA's ToxCast database). Transcriptional activation of human PPARγ1 by individual compounds and mixtures was assessed using a peroxisome proliferator response element-driven luciferase reporter. Using individual dose-response parameters and GCA, we generated predictions of PPARγ activation by the mixtures, and we compared these predictions with the empirical data. At high concentrations, GCA provided a better estimation of the experimental response compared with 3 alternative models: toxic equivalency factor, effect summation and independent action. These alternatives provided reasonable fits to the data at low concentrations in this system. These experiments support the implementation of GCA in mixtures analysis with endocrine disrupting compounds and establish PPARγ as an important target for further studies of chemical mixtures. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e

  16. Artificial neural network implementation of a near-ideal error prediction controller

    Science.gov (United States)

    Mcvey, Eugene S.; Taylor, Lynore Denise

    1992-01-01

    responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

  17. Frequency weighted model predictive control of wind turbine

    DEFF Research Database (Denmark)

    Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood

    2013-01-01

    This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...... accordingly. In practice is very hard to measure the effective wind speed, this quantity will be estimated using measurements from the turbine itself. For this purpose stationary predictive Kalman filter has been used. Stochastic simulations of the wind turbine behaviour with applied frequency weighted model...

  18. Nonlinear Model Predictive Control for Oil Reservoirs Management

    DEFF Research Database (Denmark)

    Capolei, Andrea

    . The controller consists of -A model based optimizer for maximizing some predicted financial measure of the reservoir (e.g. the net present value). -A parameter and state estimator. -Use of the moving horizon principle for data assimilation and implementation of the computed control input. The optimizer uses...... Optimization has been suggested to compensate for inherent geological uncertainties in an oil field. In robust optimization of an oil reservoir, the water injection and production borehole pressures are computed such that the predicted net present value of an ensemble of permeability field realizations...... equivalent strategy is not justified for the particular case studied in this paper. The third contribution of this thesis is a mean-variance method for risk mitigation in production optimization of oil reservoirs. We introduce a return-risk bicriterion objective function for the profit-risk tradeoff...

  19. Mother's but not father's education predicts general fluid intelligence in emerging adulthood: Behavioral and neuroanatomical evidence.

    Science.gov (United States)

    Kong, Feng; Chen, Zhencai; Xue, Song; Wang, Xu; Liu, Jia

    2015-11-01

    Lower parental education impairs cognitive abilities of their offspring such as general fluid intelligence dependent on the prefrontal cortex (PFC), but the independent contribution of mother's and father's education is unknown. We used an individual difference approach to test whether mother's and father's education independently affected general fluid intelligence in emerging adulthood at both the behavioral and neural level. Behaviorally, mother's but not father's education accounted for unique variance in general fluid intelligence in emerging adulthood (assessed by the Raven's advanced progressive matrices). Neurally, the whole-brain correlation analysis revealed that the regional gray matter volume (rGMV) in the medial PFC was related to both mother's education and general fluid intelligence but not father's education. Furthermore, after controlling for mother's education, the association between general fluid intelligence and the rGMV in medial PFC was no longer significant, indicating that mother's education plays an important role in influencing the structure of the medial PFC associated with general fluid intelligence. Taken together, our study provides the first behavioral and neural evidence that mother's education is a more important determinant of general cognitive ability in emerging adulthood than father's education. © 2015 Wiley Periodicals, Inc.

  20. New predictions for generalized spin polarizabilities from heavy baryon chiral perturbation theory

    International Nuclear Information System (INIS)

    Chung-Wen Kao; Barbara Pasquini; Marc Vanderhaeghen

    2004-01-01

    We extract the next-to-next-to-leading order results for spin-flip generalized polarizabilities (GPs) of the nucleon from the spin-dependent amplitudes for virtual Compton scattering (VCS) at Ο(p 4 ) in heavy baryon chiral perturbation theory. At this order, no unknown low energy constants enter the theory, allowing us to make absolute predictions for all spin-flip GPs. Furthermore, by using constraint equations between the GPs due to nucleon crossing combined with charge conjugation symmetry of the VCS amplitudes, we get a next-to-next-to-next-to-leading order prediction for one of the GPs. We provide estimates for forthcoming double polarization experiments which allow to access these spin-flip GPs of the nucleon

  1. Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics

    Directory of Open Access Journals (Sweden)

    Amany E. Aly

    2016-04-01

    Full Text Available When a system consisting of independent components of the same type, some appropriate actions may be done as soon as a portion of them have failed. It is, therefore, important to be able to predict later failure times from earlier ones. One of the well-known failure distributions commonly used to model component life, is the modified Weibull distribution (MWD. In this paper, two pivotal quantities are proposed to construct prediction intervals for future unobservable lifetimes based on generalized order statistics (gos from MWD. Moreover, a pivotal quantity is developed to reconstruct missing observations at the beginning of experiment. Furthermore, Monte Carlo simulation studies are conducted and numerical computations are carried out to investigate the efficiency of presented results. Finally, two illustrative examples for real data sets are analyzed.

  2. Control System Design for Cylindrical Tank Process Using Neural Model Predictive Control Technique

    Directory of Open Access Journals (Sweden)

    M. Sridevi

    2010-10-01

    Full Text Available Chemical manufacturing and process industry requires innovative technologies for process identification. This paper deals with model identification and control of cylindrical process. Model identification of the process was done using ARMAX technique. A neural model predictive controller was designed for the identified model. The performance of the controllers was evaluated using MATLAB software. The performance of NMPC controller was compared with Smith Predictor controller and IMC controller based on rise time, settling time, overshoot and ISE and it was found that the NMPC controller is better suited for this process.

  3. Control of continuous fed-batch fermentation process using neural network based model predictive controller.

    Science.gov (United States)

    Kiran, A Uma Maheshwar; Jana, Asim Kumar

    2009-10-01

    Cell growth and metabolite production greatly depend on the feeding of the nutrients in fed-batch fermentations. A strategy for controlling the glucose feed rate in fed-batch baker's yeast fermentation and a novel controller was studied. The difference between the specific carbon dioxide evolution rate and oxygen uptake rate (Qc - Qo) was used as controller variable. The controller evaluated was neural network based model predictive controller and optimizer. The performance of the controller was evaluated by the set point tracking. Results showed good performance of the controller.

  4. Dynamics and control of quadcopter using linear model predictive control approach

    Science.gov (United States)

    Islam, M.; Okasha, M.; Idres, M. M.

    2017-12-01

    This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

  5. Model predictive control approach for a CPAP-device

    Directory of Open Access Journals (Sweden)

    Scheel Mathias

    2017-09-01

    Full Text Available The obstructive sleep apnoea syndrome (OSAS is characterized by a collapse of the upper respiratory tract, resulting in a reduction of the blood oxygen- and an increase of the carbon dioxide (CO2 - concentration, which causes repeated sleep disruptions. The gold standard to treat the OSAS is the continuous positive airway pressure (CPAP therapy. The continuous pressure keeps the upper airway open and prevents the collapse of the upper respiratory tract and the pharynx. Most of the available CPAP-devices cannot maintain the pressure reference [1]. In this work a model predictive control approach is provided. This control approach has the possibility to include the patient’s breathing effort into the calculation of the control variable. Therefore a patient-individualized control strategy can be developed.

  6. FRAX®: Prediction of Major Osteoporotic Fractures in Women from the General Population: The OPUS Study

    Science.gov (United States)

    Briot, Karine; Paternotte, Simon; Kolta, Sami; Eastell, Richard; Felsenberg, Dieter; Reid, David M.; Glüer, Claus-C.; Roux, Christian

    2013-01-01

    Purposes The aim of this study was to analyse how well FRAX® predicts the risk of major osteoporotic and vertebral fractures over 6 years in postmenopausal women from general population. Patients and methods The OPUS study was conducted in European women aged above 55 years, recruited in 5 centers from random population samples and followed over 6 years. The population for this study consisted of 1748 women (mean age 74.2 years) with information on incident fractures. 742 (43.1%) had a prevalent fracture; 769 (44%) and 155 (8.9%) of them received an antiosteoporotic treatment before and during the study respectively. We compared FRAX® performance with and without bone mineral density (BMD) using receiver operator characteristic (ROC) c-statistical analysis with ORs and areas under receiver operating characteristics curves (AUCs) and net reclassification improvement (NRI). Results 85 (4.9%) patients had incident major fractures over 6 years. FRAX® with and without BMD predicted these fractures with an AUC of 0.66 and 0.62 respectively. The AUC were 0.60, 0.66, 0.69 for history of low trauma fracture alone, age and femoral neck (FN) BMD and combination of the 3 clinical risk factors, respectively. FRAX® with and without BMD predicted incident radiographic vertebral fracture (n = 65) with an AUC of 0.67 and 0.65 respectively. NRI analysis showed a significant improvement in risk assignment when BMD is added to FRAX®. Conclusions This study shows that FRAX® with BMD and to a lesser extent also without FN BMD predict major osteoporotic and vertebral fractures in the general population. PMID:24386199

  7. Tissue Doppler echocardiography predicts acute myocardial infarction, heart failure, and cardiovascular death in the general population

    DEFF Research Database (Denmark)

    Mogelvang, Rasmus; Biering-Sørensen, Tor; Jensen, Jan Skov

    2015-01-01

    AIMS: To improve risk prediction of cardiovascular morbidity and mortality, we need sensitive markers of cardiac dysfunction; Echocardiographic Tissue Doppler Imaging (TDI) is feasible and harmless and may be ideal for this purpose. METHODS AND RESULTS: Within the community-based Copenhagen City...... with a normal conventional echocardiographic examination [per cm/s decrease: HR 1.18 (1.08-1.28), P general population, TDI identifies individuals with cardiac dysfunction and high risk of cardiovascular morbidity and mortality independently of traditional risk factors, even...

  8. Stability theory and transition prediction applied to a general aviation fuselage

    Science.gov (United States)

    Spall, R. E.; Wie, Y.-S.

    1993-01-01

    The linear stability of a fully three-dimensional boundary layer formed over a general aviation fuselage was investigated. The location of the onset of transition was estimated using the N-factor method. The results were compared with existing experimental data and indicate N-factors of approximately 8.5 on the side of the fuselage and 3.0 near the top. Considerable crossflow existed along the side of the body, which significantly affected the unstable modes present in the boundary layer. Fair agreement was found between the predicted frequency range of linear instability modes and available experimental data concerning the spectral content of the boundary layer.

  9. Fast Prediction of Adsorption Properties for Platinum Nanocatalysts with Generalized Coordination Numbers

    DEFF Research Database (Denmark)

    Calle-Vallejo, Federico; Martinez, Jose I.; García Lastra, Juan Maria

    2014-01-01

    in simple terms, while being able to compare these trends with those of extended surfaces. The trends in the adsorption energies of small oxygen- and hydrogen-containing adsorbates on Pt nanoparticles of various sizes and on extended surfaces were analyzed through DFT calculations by making use...... of the generalized coordination numbers of the surface sites. This simple and predictive descriptor links the geometric arrangement of a surface to its adsorption properties. It generates linear adsorption-energy trends, captures finite-size effects, and provides more accurate descriptions than d-band centers...

  10. Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

    OpenAIRE

    Tang Xiaofeng; Gao Feng; Xu Guoyan; Ding Nenggen; Cai Yao; Liu Jian Xing

    2014-01-01

    The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimi...

  11. Self-reported musculoskeletal pain predicts long-term increase in general health care use

    DEFF Research Database (Denmark)

    Hartvigsen, Jan; Davidsen, Michael; Søgaard, Karen

    2014-01-01

    /feet. Results: Regardless of site, persons experiencing a musculoskeletal complaint had a statistically increased risk of consulting a general practitioner when compared with persons reporting no musculoskeletal complaint. For physiotherapists and chiropractors, only persons complaining of neck pain and back...... pain had an increased risk of seeking care. Regardless of pain site, except for shoulder pain, persons reporting musculoskeletal pain had a statistically significant increased risk of outpatient hospital consultations and hospital admissions. Few differences were found between pain sites in relation...... to any of the outcomes. CONCLUSIONS SELF-REPORT OF MUSCULOSKELETAL PAIN REPORTED WITHIN THE PAST TWO WEEKS PREDICTS A STATISTICALLY SIGNIFICANT LONG-TERM INCREASE IN GENERAL USE OF HEALTH CARE SERVICES IN BOTH THE PRIMARY AND THE SECONDARY HEALTH CARE SECTOR:...

  12. Protein structure validation by generalized linear model root-mean-square deviation prediction.

    Science.gov (United States)

    Bagaria, Anurag; Jaravine, Victor; Huang, Yuanpeng J; Montelione, Gaetano T; Güntert, Peter

    2012-02-01

    Large-scale initiatives for obtaining spatial protein structures by experimental or computational means have accentuated the need for the critical assessment of protein structure determination and prediction methods. These include blind test projects such as the critical assessment of protein structure prediction (CASP) and the critical assessment of protein structure determination by nuclear magnetic resonance (CASD-NMR). An important aim is to establish structure validation criteria that can reliably assess the accuracy of a new protein structure. Various quality measures derived from the coordinates have been proposed. A universal structural quality assessment method should combine multiple individual scores in a meaningful way, which is challenging because of their different measurement units. Here, we present a method based on a generalized linear model (GLM) that combines diverse protein structure quality scores into a single quantity with intuitive meaning, namely the predicted coordinate root-mean-square deviation (RMSD) value between the present structure and the (unavailable) "true" structure (GLM-RMSD). For two sets of structural models from the CASD-NMR and CASP projects, this GLM-RMSD value was compared with the actual accuracy given by the RMSD value to the corresponding, experimentally determined reference structure from the Protein Data Bank (PDB). The correlation coefficients between actual (model vs. reference from PDB) and predicted (model vs. "true") heavy-atom RMSDs were 0.69 and 0.76, for the two datasets from CASD-NMR and CASP, respectively, which is considerably higher than those for the individual scores (-0.24 to 0.68). The GLM-RMSD can thus predict the accuracy of protein structures more reliably than individual coordinate-based quality scores. Copyright © 2011 The Protein Society.

  13. Patient characteristics do not predict poor glycaemic control in type 2 diabetes patients treated in primary care

    NARCIS (Netherlands)

    Goudswaard, AN; Stolk, RP; Zuithoff, P; Rutten, GEHM

    Many diabetic patients in general practice do not achieve good glycaemic control. The aim of this study was to assess which characteristics of type 2 diabetes patients treated in primary care predict poor glycaemic control (HbA(1c) greater than or equal to7%). Data were collected from the medical

  14. Importance of Perioperative Glycemic Control in General Surgery

    Science.gov (United States)

    Kwon, Steve; Thompson, Rachel; Dellinger, Patchen; Yanez, David; Farrohki, Ellen; Flum, David

    2014-01-01

    Objective To determine the relationship of perioperative hyperglycemia and insulin administration on outcomes in elective colon/rectal and bariatric operations. Background There is limited evidence to characterize the impact of perioperative hyperglycemia and insulin on adverse outcomes in patients, with and without diabetes, undergoing general surgical procedures. Methods The Surgical Care and Outcomes Assessment Program is a Washington State quality improvement benchmarking-based initiative. We evaluated the relationship of perioperative hyperglycemia (>180 mg/dL) and insulin administration on mortality, reoperative interventions, and infections for patients undergoing elective colorectal and bariatric surgery at 47 participating hospitals between fourth quarter of 2005 and fourth quarter of 2010. Results Of the 11,633 patients (55.4 ± 15.3 years; 65.7% women) with a serum glucose determination on the day of surgery, postoperative day 1, or postoperative day 2, 29.1% of patients were hyperglycemic. After controlling for clinical factors, those with hyperglycemia had a significantly increased risk of infection [odds ratio (OR) 2.0; 95% confidence interval (CI), 1.63–2.44], reoperative interventions (OR, 1.8; 95% CI, 1.41–2.3), and death (OR, 2.71; 95% CI, 1.72–4.28). Increased risk of poor outcomes was observed both for patients with and without diabetes. Those with hyperglycemia on the day of surgery who received insulin had no significant increase in infections (OR, 1.01; 95% CI, 0.72–1.42), reoperative interventions (OR, 1.29; 95% CI, 0.89–1.89), or deaths (OR, 1.21; 95% CI, 0.61–2.42). A dose-effect relationship was found between the effectiveness of insulin-related glucose control (worst 180–250 mg/dL, best surgery patients with and without diabetes. However, patients with hyperglycemia who received insulin were at no greater risk than those with normal blood glucoses. Perioperative glucose evaluation and insulin administration in patients with

  15. Quality Control Review of the Assistant General for Audits Office of the Inspector General, National Reconnaissance Office

    National Research Council Canada - National Science Library

    Brannin, Patricia A

    2004-01-01

    .... From July 2003 through January 2004, the external review team conducted a review of the audit quality control function for the NRO Office of the Inspector General in effect for the period from August...

  16. Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems

    Science.gov (United States)

    Nguyen, Nhan

    2006-01-01

    This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.

  17. Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3

    Science.gov (United States)

    Petersen, Bjørn Molt; Boel, Mikkel; Montag, Markus; Gardner, David K.

    2016-01-01

    STUDY QUESTION Can a generally applicable morphokinetic algorithm suitable for Day 3 transfers of time-lapse monitored embryos originating from different culture conditions and fertilization methods be developed for the purpose of supporting the embryologist's decision on which embryo to transfer back to the patient in assisted reproduction? SUMMARY ANSWER The algorithm presented here can be used independently of culture conditions and fertilization method and provides predictive power not surpassed by other published algorithms for ranking embryos according to their blastocyst formation potential. WHAT IS KNOWN ALREADY Generally applicable algorithms have so far been developed only for predicting blastocyst formation. A number of clinics have reported validated implantation prediction algorithms, which have been developed based on clinic-specific culture conditions and clinical environment. However, a generally applicable embryo evaluation algorithm based on actual implantation outcome has not yet been reported. STUDY DESIGN, SIZE, DURATION Retrospective evaluation of data extracted from a database of known implantation data (KID) originating from 3275 embryos transferred on Day 3 conducted in 24 clinics between 2009 and 2014. The data represented different culture conditions (reduced and ambient oxygen with various culture medium strategies) and fertilization methods (IVF, ICSI). The capability to predict blastocyst formation was evaluated on an independent set of morphokinetic data from 11 218 embryos which had been cultured to Day 5. PARTICIPANTS/MATERIALS, SETTING, METHODS The algorithm was developed by applying automated recursive partitioning to a large number of annotation types and derived equations, progressing to a five-fold cross-validation test of the complete data set and a validation test of different incubation conditions and fertilization methods. The results were expressed as receiver operating characteristics curves using the area under the

  18. Design of nonlinear PID controller and nonlinear model predictive controller for a continuous stirred tank reactor.

    Science.gov (United States)

    Prakash, J; Srinivasan, K

    2009-07-01

    In this paper, the authors have represented the nonlinear system as a family of local linear state space models, local PID controllers have been designed on the basis of linear models, and the weighted sum of the output from the local PID controllers (Nonlinear PID controller) has been used to control the nonlinear process. Further, Nonlinear Model Predictive Controller using the family of local linear state space models (F-NMPC) has been developed. The effectiveness of the proposed control schemes has been demonstrated on a CSTR process, which exhibits dynamic nonlinearity.

  19. Prediction and control of neural responses to pulsatile electrical stimulation

    Science.gov (United States)

    Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

    2012-04-01

    This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

  20. A Traffic Prediction Algorithm for Street Lighting Control Efficiency

    Directory of Open Access Journals (Sweden)

    POPA Valentin

    2013-01-01

    Full Text Available This paper presents the development of a traffic prediction algorithm that can be integrated in a street lighting monitoring and control system. The prediction algorithm must enable the reduction of energy costs and improve energy efficiency by decreasing the light intensity depending on the traffic level. The algorithm analyses and processes the information received at the command center based on the traffic level at different moments. The data is collected by means of the Doppler vehicle detection sensors integrated within the system. Thus, two methods are used for the implementation of the algorithm: a neural network and a k-NN (k-Nearest Neighbor prediction algorithm. For 500 training cycles, the mean square error of the neural network is 9.766 and for 500.000 training cycles the error amounts to 0.877. In case of the k-NN algorithm the error increases from 8.24 for k=5 to 12.27 for a number of 50 neighbors. In terms of a root means square error parameter, the use of a neural network ensures the highest performance level and can be integrated in a street lighting control system.

  1. General correlation for prediction of critical heat flux ratio in water cooled channels

    Energy Technology Data Exchange (ETDEWEB)

    Pernica, R.; Cizek, J.

    1995-09-01

    The paper present the general empirical Critical Heat Flux Ration (CHFR) correlation which is valid for vertical water upflow through tubes, internally heated concentric annuli and rod bundles geometries with both wide and very tight square and triangular rods lattices. The proposed general PG correlation directly predicts the CHFR, it comprises axial and radial non-uniform heating, and is valid in a wider range of thermal hydraulic conditions than previously published critical heat flux correlations. The PG correlation has been developed using the critical heat flux Czech data bank which includes more than 9500 experimental data on tubes, 7600 data on rod bundles and 713 data on internally heated concentric annuli. Accuracy of the CHFR prediction, statistically assessed by the constant dryout conditions approach, is characterized by the mean value nearing 1.00 and the standard deviation less than 0.06. Moverover, a subchannel form of the PG correlations is statistically verified on Westinghouse and Combustion Engineering rod bundle data bases, i.e. more than 7000 experimental CHF points of Columbia University data bank were used.

  2. A model predictive control approach to design a parameterized adaptive cruise control

    NARCIS (Netherlands)

    Naus, G.J.L.; Ploeg, J.; Molengraft, M.J.G. van de; Heemels, W.P.M.H.; Steinbuch, M.

    2010-01-01

    The combination of different desirable characteristics and situation-dependent behavior cause the design of adaptive cruise control (ACC) systems to be time consuming and tedious. This chapter presents a systematic approach for the design and tuning of an ACC, based on model predictive control

  3. Study of Model Predictive Control for Path-Following Autonomous Ground Vehicle Control under Crosswind Effect

    Directory of Open Access Journals (Sweden)

    Fitri Yakub

    2016-01-01

    Full Text Available We present a comparative study of model predictive control approaches of two-wheel steering, four-wheel steering, and a combination of two-wheel steering with direct yaw moment control manoeuvres for path-following control in autonomous car vehicle dynamics systems. Single-track mode, based on a linearized vehicle and tire model, is used. Based on a given trajectory, we drove the vehicle at low and high forward speeds and on low and high road friction surfaces for a double-lane change scenario in order to follow the desired trajectory as close as possible while rejecting the effects of wind gusts. We compared the controller based on both simple and complex bicycle models without and with the roll vehicle dynamics for different types of model predictive control manoeuvres. The simulation result showed that the model predictive control gave a better performance in terms of robustness for both forward speeds and road surface variation in autonomous path-following control. It also demonstrated that model predictive control is useful to maintain vehicle stability along the desired path and has an ability to eliminate the crosswind effect.

  4. Design and implementation of parameterized adaptive cruise control: An explicit model predictive control approach

    NARCIS (Netherlands)

    Naus, G.J.L.; Ploeg, J.; Molengraft, M.J.G. van de; Heemels, W.P.M.H.; Steinbuch, M.

    2010-01-01

    The combination of different characteristics and situation-dependent behavior cause the design of adaptive cruise control (ACC) systems to be time consuming. This paper presents a systematic approach for the design of a parameterized ACC, based on explicit model predictive control. A unique feature

  5. General model and control of an n rotor helicopter

    International Nuclear Information System (INIS)

    Sidea, A G; Brogaard, R Yding; Andersen, N A; Ravn, O

    2014-01-01

    The purpose of this study was to create a dynamic, nonlinear mathematical model of a multirotor that would be valid for different numbers of rotors. Furthermore, a set of Single Input Single Output (SISO) controllers were implemented for attitude control. Both model and controllers were tested experimentally on a quadcopter. Using the combined model and controllers, simple system simulation and control is possible, by replacing the physical values for the individual systems

  6. General model and control of an n rotor helicopter

    Science.gov (United States)

    Sidea, A. G.; Yding Brogaard, R.; Andersen, N. A.; Ravn, O.

    2014-12-01

    The purpose of this study was to create a dynamic, nonlinear mathematical model of a multirotor that would be valid for different numbers of rotors. Furthermore, a set of Single Input Single Output (SISO) controllers were implemented for attitude control. Both model and controllers were tested experimentally on a quadcopter. Using the combined model and controllers, simple system simulation and control is possible, by replacing the physical values for the individual systems.

  7. Model predictive control of wind energy conversion systems

    CERN Document Server

    Yaramasu, Venkata Narasimha R

    2017-01-01

    The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS.

  8. Model Predictive Control of the Grain Drying Process

    Directory of Open Access Journals (Sweden)

    Feng Han

    2012-01-01

    Full Text Available Drying plays an important role in the postharvesting process of grain. To ensure the quality of the dried grain and improve the intelligent level in drying process, a digital simulation of corn drying machine system based on a virtual instrument was established for 5HSZ dryer, automatically control the air temperature, and predict the discharging speed of grain and so forth. Finally, an online measurement and automated control software of grain parameters were developed to provide the changes of moisture, temperature, humidity, and germination rate in the process of drying. The study carried out in the actual processing showed that it can meet the requirements of the actual drying operation, effectively control the stability of the grain moisture, and keep the dry food quality.

  9. Explicit Nonlinear Model Predictive Control Theory and Applications

    CERN Document Server

    Grancharova, Alexandra

    2012-01-01

    Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: Ø  Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; �...

  10. Developing Control System of Electrical Devices with Operational Expense Prediction

    Science.gov (United States)

    Sendari, Siti; Wahyu Herwanto, Heru; Rahmawati, Yuni; Mukti Putranto, Dendi; Fitri, Shofiana

    2017-04-01

    The purpose of this research is to develop a system that can monitor and record home electrical device’s electricity usage. This system has an ability to control electrical devices in distance and predict the operational expense. The system was developed using micro-controllers and WiFi modules connected to PC server. The communication between modules is arranged by server via WiFi. Beside of reading home electrical devices electricity usage, the unique point of the proposed-system is the ability of micro-controllers to send electricity data to server for recording the usage of electrical devices. The testing of this research was done by Black-box method to test the functionality of system. Testing system run well with 0% error.

  11. Economic Model Predictive Control for Spray Drying Plants

    DEFF Research Database (Denmark)

    Petersen, Lars Norbert

    and MPC strategies to optimize the operation of four-stage spray dryers. The models are first-principle dynamic models with parameters identified from dryer specific experiments and powder properties identified from laboratory tests. A simulation model is used for detailed closed-loop simulations...... and a complexity reduced control model is used for state estimation and prediction in the controllers. These models facilitate development and comparison of control strategies. We develop two MPC strategies; a linear tracking MPC with a Real-Time Optimization layer (MPC with RTO) and an Economic Nonlinear MPC (E...... and sticky powder is avoided from building up on the dryer walls; 3) Demonstrate the industrial application of an MPC strategy to a full-scale industrial four-stage spray dryer. The main scientific contributions can be summarized to: - Modeling of a four-stage spray dryer. We develop new first-principles...

  12. Thermal Storage Power Balancing with Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2013-01-01

    . The total power consumption of all loads is controlled indirectly through a real-time price. The MPC incorporates forecasts of the power production and disturbances that influence the loads, e.g. time-varying weather forecasts, in order to react ahead of time. A simulation scenario demonstrates......The method described in this paper balances power production and consumption with a large number of thermal loads. Linear controllers are used for the loads to track a temperature set point, while Model Predictive Control (MPC) and model estimation of the load behavior are used for coordination...... that the method allows for the integration of flexible thermal loads in a smart energy system in which consumption follows the changing production....

  13. A statistical intercomparison of temperature and precipitation predicted by four general circulation models with historical data

    International Nuclear Information System (INIS)

    Grotch, S.L.

    1991-01-01

    This study is a detailed intercomparison of the results produced by four general circulation models (GCMs) that have been used to estimate the climatic consequences of a doubling of the CO 2 concentration. Two variables, surface air temperature and precipitation, annually and seasonally averaged, are compared for both the current climate and for the predicted equilibrium changes after a doubling of the atmospheric CO 2 concentration. The major question considered here is: how well do the predictions from different GCMs agree with each other and with historical climatology over different areal extents, from the global scale down to the range of only several gridpoints? Although the models often agree well when estimating averages over large areas, substantial disagreements become apparent as the spatial scale is reduced. At scales below continental, the correlations observed between different model predictions are often very poor. The implications of this work for investigation of climatic impacts on a regional scale are profound. For these two important variables, at least, the poor agreement between model simulations of the current climate on the regional scale calls into question the ability of these models to quantitatively estimate future climatic change on anything approaching the scale of a few (< 10) gridpoints, which is essential if these results are to be used in meaningful resource-assessment studies. A stronger cooperative effort among the different modeling groups will be necessary to assure that we are getting better agreement for the right reasons, a prerequisite for improving confidence in model projections. 11 refs.; 10 figs

  14. Predicting muscle fatigue: a response surface approximation based on proper generalized decomposition technique.

    Science.gov (United States)

    Sierra, M; Grasa, J; Muñoz, M J; Miana-Mena, F J; González, D

    2017-04-01

    A novel technique is proposed to predict force reduction in skeletal muscle due to fatigue under the influence of electrical stimulus parameters and muscle physiological characteristics. Twelve New Zealand white rabbits were divided in four groups ([Formula: see text]) to obtain the active force evolution of in vitro Extensor Digitorum Longus muscles for an hour of repeated contractions under different electrical stimulation patterns. Left and right muscles were tested, and a total of 24 samples were used to construct a response surface based in the proper generalized decomposition. After the response surface development, one additional rabbit was used to check the predictive potential of the technique. This multidimensional surface takes into account not only the decay of the maximum repeated peak force, but also the shape evolution of each contraction, muscle weight, electrical input signal and stimulation protocol. This new approach of the fatigue simulation challenge allows to predict, inside the multispace surface generated, the muscle response considering other stimulation patterns, different tissue weight, etc.

  15. Multivariate linear regression analysis to identify general factors for quantitative predictions of implant stability quotient values.

    Directory of Open Access Journals (Sweden)

    Hairong Huang

    Full Text Available This study identified potential general influencing factors for a mathematical prediction of implant stability quotient (ISQ values in clinical practice.We collected the ISQ values of 557 implants from 2 different brands (SICace and Osstem placed by 2 surgeons in 336 patients. Surgeon 1 placed 329 SICace implants, and surgeon 2 placed 113 SICace implants and 115 Osstem implants. ISQ measurements were taken at T1 (immediately after implant placement and T2 (before dental restoration. A multivariate linear regression model was used to analyze the influence of the following 11 candidate factors for stability prediction: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting, insertion torque, I-stage or II-stage healing pattern, implant diameter, implant length and T1-T2 time interval.The need for bone grafting as a predictor significantly influenced ISQ values in all three groups at T1 (weight coefficients ranging from -4 to -5. In contrast, implant diameter consistently influenced the ISQ values in all three groups at T2 (weight coefficients ranging from 3.4 to 4.2. Other factors, such as sex, age, I/II-stage implantation and bone type, did not significantly influence ISQ values at T2, and implant length did not significantly influence ISQ values at T1 or T2.These findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice.

  16. A statistical intercomparison of temperature and precipitation predicted by four general circulation models with historical data

    International Nuclear Information System (INIS)

    Grotch, S.L.

    1990-01-01

    This study is a detailed intercomparison of the results produced by four general circulation models (GCMs) that have been used to estimate the climatic consequences of a doubling of the CO 2 concentration. Two variables, surface air temperature and precipitation, annually and seasonally averaged, are compared for both the current climate and for the predicted equilibrium changes after a doubling of the atmospheric CO 2 concentration. The major question considered here is: how well do the predictions from different GCMs agree with each other and with historical climatology over different areal extents, from the global scale down to the range of only several gridpoints? Although the models often agree well when estimating averages over large areas, substantial disagreements become apparent as the spatial scale is reduced. At scales below continental, the correlations observed between different model predictions are often very poor. The implications of this work for investigation of climatic impacts on a regional scale are profound. For these two important variables, at least, the poor agreement between model simulations of the current climate on the regional scale calls into question the ability of these models to quantitatively estimate future climatic change on anything approaching the scale of a few (< 10) gridpoints, which is essential if these results are to be used in meaningful resource-assessment studies. A stronger cooperative effort among the different modeling groups will be necessary to assure that we are getting better agreement for the right reasons, a prerequisite for improving confidence in model projections

  17. Robust stability in constrained predictive control through the Youla parameterisations

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2011-01-01

    In this article we take advantage of the primary and dual Youla parameterisations to set up a soft constrained model predictive control (MPC) scheme. In this framework it is possible to guarantee stability in face of norm-bounded uncertainties. Under special conditions guarantees are also given...... for hard input constraints. In more detail, we parameterise the MPC predictions in terms of the primary Youla parameter and use this parameter as the on-line optimisation variable. The uncertainty is parameterised in terms of the dual Youla parameter. Stability can then be guaranteed through small gain...... arguments on the loop consisting of the primary and dual Youla parameter. This is included in the MPC optimisation as a constraint on the induced gain of the optimisation variable. We illustrate the method with a numerical simulation example....

  18. Robust stability in predictive control with soft constraints

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

    2010-01-01

    In this paper we take advantage of the primary and dual Youla parameterizations for setting up a soft constrained model predictive control (MPC) scheme for which stability is guaranteed in face of norm-bounded uncertainties. Under special conditions guarantees are also given for hard input...... constraints. In more detail, we parameterize the MPC predictions in terms of the primary Youla parameter and use this parameter as the online optimization variable. The uncertainty is parameterized in terms of the dual Youla parameter. Stability can then be guaranteed through small gain arguments on the loop...... consisting of the primary and dual Youla parameter. This is included in the MPC optimization as a constraint on the induced gain of the optimization variable. We illustrate the method with a numerical simulation example....

  19. Block factorization of step response model predictive control problems

    DEFF Research Database (Denmark)

    Kufoalor, D. K.M.; Frison, Gianluca; Imsland, L.

    2017-01-01

    implemented in the HPMPC framework, and the performance is evaluated through simulation studies. The results confirm that a computationally fast controller is achieved, compared to the traditional step response MPC scheme that relies on an explicit prediction formulation. Moreover, the tailored condensing......By introducing a stage-wise prediction formulation that enables the use of highly efficient quadratic programming (QP) solution methods, this paper expands the computational toolbox for solving step response MPC problems. We propose a novel MPC scheme that is able to incorporate step response data...... algorithm exhibits superior performance and produces solution times comparable to that achieved when using a condensing scheme for an equivalent (but much smaller) state-space model derived from first-principles. Implementation aspects necessary for high performance on embedded platforms are discussed...

  20. The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.

    Science.gov (United States)

    Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun

    2017-01-01

    Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.

  1. Does general movements quality in term infants predict cerebral palsy and milder forms of limited mobility at 6 years?

    Science.gov (United States)

    van Iersel, Patricia A M; Bakker, Saskia C M; Jonker, Arnold J H; Hadders-Algra, Mijna

    2016-12-01

    To evaluate in term infants associations between quality of general movements and developmental outcome in term infants at 6 years with either cerebral palsy (CP) or limited mobility without CP. Participants of this prospective study were 145 term infants (86 male, 59 female). Their general movements quality was assessed at 'writhing' and 'fidgety' general movements age (3wks and 13wks post term). The assessment at 6 years consisted of a neurological examination, including assessment of minor neurological dysfunction (MND), evaluation of mobility with the Movement Assessment Battery for Children, and of behaviour and learning problems with questionnaires. Definitely abnormal general movements at writhing age were not associated with CP, whereas definitely abnormal general movements at fidgety age were (sensitivity 60%; specificity 91%; positive predictive value 19%, negative predictive value 98%). In children without CP, general movements quality was not associated with limited mobility, but it was associated to a minor extent with MND. In term infants, definitely abnormal general movements at fidgety age do predict CP, but with lower accuracy than in preterm infants. General movements quality does not predict limited mobility in children without CP. The study supports suggestions that predictive value of general movements assessment in term infants is lower than that in preterm infants. © 2016 Mac Keith Press.

  2. Bridging the gap between the linear and nonlinear predictive control: Adaptations fo refficient building climate control

    Czech Academy of Sciences Publication Activity Database

    Pčolka, M.; Žáčeková, E.; Robinett, R.; Čelikovský, Sergej; Šebek, M.

    2016-01-01

    Roč. 53, č. 1 (2016), s. 124-138 ISSN 0967-0661 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Model predictive control * Identification for control * Building climatecontrol Subject RIV: BC - Control Systems Theory Impact factor: 2.602, year: 2016 http://library.utia.cas.cz/separaty/2016/TR/celikovsky-0460306.pdf

  3. Design of Smith-like Predictive Controller with Communication Delay Adaptation

    OpenAIRE

    Jasmin Velagic

    2008-01-01

    This paper addresses the design of predictive networked controller with adaptation of a communication delay. The networked control system contains random delays from sensor to controller and from controller to actuator. The proposed predictive controller includes an adaptation loop which decreases the influence of communication delay on the control performance. Also, the predictive controller contains a filter which improves the robustness of the control system. The perfo...

  4. Model predictive control for ethanol steam reformers with membrane separation

    OpenAIRE

    Serra, Maria; Ocampo-Martínez, Carlos; Li, Mingming; Llorca Piqué, Jordi

    2017-01-01

    © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This paper focuses on the dynamic modelling and the predictive control of an ethanol steam reformer (ESR) with Pdsingle bondAg membrane separation stage for the generation of pure hydrogen. Hydrogen purity necessary to feed a proton exchange membrane fuel cell (PEMFC) is required. A non-linear dynamic model of the ESR is developed together with a procedure f...

  5. Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

    2017-01-01

    This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...

  6. A LIDAR-assisted model predictive controller added on a traditional wind turbine controller

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Hansen, Morten Hartvig

    2016-01-01

    LIDAR-assisted collective pitch control shows promising results for load reduction in the full load operating region of horizontal axis wind turbines (WT). Utilizing LIDARs in WT control can be approached in different ways; One method is to design the WT controller from ground up based on the LIDAR...... measurements. Nevertheless, to make the LIDAR-assisted controller easily implementable on existing wind turbines, one can design a controller that is added to the original and existing WT controller. This add-on solution makes it easier to prove the applicability and performance of the LIDAR-assisted WT...... control and opens the market of retrofitting existing wind turbines with the new technology. In this paper, we suggest a model predictive controller (MPC) that is added to the basic gain scheduled PI controller of a WT to enhance the performance of the closed loop system using LIDAR measurements...

  7. Predictive Function Control for Communication-Based Train Control (CBTC Systems

    Directory of Open Access Journals (Sweden)

    Bing Bu

    2013-01-01

    Full Text Available In Communication-Based Train Control (CBTC systems, random transmission delays and packet drops are inevitable in the wireless networks, which could result in unnecessary traction, brakes or even emergency brakes of trains, losses of line capacity and passenger dissatisfaction. This paper applies predictive function control technology with a mixed H2/∞ control approach to improve the control performances. The controller is in the state feedback form and satisfies the requirement of quadratic input and state constraints. A linear matrix inequality (LMI approach is developed to solve the control problem. The proposed method attenuates disturbances by incorporating H2/∞ into the control scheme. The control command from the automatic train operation (ATO is included in the reward function to optimize the train's running profile. The influence of transmission delays and packet drops is alleviated through improving the performances of the controller. Simulation results show that the method is effective to improve the performances and robustness of CBTC systems.

  8. Artificial pancreas: model predictive control design from clinical experience.

    Science.gov (United States)

    Toffanin, Chiara; Messori, Mirko; Di Palma, Federico; De Nicolao, Giuseppe; Cobelli, Claudio; Magni, Lalo

    2013-11-01

    The objective of this research is to develop a new artificial pancreas that takes into account the experience accumulated during more than 5000 h of closed-loop control in several clinical research centers. The main objective is to reduce the mean glucose value without exacerbating hypo phenomena. Controller design and in silico testing were performed on a new virtual population of the University of Virginia/Padova simulator. A new sensor model was developed based on the Comparison of Two Artificial Pancreas Systems for Closed-Loop Blood Glucose Control versus Open-Loop Control in Patients with Type 1 Diabetes trial AP@home data. The Kalman filter incorporated in the controller has been tuned using plasma and pump insulin as well as plasma and continuous glucose monitoring measures collected in clinical research centers. New constraints describing clinical knowledge not incorporated in the simulator but very critical in real patients (e.g., pump shutoff) have been introduced. The proposed model predictive control (MPC) is characterized by a low computational burden and memory requirements, and it is ready for an embedded implementation. The new MPC was tested with an intensive simulation study on the University of Virginia/Padova simulator equipped with a new virtual population. It was also used in some preliminary outpatient pilot trials. The obtained results are very promising in terms of mean glucose and number of patients in the critical zone of the control variability grid analysis. The proposed MPC improves on the performance of a previous controller already tested in several experiments in the AP@home and JDRF projects. This algorithm complemented with a safety supervision module is a significant step toward deploying artificial pancreases into outpatient environments for extended periods of time. © 2013 Diabetes Technology Society.

  9. Model predictive control of a solar-thermal reactor

    Science.gov (United States)

    Saade Saade, Maria Elizabeth

    Solar-thermal reactors represent a promising alternative to fossil fuels because they can harvest solar energy and transform it into storable and transportable fuels. The operation of solar-thermal reactors is restricted by the available sunlight and its inherently transient behavior, which affects the performance of the reactors and limits their efficiency. Before solar-thermal reactors can become commercially viable, they need to be able to maintain a continuous high-performance operation, even in the presence of passing clouds. A well-designed control system can preserve product quality and maintain stable product compositions, resulting in a more efficient and cost-effective operation, which can ultimately lead to scale-up and commercialization of solar thermochemical technologies. In this work, we propose a model predictive control (MPC) system for a solar-thermal reactor for the steam-gasification of biomass. The proposed controller aims at rejecting the disturbances in solar irradiation caused by the presence of clouds. A first-principles dynamic model of the process was developed. The model was used to study the dynamic responses of the process variables and to identify a linear time-invariant model used in the MPC algorithm. To provide an estimation of the disturbances for the control algorithm, a one-minute-ahead direct normal irradiance (DNI) predictor was developed. The proposed predictor utilizes information obtained through the analysis of sky images, in combination with current atmospheric measurements, to produce the DNI forecast. In the end, a robust controller was designed capable of rejecting disturbances within the operating region. Extensive simulation experiments showed that the controller outperforms a finely-tuned multi-loop feedback control strategy. The results obtained suggest that our controller is suitable for practical implementation.

  10. Are the general equations to predict BMR applicable to patients with anorexia nervosa?

    Science.gov (United States)

    Marra, M; Polito, A; De Filippo, E; Cuzzolaro, M; Ciarapica, D; Contaldo, F; Scalfi, L

    2002-03-01

    To determine whether the general equations to predict basal metabolic rate (BMR) can be reliably applied to female anorectics. Two hundred and thirty-seven female patients with anorexia nervosa (AN) were divided into an adolescent group [n=43, 13-17 yrs, 39.3+/-5.0 kg, body mass index (BMI) (weight/height) 15.5+/-1.8 kg/m2] and a young-adult group (n=194, 18-40 yrs, 40.5+/-6.1 kg, BMI 15.6+/-1.9 kg/m2). BMR values determined by indirect calorimetry were compared with those predicted according to either the WHO/FAO/UNU or the Harris-Benedict general equations, or using the Schebendach correction formula (proposed for adjusting the Harris-Benedict estimates in anorectics). Measured BMR was 3,658+/-665 kJ/day in the adolescent and 3,907+/-760 kJ/day in the young-adult patients. In the adolescent group, the differences between predicted and measured values were (mean+/-SD) 1,466 529 kJ/day (+44+/-21%) for WHO/FAO/UNU, 1,587+/-552 kJ/day (+47+/-23%) for the Harris-Benedict and -20+/-510 kJ/day for the Schebendach (+1+/-13%), while in the young-adult group the corresponding values were 696+/-570 kJ/day (+24+/-24%), 1,252+/-644 kJ/day (+37+/-27%) and -430+/-640 kJ/day (-9+/-16%). The bias was negatively associated with weight and BMI in both groups when using the WHO/FAO/UNU and Harris-Benedict equations, and with age in the young-adult group for the Harris-Benedict and Schebendach equations. The WHO/FAO/UNU and Harris-Benedict equations greatly overestimate BMR in AN. Accurate estimation is to some extent dependent on individual characteristics such as age, weight or BMI. The Schebendach correction formula accurately predicts BMR in female adolescents, but not in young adult women with AN.

  11. Predictive and reinforcement learning for magneto-hydrodynamic control of hypersonic flows

    Science.gov (United States)

    Kulkarni, Nilesh Vijay

    Increasing needs for autonomy in future aerospace systems and immense progress in computing technology have motivated the development of on-line adaptive control techniques to account for modeling errors, changes in system dynamics, and faults occurring during system operation. After extensive treatment of the inner-loop adaptive control dealing mainly with stable adaptation towards desired transient behavior, adaptive optimal control has started receiving attention in literature. Motivated by the problem of optimal control of the magneto-hydrodynamic (MHD) generator at the inlet of the scramjet engine of a hypersonic flight vehicle, this thesis treats the general problem of efficiently combining off-line and on-line optimal control methods. The predictive control approach is chosen as the off-line method for designing optimal controllers using all the existing system knowledge. This controller is then adapted on-line using policy-iteration-based Q-learning, which is a stable model-free reinforcement learning approach. The combined approach is first illustrated in the optimal control of linear systems, which helps in the analysis as well as the validation of the method. A novel neural-networks-based parametric predictive control approach is then designed for the off-line optimal control of non-linear systems. The off-line approach is illustrated by applications to aircraft and spacecraft systems. This is followed by an extensive treatment of the off-line optimal control of the MHD generator using this neuro-control approach. On-line adaptation of the controller is implemented using several novel schemes derived from the policy-iteration-based Q-learning. The implementation results demonstrate the success of these on-line algorithms for adapting towards modeling errors in the off-line design.

  12. Predicting, monitoring and controlling geomechanical effects of CO2 injection

    International Nuclear Information System (INIS)

    Streit, J.E.; Siggins, A.F.

    2005-01-01

    A key objective of geological carbon dioxide (CO 2 ) storage in porous rock is long-term subsurface containment of CO 2 . Fault stability and maximum sustainable pore-fluid pressures should be estimated in geomechanical studies in order to avoid damage to reservoir seals and fault seals of storage sites during CO 2 injection. Such analyses rely on predicting the evolution of effective stresses in rocks and faults during CO 2 injection. However, geomechanical analyses frequently do not incorporate poroelastic behaviour of reservoir rock, as relevant poroelastic properties are rarely known. The knowledge of rock poroelastic properties would allow the use of seismic methods for the accurate measurement of the effective stress evolution during CO 2 injection. This paper discussed key geomechanical effects of CO 2 injection into porous rock, and in particular, focused on the effects that the poroelasticity of reservoir rocks and pore pressure/stress coupling have on effective stresses. Relevant geophysical monitoring techniques were also suggested. The paper also outlined how these techniques could be applied to measure stress changes related to poroelastic rock behaviour during CO 2 injection and to test the predictions of sustainable changes in effective stress in CO 2 storage sites. It was concluded that a combination of predictive geomechanical techniques and application of geophysical monitoring techniques is a valid new concept for controlling and monitoring the geomechanical effects of CO 2 storage. 36 refs., 5 figs

  13. Predictive mechanisms in the control of contour following.

    Science.gov (United States)

    Tramper, Julian J; Flanders, Martha

    2013-06-01

    In haptic exploration, when running a fingertip along a surface, the control system may attempt to anticipate upcoming changes in curvature in order to maintain a consistent level of contact force. Such predictive mechanisms are well known in the visual system, but have yet to be studied in the somatosensory system. Thus, the present experiment was designed to reveal human capabilities for different types of haptic prediction. A robot arm with a large 3D workspace was attached to the index fingertip and was programmed to produce virtual surfaces with curvatures that varied within and across trials. With eyes closed, subjects moved the fingertip around elliptical hoops with flattened regions or Limaçon shapes, where the curvature varied continuously. Subjects anticipated the corner of the flattened region rather poorly, but for the Limaçon shapes, they varied finger speed with upcoming curvature according to the two-thirds power law. Furthermore, although the Limaçon shapes were randomly presented in various 3D orientations, modulation of contact force also indicated good anticipation of upcoming changes in curvature. The results demonstrate that it is difficult to haptically anticipate the spatial location of an abrupt change in curvature, but smooth changes in curvature may be facilitated by anticipatory predictions.

  14. Model Predictive Control-Based Fast Charging for Vehicular Batteries

    Directory of Open Access Journals (Sweden)

    Zhibin Song

    2011-08-01

    Full Text Available Battery fast charging is one of the most significant and difficult techniques affecting the commercialization of electric vehicles (EVs. In this paper, we propose a fast charge framework based on model predictive control, with the aim of simultaneously reducing the charge duration, which represents the out-of-service time of vehicles, and the increase in temperature, which represents safety and energy efficiency during the charge process. The RC model is employed to predict the future State of Charge (SOC. A single mode lumped-parameter thermal model and a neural network trained by real experimental data are also applied to predict the future temperature in simulations and experiments respectively. A genetic algorithm is then applied to find the best charge sequence under a specified fitness function, which consists of two objectives: minimizing the charging duration and minimizing the increase in temperature. Both simulation and experiment demonstrate that the Pareto front of the proposed method dominates that of the most popular constant current constant voltage (CCCV charge method.

  15. General prognostic scores in outcome prediction for cancer patients admitted to the intensive care unit.

    Science.gov (United States)

    Kopterides, Petros; Liberopoulos, Panayiotis; Ilias, Ioannis; Anthi, Anastasia; Pragkastis, Dimitrios; Tsangaris, Iraklis; Tsaknis, Georgios; Armaganidis, Apostolos; Dimopoulou, Ioanna

    2011-01-01

    Intensivists and nursing staff are often reluctant to admit patients with cancer to the intensive care unit even though these patients' survival rate has improved since the 1980s. To identify factors associated with mortality in cancer patients admitted to the intensive care unit and to assess and compare the effectiveness of 3 general prognostic models: the Acute Physiology and Chronic Health Evaluation (APACHE) II, the Simplified Acute Physiology Score (SAPS II), and the Sequential Organ Failure Assessment (SOFA). A prospective observational cohort study was performed in 2 general intensive care units. Discrimination was assessed by using area under the receiver operating characteristic curves, and calibration was evaluated by using Hosmer-Lemeshow goodness-of-fit tests. A total of 126 patients were included during a 3-year period. The observed mortality was 46.8%. All 3 general models showed excellent discrimination (area under the curve >0.8) and good calibration (P = .17, .14, and .22 for APACHE II, SAPS II, and SOFA, respectively). However, discrimination was significantly better with APACHE II scores than with SOFA scores (P = .02). Multivariate analyses indicated that independent of the 3 severity-of-illness scores, unfavorable risk factors for mortality included a patient's preadmission performance status, source of admission (internal medicine vs surgery department), and the presence of septic shock, infection, or anemia. Combining SOFA and SAPS II scores with these variables created prognostic models with improved calibration and discrimination. The general prognostic models seem fairly accurate in the prediction of mortality in critically ill cancer patients in the intensive care unit.

  16. Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control

    DEFF Research Database (Denmark)

    Guo, Yifei; Gao, Houlei; Wu, Qiuwei

    2018-01-01

    This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well...... as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active power outputs of WTGs on voltage control are also taken into consideration. The predictive model of VSC...... with a typical cascaded control structure is derived in details. The sensitivity coefficients are calculated by an analytical method to improve the computational efficiency. A VSC-HVDC connected OWF with 64 WTGs was used to validate the proposed voltage control strategy....

  17. Predictive Solar-Integrated Commercial Building Load Control

    Energy Technology Data Exchange (ETDEWEB)

    Glasgow, Nathan [EdgePower Inc., Aspen, CO (United States)

    2017-01-31

    This report is the final technical report for the Department of Energy SunShot award number EE0007180 to EdgePower Inc., for the project entitled “Predictive Solar-Integrated Commercial Building Load Control.” The goal of this project was to successfully prove that the integration of solar forecasting and building load control can reduce demand charge costs for commercial building owners with solar PV. This proof of concept Tier 0 project demonstrated its value through a pilot project at a commercial building. This final report contains a summary of the work completed through he duration of the project. Clean Power Research was a sub-recipient on the award.

  18. Demand Management Based on Model Predictive Control Techniques

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2014-01-01

    Full Text Available Demand management (DM is the process that helps companies to sell the right product to the right customer, at the right time, and for the right price. Therefore the challenge for any company is to determine how much to sell, at what price, and to which market segment while maximizing its profits. DM also helps managers efficiently allocate undifferentiated units of capacity to the available demand with the goal of maximizing revenue. This paper introduces control system approach to demand management with dynamic pricing (DP using the model predictive control (MPC technique. In addition, we present a proper dynamical system analogy based on active suspension and a stability analysis is provided via the Lyapunov direct method.

  19. Predictive current control of permanent magnet synchronous motor based on linear active disturbance rejection control

    Science.gov (United States)

    Li, Kunpeng

    2017-01-01

    The compatibility problem between rapidity and overshooting in the traditional predictive current control structure is inevitable and difficult to solve by reason of using PI controller. A novel predictive current control (PCC) algorithm for permanent magnet synchronous motor (PMSM) based on linear active disturbance rejection control (LADRC) is presented in this paper. In order to displace PI controller, the LADRC strategy which consisted of linear state error feedback (LSEF) control algorithm and linear extended state observer (LESO), is designed based on the mathematic model of PMSM. The purpose of LSEF is to make sure fast response to load mutation and system uncertainties, and LESO is designed to estimate the uncertain disturbances. The principal structures of the proposed system are speed outer loop based on LADRC and current inner loop based on predictive current control. Especially, the instruction value of qaxis current in inner loop is derived from the control quantity which is designed in speed outer loop. The simulation is carried out in Matlab/Simulink software, and the results illustrate that the dynamic and static performances of proposed system are satisfied. Moreover the robust against model parameters mismatch is enhanced obviously.

  20. Model predictive control-based efficient energy recovery control strategy for regenerative braking system of hybrid electric bus

    International Nuclear Information System (INIS)

    Li, Liang; Zhang, Yuanbo; Yang, Chao; Yan, Bingjie; Marina Martinez, C.

    2016-01-01

    Highlights: • A 7-degree-of-freedom model of hybrid electric vehicle with regenerative braking system is built. • A modified nonlinear model predictive control strategy is developed. • The particle swarm optimization algorithm is employed to solve the optimization problem. • The proposed control strategy is verified by simulation and hardware-in-loop tests. • Test results verify the effectiveness of the proposed control strategy. - Abstract: As one of the main working modes, the energy recovered with regenerative braking system provides an effective approach so as to greatly improve fuel economy of hybrid electric bus. However, it is still a challenging issue to ensure braking stability while maximizing braking energy recovery. To solve this problem, an efficient energy recovery control strategy is proposed based on the modified nonlinear model predictive control method. Firstly, combined with the characteristics of the compound braking process of single-shaft parallel hybrid electric bus, a 7 degrees of freedom model of the vehicle longitudinal dynamics is built. Secondly, considering nonlinear characteristic of the vehicle model and the efficiency of regenerative braking system, the particle swarm optimization algorithm within the modified nonlinear model predictive control is adopted to optimize the torque distribution between regenerative braking system and pneumatic braking system at the wheels. So as to reduce the computational time of modified nonlinear model predictive control, a nearest point method is employed during the braking process. Finally, the simulation and hardware-in-loop test are carried out on road conditions with different tire–road adhesion coefficients, and the proposed control strategy is verified by comparing it with the conventional control method employed in the baseline vehicle controller. The simulation and hardware-in-loop test results show that the proposed strategy can ensure vehicle safety during emergency braking

  1. Nurse practitioners substituting for general practitioners: randomized controlled trial.

    Science.gov (United States)

    Dierick-van Daele, Angelique T M; Metsemakers, Job F M; Derckx, Emmy W C C; Spreeuwenberg, Cor; Vrijhoef, Hubertus J M

    2009-02-01

    This paper is a report of a study conducted to evaluate process and outcomes of care provided to patients with common complaints by general practitioners or specially trained nurse practitioners as first point of contact. Studies in the United States of America and Great Britain show that substituting nurse practitioners for general practitioners results in higher patient satisfaction and higher quality of care. As the American and British healthcare system and settings differ from that in The Netherlands, a Dutch trial was conducted. A total of 1501 patients in 15 general practices were randomized to consultation by a general practitioner or a nurse practitioner. Data were collected over a 6-month period in 2006 by means of questionnaires, extracting medical records from practice computer systems and recording the length of consultations. In both groups, the patients highly appreciated the quality of care. No statistically significant differences were found in health status, medical resource consumption and compliance of practical guidelines in primary care in The Netherlands. Patients in the NP intervention group were more often invited to re-attend, had more follow-up consultations and their consultations took statistically significantly longer. Nurse practitioners and general practitioners provide comparable care. Our findings support an increased involvement of specially trained nurse practitioners in the Dutch primary care and contribute to knowledge of the effectiveness of care provision by nurse practitioners from a national and international perspective.

  2. General Quality Control (QC) Guidelines for SAM Methods

    Science.gov (United States)

    Learn more about quality control guidelines and recommendations for the analysis of samples using the methods listed in EPA's Selected Analytical Methods for Environmental Remediation and Recovery (SAM).

  3. Prediction of radio frequency power generation of Neptune's magnetosphere from generalized radiometric Bode's law

    Science.gov (United States)

    Million, M. A.; Goertz, C. K.

    1988-01-01

    Magnetospheric radio frequency emission power has been shown to vary as a function of both solar wind and planetary values such as magnetic field by Kaiser and Desch (1984). Planetary magnetic fields have been shown to scale with planetary variables such as density and angular momentum by numerous researchers. This paper combines two magnetic scaling laws with the radiometric law to yield 'Bode's'-type laws governing planetary radio emissions. Further analysis allows the reduction of variables to planetary mass and orbital distance. These generalized laws are then used to predict the power otuput of Neptune to be about 1.6 x 10 to the 7th W; with the intensity peaking at about 3 MHz.

  4. Prediction of chronic critical illness in a general intensive care unit

    Directory of Open Access Journals (Sweden)

    Sérgio H. Loss

    2013-06-01

    Full Text Available OBJECTIVE: To assess the incidence, costs, and mortality associated with chronic critical illness (CCI, and to identify clinical predictors of CCI in a general intensive care unit. METHODS: This was a prospective observational cohort study. All patients receiving supportive treatment for over 20 days were considered chronically critically ill and eligible for the study. After applying the exclusion criteria, 453 patients were analyzed. RESULTS: There was an 11% incidence of CCI. Total length of hospital stay, costs, and mortality were significantly higher among patients with CCI. Mechanical ventilation, sepsis, Glasgow score < 15, inadequate calorie intake, and higher body mass index were independent predictors for cci in the multivariate logistic regression model. CONCLUSIONS: CCI affects a distinctive population in intensive care units with higher mortality, costs, and prolonged hospitalization. Factors identifiable at the time of admission or during the first week in the intensive care unit can be used to predict CCI.

  5. Prediction of chronic critical illness in a general intensive care unit.

    Science.gov (United States)

    Loss, Sérgio H; Marchese, Cláudia B; Boniatti, Márcio M; Wawrzeniak, Iuri C; Oliveira, Roselaine P; Nunes, Luciana N; Victorino, Josué A

    2013-01-01

    To assess the incidence, costs, and mortality associated with chronic critical illness (CCI), and to identify clinical predictors of CCI in a general intensive care unit. This was a prospective observational cohort study. All patients receiving supportive treatment for over 20 days were considered chronically critically ill and eligible for the study. After applying the exclusion criteria, 453 patients were analyzed. There was an 11% incidence of CCI. Total length of hospital stay, costs, and mortality were significantly higher among patients with CCI. Mechanical ventilation, sepsis, Glasgow score intensive care units with higher mortality, costs, and prolonged hospitalization. Factors identifiable at the time of admission or during the first week in the intensive care unit can be used to predict CCI. Copyright © 2013 Elsevier Editora Ltda. All rights reserved.

  6. Serum soluble CD163 predicts risk of type 2 diabetes in the general population

    DEFF Research Database (Denmark)

    Møller, Holger J; Frikke-Schmidt, Ruth; Moestrup, Søren K

    2011-01-01

    has developed. METHODS: A prospective cohort study of 8849 study participants from the general population, the Copenhagen City Heart Study, was followed for 18 years for incidence of type 2 diabetes. Risk of disease was calculated according to age- and sex-adjusted percentile categories of serum s......%-33% category. In overweight men 50-70 and >70 years of age, serum sCD163 concentrations in the top 5% group predicted an absolute 10-year risk of type 2 diabetes of 29% and 36% vs 7% and 8% in the lowest percentile group. Equivalent values in women were 19% and 24% vs 4% and 5%. CONCLUSIONS: Increased......BACKGROUND: Activation of adipose tissue macrophages with concomitant low-grade inflammation is believed to play a central role in the development of type 2 diabetes. We tested whether a new macrophage-derived biomarker, soluble CD163 (sCD163), identifies at-risk individuals before overt disease...

  7. Predictive Control, Competitive Model Business Planning, and Innovation ERP

    DEFF Research Database (Denmark)

    Nourani, Cyrus F.; Lauth, Codrina

    2015-01-01

    New optimality principles are put forth based on competitive model business planning. A Generalized MinMax local optimum dynamic programming algorithm is presented and applied to business model computing where predictive techniques can determine local optima. Based on a systems model an enterprise...... is not viewed as the sum of its component elements, but the product of their interactions. The paper starts with introducing a systems approach to business modeling. A competitive business modeling technique, based on the author's planning techniques is applied. Systemic decisions are based on common...... organizational goals, and as such business planning and resource assignments should strive to satisfy higher organizational goals. It is critical to understand how different decisions affect and influence one another. Here, a business planning example is presented where systems thinking technique, using Causal...

  8. General

    Indian Academy of Sciences (India)

    Page S20: NMR compound 4i. Page S22: NMR compound 4j. General: Chemicals were purchased from Fluka, Merck and Aldrich Chemical Companies. All the products were characterized by comparison of their IR, 1H NMR and 13C NMR spectroscopic data and their melting points with reported values. General procedure ...

  9. Prostate-specific antigen and long-term prediction of prostate cancer incidence and mortality in the general population

    DEFF Research Database (Denmark)

    Orsted, David D; Nordestgaard, Børge G; Jensen, Gorm B

    2012-01-01

    It is largely unknown whether prostate-specific antigen (PSA) level at first date of testing predicts long-term risk of prostate cancer (PCa) incidence and mortality in the general population.......It is largely unknown whether prostate-specific antigen (PSA) level at first date of testing predicts long-term risk of prostate cancer (PCa) incidence and mortality in the general population....

  10. Developing a methodology to predict PM10 concentrations in urban areas using generalized linear models.

    Science.gov (United States)

    Garcia, J M; Teodoro, F; Cerdeira, R; Coelho, L M R; Kumar, Prashant; Carvalho, M G

    2016-09-01

    A methodology to predict PM10 concentrations in urban outdoor environments is developed based on the generalized linear models (GLMs). The methodology is based on the relationship developed between atmospheric concentrations of air pollutants (i.e. CO, NO2, NOx, VOCs, SO2) and meteorological variables (i.e. ambient temperature, relative humidity (RH) and wind speed) for a city (Barreiro) of Portugal. The model uses air pollution and meteorological data from the Portuguese monitoring air quality station networks. The developed GLM considers PM10 concentrations as a dependent variable, and both the gaseous pollutants and meteorological variables as explanatory independent variables. A logarithmic link function was considered with a Poisson probability distribution. Particular attention was given to cases with air temperatures both below and above 25°C. The best performance for modelled results against the measured data was achieved for the model with values of air temperature above 25°C compared with the model considering all ranges of air temperatures and with the model considering only temperature below 25°C. The model was also tested with similar data from another Portuguese city, Oporto, and results found to behave similarly. It is concluded that this model and the methodology could be adopted for other cities to predict PM10 concentrations when these data are not available by measurements from air quality monitoring stations or other acquisition means.

  11. RoboCon: A general purpose telerobotic control center

    International Nuclear Information System (INIS)

    Draper, J.V.; Noakes, M.W.; Blair, L.M.

    1997-01-01

    This report describes human factors issues involved in the design of RoboCon, a multi-purpose control center for use in US Department of Energy remote handling applications. RoboCon is intended to be a flexible, modular control center capable of supporting a wide variety of robotic devices

  12. Exact Boundary Controllability of Electromagnetic Fields in a General Region

    International Nuclear Information System (INIS)

    Eller, M. M.; Masters, J. E.

    2002-01-01

    We prove exact controllability for Maxwell's system with variable coefficients in a bounded domain by a current flux in the boundary. The proof relies on a duality argument which reduces the proof of exact controllability to the proof of continuous observability for the homogeneous adjoint system. There is no geometric restriction imposed on the domain

  13. RoboCon: A general purpose telerobotic control center

    Energy Technology Data Exchange (ETDEWEB)

    Draper, J.V.; Noakes, M.W. [Oak Ridge National Lab., TN (United States). Robotics and Process Systems Div.; Schempf, H. [Carnegie Mellon Univ., Pittsburgh, PA (United States); Blair, L.M. [Human Machine Interfaces, Inc., Knoxville, TN (United States)

    1997-02-01

    This report describes human factors issues involved in the design of RoboCon, a multi-purpose control center for use in US Department of Energy remote handling applications. RoboCon is intended to be a flexible, modular control center capable of supporting a wide variety of robotic devices.

  14. General model and control of an n rotor helicopter

    DEFF Research Database (Denmark)

    Sidea, Adriana-Gabriela; Brogaard, Rune Yding; Andersen, Nils Axel

    2015-01-01

    The purpose of this study was to create a dynamic, nonlinear mathematical model ofa multirotor that would be valid for different numbers of rotors. Furthermore, a set of SingleInput Single Output (SISO) controllers were implemented for attitude control. Both model andcontrollers were tested...

  15. General-purpose microprocessor-based control chassis

    International Nuclear Information System (INIS)

    Halbig, J.K.; Klosterbuer, S.F.; Swenson, D.A.

    1979-12-01

    The objective of the Pion Generation for Medical Irradiations (PIGMI) program at the Los Alamos Scientific Laboratory is to develop the technology to build smaller, less expensive, and more reliable proton linear accelerators for medical applications. For this program, a powerful, simple, inexpensive, and reliable control and data acquisition system was developed. The system has a NOVA 3D computer with a real time disk-operating system (RDOS) that communicates with distributed microprocessor-based controllers which directly control data input/output chassis. At the heart of the controller is a microprocessor crate which was conceived at the Fermi National Accelerator Laboratory. This idea was applied to the design of the hardware and software of the controller

  16. Study on noise prediction model and control schemes for substation.

    Science.gov (United States)

    Chen, Chuanmin; Gao, Yang; Liu, Songtao

    2014-01-01

    With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods.

  17. Study on Noise Prediction Model and Control Schemes for Substation

    Science.gov (United States)

    Gao, Yang; Liu, Songtao

    2014-01-01

    With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods. PMID:24672356

  18. Design and Performance Analysis of Incremental Networked Predictive Control Systems.

    Science.gov (United States)

    Pang, Zhong-Hua; Liu, Guo-Ping; Zhou, Donghua

    2016-06-01

    This paper is concerned with the design and performance analysis of networked control systems with network-induced delay, packet disorder, and packet dropout. Based on the incremental form of the plant input-output model and an incremental error feedback control strategy, an incremental networked predictive control (INPC) scheme is proposed to actively compensate for the round-trip time delay resulting from the above communication constraints. The output tracking performance and closed-loop stability of the resulting INPC system are considered for two cases: 1) plant-model match case and 2) plant-model mismatch case. For the former case, the INPC system can achieve the same output tracking performance and closed-loop stability as those of the corresponding local control system. For the latter case, a sufficient condition for the stability of the closed-loop INPC system is derived using the switched system theory. Furthermore, for both cases, the INPC system can achieve a zero steady-state output tracking error for step commands. Finally, both numerical simulations and practical experiments on an Internet-based servo motor system illustrate the effectiveness of the proposed method.

  19. Prediction models and control algorithms for predictive applications of setback temperature in cooling systems

    International Nuclear Information System (INIS)

    Moon, Jin Woo; Yoon, Younju; Jeon, Young-Hoon; Kim, Sooyoung

    2017-01-01

    Highlights: • Initial ANN model was developed for predicting the time to the setback temperature. • Initial model was optimized for producing accurate output. • Optimized model proved its prediction accuracy. • ANN-based algorithms were developed and tested their performance. • ANN-based algorithms presented superior thermal comfort or energy efficiency. - Abstract: In this study, a temperature control algorithm was developed to apply a setback temperature predictively for the cooling system of a residential building during occupied periods by residents. An artificial neural network (ANN) model was developed to determine the required time for increasing the current indoor temperature to the setback temperature. This study involved three phases: development of the initial ANN-based prediction model, optimization and testing of the initial model, and development and testing of three control algorithms. The development and performance testing of the model and algorithm were conducted using TRNSYS and MATLAB. Through the development and optimization process, the final ANN model employed indoor temperature and the temperature difference between the current and target setback temperature as two input neurons. The optimal number of hidden layers, number of neurons, learning rate, and moment were determined to be 4, 9, 0.6, and 0.9, respectively. The tangent–sigmoid and pure-linear transfer function was used in the hidden and output neurons, respectively. The ANN model used 100 training data sets with sliding-window method for data management. Levenberg-Marquart training method was employed for model training. The optimized model had a prediction accuracy of 0.9097 root mean square errors when compared with the simulated results. Employing the ANN model, ANN-based algorithms maintained indoor temperatures better within target ranges. Compared to the conventional algorithm, the ANN-based algorithms reduced the duration of time, in which the indoor temperature

  20. Model-free adaptive sliding mode controller design for generalized ...

    Indian Academy of Sciences (India)

    To solve the difficulties from the little knowledge about the master–slave system and to overcome the bad effects of the external disturbances on the generalized projective synchronization, the radial basis function neural networks are used to approach the packaged unknown master system and the packaged unknown ...

  1. Model-free adaptive sliding mode controller design for generalized ...

    Indian Academy of Sciences (India)

    L M WANG

    2017-08-16

    Aug 16, 2017 ... Abstract. A novel model-free adaptive sliding mode strategy is proposed for a generalized projective synchronization (GPS) between two entirely unknown fractional-order chaotic systems subject to the external disturbances. To solve the difficulties from the little knowledge about the master–slave system ...

  2. Design and Application of Offset-Free Model Predictive Control Disturbance Observation Method

    Directory of Open Access Journals (Sweden)

    Xue Wang

    2016-01-01

    Full Text Available Model predictive control (MPC with its lower request to the mathematical model, excellent control performance, and convenience online calculation has developed into a very important subdiscipline with rich theory foundation and practical application. However, unmeasurable disturbance is widespread in industrial processes, which is difficult to deal with directly at present. In most of the implemented MPC strategies, the method of incorporating a constant output disturbance into the process model is introduced to solve this problem, but it fails to achieve offset-free control once the unmeasured disturbances access the process. Based on the Kalman filter theory, the problem is solved by using a more general disturbance model which is superior to the constant output disturbance model. This paper presents the necessary conditions for offset-free model predictive control based on the model. By applying disturbance model, the unmeasurable disturbance vectors are augmented as the states of control system, and the Kalman filer is used to estimate unmeasurable disturbance and its effect on the output. Then, the dynamic matrix control (DMC algorithm is improved by utilizing the feed-forward compensation control strategy with the disturbance estimated.

  3. Non linear predictive control of a LEGO mobile robot

    Science.gov (United States)

    Merabti, H.; Bouchemal, B.; Belarbi, K.; Boucherma, D.; Amouri, A.

    2014-10-01

    Metaheuristics are general purpose heuristics which have shown a great potential for the solution of difficult optimization problems. In this work, we apply the meta heuristic, namely particle swarm optimization, PSO, for the solution of the optimization problem arising in NLMPC. This algorithm is easy to code and may be considered as alternatives for the more classical solution procedures. The PSO- NLMPC is applied to control a mobile robot for the tracking trajectory and obstacles avoidance. Experimental results show the strength of this approach.

  4. TACO: a general-purpose tool for predicting cell-type-specific transcription factor dimers.

    Science.gov (United States)

    Jankowski, Aleksander; Prabhakar, Shyam; Tiuryn, Jerzy

    2014-03-19

    Cooperative binding of transcription factor (TF) dimers to DNA is increasingly recognized as a major contributor to binding specificity. However, it is likely that the set of known TF dimers is highly incomplete, given that they were discovered using ad hoc approaches, or through computational analyses of limited datasets. Here, we present TACO (Transcription factor Association from Complex Overrepresentation), a general-purpose standalone software tool that takes as input any genome-wide set of regulatory elements and predicts cell-type-specific TF dimers based on enrichment of motif complexes. TACO is the first tool that can accommodate motif complexes composed of overlapping motifs, a characteristic feature of many known TF dimers. Our method comprehensively outperforms existing tools when benchmarked on a reference set of 29 known dimers. We demonstrate the utility and consistency of TACO by applying it to 152 DNase-seq datasets and 94 ChIP-seq datasets. Based on these results, we uncover a general principle governing the structure of TF-TF-DNA ternary complexes, namely that the flexibility of the complex is correlated with, and most likely a consequence of, inter-motif spacing.

  5. Improving the predictive accuracy of hurricane power outage forecasts using generalized additive models.

    Science.gov (United States)

    Han, Seung-Ryong; Guikema, Seth D; Quiring, Steven M

    2009-10-01

    Electric power is a critical infrastructure service after hurricanes, and rapid restoration of electric power is important in order to minimize losses in the impacted areas. However, rapid restoration of electric power after a hurricane depends on obtaining the necessary resources, primarily repair crews and materials, before the hurricane makes landfall and then appropriately deploying these resources as soon as possible after the hurricane. This, in turn, depends on having sound estimates of both the overall severity of the storm and the relative risk of power outages in different areas. Past studies have developed statistical, regression-based approaches for estimating the number of power outages in advance of an approaching hurricane. However, these approaches have either not been applicable for future events or have had lower predictive accuracy than desired. This article shows that a different type of regression model, a generalized additive model (GAM), can outperform the types of models used previously. This is done by developing and validating a GAM based on power outage data during past hurricanes in the Gulf Coast region and comparing the results from this model to the previously used generalized linear models.

  6. General man-machine interface used in accelerators controls

    International Nuclear Information System (INIS)

    Boutheon, M.; Di Maio, F.; Pace, A.

    1992-01-01

    A large community is now using Workstations as Accelerators Computer Controls Interface, through the concepts of windows - menus - synoptics - icons. Some standards were established for the CERN-PS control systems rejuvenation. The Booster-to-PS transfer and injection process is now entirely operated with these tools. This application constitutes a global environment providing the users with the controls, analysis, visualization of a part of an accelerator. Individual commands, measurements, and specialized programs including complex treatments are available in a homogeneous frame. Some months of experience in current operation have shown that this model can be extended to the whole project. (author)

  7. General problems of dynamics and control of vibratory gyroscopes

    CSIR Research Space (South Africa)

    Shatalov, MY

    2008-05-01

    Full Text Available resonator gyroscope. The foundations of feedback control in the gyroscopes are considered and classification of the main operational regimes is given in terms of the integral manifolds and new classes of nonlinear parametric excitation forces are added...

  8. Predictability of 2-year La Niña events in a coupled general circulation model

    Science.gov (United States)

    DiNezio, Pedro N.; Deser, Clara; Okumura, Yuko; Karspeck, Alicia

    2017-12-01

    The predictability of the duration of La Niña is assessed using the Community Earth System Model Version 1 (CESM1), a coupled climate model capable of simulating key features of the El Niño/Southern Oscillation (ENSO) phenomenon, including the multi-year duration of La Niña. Statistical analysis of a 1800 year long control simulation indicates that a strong thermocline discharge or a strong El Niño can lead to La Niña conditions that last 2 years (henceforth termed 2-year LN). This relationship suggest that 2-year LN maybe predictable 18 to 24 months in advance. Perfect model forecasts performed with CESM1 are used to further explore the link between 2-year LN and the "Discharge" and "Peak El Niño" predictors. Ensemble forecasts are initialized on January and July coinciding with ocean states characterized by peak El Niño amplitudes and peak thermocline discharge respectively. Three cases with different magnitudes of these predictors are considered resulting in a total of six ensembles. Each "Peak El Niño" and "Discharge" ensemble forecast consists of 30 or 20 members respectively, generated by adding a infinitesimally small perturbation to the atmospheric initial conditions unique to each member. The forecasts show that the predictability of 2-year LN, measured by the potential prediction utility (PPU) of the Niño-3.4 SST index during the second year, is related to the magnitude of the initial conditions. Forecasts initialized with strong thermocline discharge or strong peak El Niño amplitude show higher PPU than those with initial conditions of weaker magnitude. Forecasts initialized from states characterized by weaker predictors are less predictable, mainly because the ensemble-mean signal is smaller, and therefore PPU is reduced due to the influence of forecast spread. The error growth of the forecasts, measured by the spread of the Niño-3.4 SST index, is independent of the initial conditions and appears to be driven by wind variability over the

  9. Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control

    OpenAIRE

    Guo, Yifei; Gao, Houlei; Wu, Qiuwei; Zhao, Haoran; Østergaard, Jacob; Shahidehpour, Mohammad

    2018-01-01

    This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active po...

  10. Wave Disturbance Reduction of a Floating Wind Turbine Using a Reference Model-based Predictive Control

    DEFF Research Database (Denmark)

    Christiansen, Søren; Tabatabaeipour, Seyed Mojtaba; Bak, Thomas

    2013-01-01

    a controller designed for an onshore wind turbine yields instability in the fore-aft rotation. In this paper, we propose a general framework, where a reference model models the desired closed-loop behavior of the system. Model predictive control combined with a state estimator finds the optimal rotor blade...... pitch such that the state trajectories of the controlled system tracks the reference trajectories. The framework is demonstrated with a reference model of the desired closed-loop system undisturbed by the incident waves. This allows the wave-induced motion of the platform to be damped significantly...... compared to a baseline floating wind turbine controller at the cost of more pitch action....

  11. Model Predictive Control for Flexible Power Consumption of Large-Scale Refrigeration Systems

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Stoustrup, Jakob; Rasmussen, Henrik

    2014-01-01

    A model predictive control (MPC) scheme is introduced to directly control the electrical power consumption of large-scale refrigeration systems. Deviation from the baseline of the consumption is corresponded to the storing and delivering of thermal energy. By virtue of such correspondence......, the control method can be employed for regulating power services in the smart grid. The proposed scheme contains the control of cooling capacity as well as optimizing the efficiency factor of the system, which is in general a nonconvex optimization problem. By introducing a fictitious manipulated variable......, and novel incorporation of the evaporation temperature set-point into optimization problem, the convex optimization problem is formulated within the MPC scheme. The method is applied to a simulation benchmark of large-scale refrigeration systems including several medium and low temperature cold reservoirs....

  12. Scheduled asthma management in general practice generally improve asthma control in those who attend

    DEFF Research Database (Denmark)

    Backer, Vibeke; Bornemann, Maja; Knudsen, Anja Dorte Brandt

    2012-01-01

    Successful asthma management involves guideline-based treatment and regular follow-up. We aimed to study the level of disease control in asthmatic individuals managed by their GP and a dedicated nurse when using a systematic asthma consultation guide based on Global Initiative of Asthma guidelines...

  13. Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

    Science.gov (United States)

    McMillan, Michelle L.; Mackie, Scott A.; Gissen, Abe; Vukasinovic, Bojan; Lakebrink, Matthew T.; Glezer, Ari; Mani, Mori; Mace, James L.

    2011-01-01

    Fail-safe, hybrid, flow control (HFC) is a promising technology for meeting high-speed cruise efficiency, low-noise signature, and reduced fuel-burn goals for future, Hybrid-Wing-Body (HWB) aircraft with embedded engines. This report details the development of HFC technology that enables improved inlet performance in HWB vehicles with highly integrated inlets and embedded engines without adversely affecting vehicle performance. In addition, new test techniques for evaluating Boundary-Layer-Ingesting (BLI)-inlet flow-control technologies developed and demonstrated through this program are documented, including the ability to generate a BLI-like inlet-entrance flow in a direct-connect, wind-tunnel facility, as well as, the use of D-optimal, statistically designed experiments to optimize test efficiency and enable interpretation of results. Validated improvements in numerical analysis tools and methods accomplished through this program are also documented, including Reynolds-Averaged Navier-Stokes CFD simulations of steady-state flow physics for baseline, BLI-inlet diffuser flow, as well as, that created by flow-control devices. Finally, numerical methods were employed in a ground-breaking attempt to directly simulate dynamic distortion. The advances in inlet technologies and prediction tools will help to meet and exceed "N+2" project goals for future HWB aircraft.

  14. Outdoor flocking of quadcopter drones with decentralized model predictive control.

    Science.gov (United States)

    Yuan, Quan; Zhan, Jingyuan; Li, Xiang

    2017-11-01

    In this paper, we present a multi-drone system featured with a decentralized model predictive control (DMPC) flocking algorithm. The drones gather localized information from neighbors and update their velocities using the DMPC flocking algorithm. In the multi-drone system, data packages are transmitted through XBee ® wireless modules in broadcast mode, yielding such an anonymous and decentralized system where all the calculations and controls are completed on an onboard minicomputer of each drone. Each drone is a double-layered agent system with the coordination layer running multi-drone flocking algorithms and the flight control layer navigating the drone, and the final formation of the flock relies on both the communication range and the desired inter-drone distance. We give both numerical simulations and field tests with a flock of five drones, showing that the DMPC flocking algorithm performs well on the presented multi-drone system in both the convergence rate and the ability of tracking a desired path. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Left ventricular filling pressure by septal and lateral E/e' equally predict cardiovascular events in the general population

    DEFF Research Database (Denmark)

    Wang, Joanna Nan; Biering-Sørensen, Tor; Jørgensen, Peter Godsk

    2017-01-01

    PURPOSE: There exists no consensus on the site of E/e' measurement. This study aimed to evaluate the predictive value of septal and lateral E/e' along with the importance of their intra-individual difference. METHODS: In 1775 persons from the general population, peak early diastolic velocity (e...... no predictive value (p = 0.79). E/e'septal was generally higher than E/e'lateral, thus age- and sex-specific normal values were reported for both sites for a population free of cardiac events during 10 years of follow-up. CONCLUSIONS: Septal and lateral E/e' are equally useful in predicting cardiac events...... in the general population. Measuring both sites provides no further predictive value than measuring a single site....

  16. The Comparison Study of Short-Term Prediction Methods to Enhance the Model Predictive Controller Applied to Microgrid Energy Management

    Directory of Open Access Journals (Sweden)

    César Hernández-Hernández

    2017-06-01

    Full Text Available Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing them to be combined with model predictive control. Comparisons of different prediction methods and different optimum energy distribution scenarios are provided, permitting us to determine when short-term energy prediction models should be used. The proposed prediction models in addition to the model predictive control strategy appear as a promising solution to energy management in microgrids. The controller has the task of performing the management of electricity purchase and sale to the power grid, maximizing the use of renewable energy sources and managing the use of the energy storage system. Simulations were performed with different weather conditions of solar irradiation. The obtained results are encouraging for future practical implementation.

  17. Predictive control of intersegmental tarsal movements in an insect.

    Science.gov (United States)

    Costalago-Meruelo, Alicia; Simpson, David M; Veres, Sandor M; Newland, Philip L

    2017-08-01

    In many animals intersegmental reflexes are important for postural and movement control but are still poorly undesrtood. Mathematical methods can be used to model the responses to stimulation, and thus go beyond a simple description of responses to specific inputs. Here we analyse an intersegmental reflex of the foot (tarsus) of the locust hind leg, which raises the tarsus when the tibia is flexed and depresses it when the tibia is extended. A novel method is described to measure and quantify the intersegmental responses of the tarsus to a stimulus to the femoro-tibial chordotonal organ. An Artificial Neural Network, the Time Delay Neural Network, was applied to understand the properties and dynamics of the reflex responses. The aim of this study was twofold: first to develop an accurate method to record and analyse the movement of an appendage and second, to apply methods to model the responses using Artificial Neural Networks. The results show that Artificial Neural Networks provide accurate predictions of tarsal movement when trained with an average reflex response to Gaussian White Noise stimulation compared to linear models. Furthermore, the Artificial Neural Network model can predict the individual responses of each animal and responses to others inputs such as a sinusoid. A detailed understanding of such a reflex response could be included in the design of orthoses or functional electrical stimulation treatments to improve walking in patients with neurological disorders as well as the bio/inspired design of robots.

  18. Robust Model Predictive Control of a Wind Turbine

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    , a new sensor is introduced in the EKF to give faster estimations. Wind speed estimation error is used to assess uncertainties in the linearized model. Significant uncertainties are considered to be in the gain of the system (B matrix of the state space model). Therefore this special structure......In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...

  19. Numerical Prediction of Hydromechanical Behaviour of Controllable Pitch Propeller

    Directory of Open Access Journals (Sweden)

    Saman Tarbiat

    2014-01-01

    Full Text Available The research described in this paper was carried out to predict hydrodynamic and frictional forces of controllable pitch propeller (CPP that bring about fretting problems in a blade bearing. The governing equations are Reynolds-averaged Navier-Stokes (RANS and are solved by OpenFOAM solver for hydrodynamic forces behind the ship’s wake. Frictional forces are calculated by practical mechanical formulae. Different advance velocities with constant rotational speed for blades are used to achieve hydrodynamic coefficients in open water and the wake behind the propeller. Results are compared at four different pitches. Detailed numerical results of 3D modelling of the propeller, hydrodynamic characteristics, and probability of the fretting motion in the propeller are presented. Results show that the probability of the fretting movement is related to the pitch.

  20. Prediction-based association control scheme in dense femtocell networks

    Science.gov (United States)

    Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

    2017-01-01

    The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system’s effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective. PMID:28328992

  1. A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

    Science.gov (United States)

    Downey, Brandon; Schmitt, John; Beller, Justin; Russell, Brian; Quach, Anthony; Hermann, Elizabeth; Lyon, David; Breit, Jeffrey

    2017-11-01

    As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed-batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647-1661, 2017. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

  2. Predictive Sampling of Rare Conformational Events in Aqueous Solution: Designing a Generalized Orthogonal Space Tempering Method.

    Science.gov (United States)

    Lu, Chao; Li, Xubin; Wu, Dongsheng; Zheng, Lianqing; Yang, Wei

    2016-01-12

    In aqueous solution, solute conformational transitions are governed by intimate interplays of the fluctuations of solute-solute, solute-water, and water-water interactions. To promote molecular fluctuations to enhance sampling of essential conformational changes, a common strategy is to construct an expanded Hamiltonian through a series of Hamiltonian perturbations and thereby broaden the distribution of certain interactions of focus. Due to a lack of active sampling of configuration response to Hamiltonian transitions, it is challenging for common expanded Hamiltonian methods to robustly explore solvent mediated rare conformational events. The orthogonal space sampling (OSS) scheme, as exemplified by the orthogonal space random walk and orthogonal space tempering methods, provides a general framework for synchronous acceleration of slow configuration responses. To more effectively sample conformational transitions in aqueous solution, in this work, we devised a generalized orthogonal space tempering (gOST) algorithm. Specifically, in the Hamiltonian perturbation part, a solvent-accessible-surface-area-dependent term is introduced to implicitly perturb near-solute water-water fluctuations; more importantly in the orthogonal space response part, the generalized force order parameter is generalized as a two-dimension order parameter set, in which essential solute-solvent and solute-solute components are separately treated. The gOST algorithm is evaluated through a molecular dynamics simulation study on the explicitly solvated deca-alanine (Ala10) peptide. On the basis of a fully automated sampling protocol, the gOST simulation enabled repetitive folding and unfolding of the solvated peptide within a single continuous trajectory and allowed for detailed constructions of Ala10 folding/unfolding free energy surfaces. The gOST result reveals that solvent cooperative fluctuations play a pivotal role in Ala10 folding/unfolding transitions. In addition, our assessment

  3. An FPGA- Based General-Purpose Data Acquisition Controller

    Science.gov (United States)

    Robson, C. C. W.; Bousselham, A.; Bohm

    2006-08-01

    System development in advanced FPGAs allows considerable flexibility, both during development and in production use. A mixed firmware/software solution allows the developer to choose what shall be done in firmware or software, and to make that decision late in the process. However, this flexibility comes at the cost of increased complexity. We have designed a modular development framework to help to overcome these issues of increased complexity. This framework comprises a generic controller that can be adapted for different systems by simply changing the software or firmware parts. The controller can use both soft and hard processors, with or without an RTOS, based on the demands of the system to be developed. The resulting system uses the Internet for both control and data acquisition. In our studies we developed the embedded system in a Xilinx Virtex-II Pro FPGA, where we used both PowerPC and MicroBlaze cores, http, Java, and LabView for control and communication, together with the MicroC/OS-II and OSE operating systems

  4. Control rod computer code IAMCOS: general theory and numerical methods

    International Nuclear Information System (INIS)

    West, G.

    1982-11-01

    IAMCOS is a computer code for the description of mechanical and thermal behavior of cylindrical control rods for fast breeders. This code version was applied, tested and modified from 1979 to 1981. In this report are described the basic model (02 version), theoretical definitions and computation methods [fr

  5. Synchronization of general complex networks via adaptive control ...

    Indian Academy of Sciences (India)

    2014-03-07

    Mar 7, 2014 ... networks with derivative coupling and time-delay coupling was investigated by adaptive control schemes [42]. However ... [41], the synchronization of complex dynamical networks with non-derivative coupling and derivative coupling .... For any symmetric positive definite matrix. M ∈ Rn×n and x,y ∈ Rn, ...

  6. Steering Angle Control of Car for Dubins Path-tracking Using Model Predictive Control

    Science.gov (United States)

    Kusuma Rahma Putri, Dian; Subchan; Asfihani, Tahiyatul

    2018-03-01

    Car as one of transportation is inseparable from technological developments. About ten years, there are a lot of research and development on lane keeping system(LKS) which is a system that automaticaly controls the steering to keep the vehicle especially car always on track. This system can be developed for unmanned cars. Unmanned system car requires navigation, guidance and control which is able to direct the vehicle to move toward the desired path. The guidance system is represented by using Dubins-Path that will be controlled by using Model Predictive Control. The control objective is to keep the car’s movement that represented by dinamic lateral motion model so car can move according to the path appropriately. The simulation control on the four types of trajectories that generate the value for steering angle and steering angle changes are at the specified interval.

  7. 46 CFR 154.701 - Cargo pressure and temperature control: General.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 5 2010-10-01 2010-10-01 false Cargo pressure and temperature control: General. 154.701... Equipment Cargo Pressure and Temperature Control § 154.701 Cargo pressure and temperature control: General... the MARVS under § 154.405; or (b) Be refrigerated by a system meeting § 154.702, and each refrigerated...

  8. Effectiveness of dementia follow-up care by memory clinics or general practitioners: randomised controlled trial

    NARCIS (Netherlands)

    Meeuwsen, E.J.; Melis, R.J.F.; Van der Aa, G.C.H.M.; Goluke-Willemse, G.A.M.; De Leest, B.J.M.; van Raak, F.H.J.M.; Scholzel-Dorenbos, C.J.M.; Verheijen, D.C.M.; Verhey, F. R. J.; Visser, M.C.; Wolfs, C.A.; Adang, E.M.M.; Olde Rikkert, M.G.M.

    2012-01-01

    Objective: To examine the effectiveness of post-diagnosis dementia treatment and coordination of care by memory clinics compared with general practitioners. Design: Multicentre randomised controlled trial. Setting: Nine memory clinics and 159 general practitioners in the Netherlands. Participants:

  9. Effectiveness of dementia follow-up care by memory clinics or general practitioners: randomised controlled trial.

    NARCIS (Netherlands)

    Meeuwsen, E.J.; Melis, R.J.F.; Aa, G.C. Van Der; Goluke-Willemse, G.A.; Leest, B.J. de; Raak, F.H. van; Scholzel-Dorenbos, C.J.M.; Verheijen, D.C.; Verhey, F.R.J.; Visser, M. de; Wolfs, C.A.; Adang, E.M.M.; Olde Rikkert, M.G.

    2012-01-01

    OBJECTIVE: To examine the effectiveness of post-diagnosis dementia treatment and coordination of care by memory clinics compared with general practitioners. DESIGN: Multicentre randomised controlled trial. SETTING: Nine memory clinics and 159 general practitioners in the Netherlands. PARTICIPANTS:

  10. Differences in pain-related fear acquisition and generalization: an experimental study comparing patients with fibromyalgia and healthy controls.

    Science.gov (United States)

    Meulders, Ann; Jans, Anne; Vlaeyen, Johan W S

    2015-01-01

    Anomalies in fear learning, such as failure to inhibit fear to safe stimuli, lead to sustained anxiety, which in turn may augment pain. In the same vein, stimulus generalization is adaptive as it enables individuals to extrapolate the predictive value of 1 stimulus to similar stimuli. However, when fear spreads in an unbridled way to novel technically safe stimuli, stimulus generalization becomes maladaptive and may lead to dysfunctional avoidance behaviors and culminate in severe pain disability. In a voluntary movement conditioning paradigm, we compared the acquisition and generalization of pain-related fear in patients with fibromyalgia (FM) and healthy controls. During acquisition, participants received predictable pain in 1 context (ie, 1 movement predicts pain, whereas another does not), and unpredictable pain in another (ie, pain never contingent upon movement). Fear generalization to novel movements (resembling the original painful or nonpainful movement) was tested in both contexts. Results indicated that the FM group showed slower differential acquisition of pain-related fear in the predictable context, and more contextual pain-related fear in the unpredictable context. Fear of movement-related pain spreads selectively to novel movements similar to the original painful movement, and not to those resembling the nonpainful movement in the healthy controls, but nondifferential fear generalization was observed in FM. As expected, in the unpredictable context, we also observed nondifferential fear generalization; this effect was more pronounced in FM. Given the status of overgeneralization as a plausible transdiagnostic pathogenic marker, we believe that this research might increase our knowledge about pathogenesis of musculoskeletal widespread pain.

  11. Predictive wavefront control for Adaptive Optics with arbitrary control loop delays

    Energy Technology Data Exchange (ETDEWEB)

    Poyneer, L A; Veran, J

    2007-10-30

    We present a modification of the closed-loop state space model for AO control which allows delays that are a non-integer multiple of the system frame rate. We derive the new forms of the Predictive Fourier Control Kalman filters for arbitrary delays and show that they are linear combinations of the whole-frame delay terms. This structure of the controller is independent of the delay. System stability margins and residual error variance both transition gracefully between integer-frame delays.

  12. Coordinated Voltage Control of a Wind Farm based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

    2016-01-01

    This paper presents an autonomous wind farm voltage controller based on Model Predictive Control (MPC). The reactive power compensation and voltage regulation devices of the wind farm include Static Var Compensators (SVCs), Static Var Generators (SVGs), Wind Turbine Generators (WTGs) and On...... are calculated based on an analytical method to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both voltage violated and normal operation conditions. A wind farm with 20 wind turbines was used to conduct case studies to verify the proposed coordinated...

  13. Distributed Model Predictive Control of A Wind Farm for Optimal Active Power Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

    2015-01-01

    , which combines the clustering, linear identification and pattern recognition techniques. The developed model, consisting of 47 affine dynamics, is verified by the comparison with a widely-used nonlinear wind turbine model. It can be used as a predictive model for the Model Predictive Control (MPC......This paper presents a dynamic discrete-time Piece- Wise Affine (PWA) model of a wind turbine for the optimal active power control of a wind farm. The control objectives include both the power reference tracking from the system operator and the wind turbine mechanical load minimization. Instead...... of partial linearization of the wind turbine model at selected operating points, the nonlinearities of the wind turbine model are represented by a piece-wise static function based on the wind turbine system inputs and state variables. The nonlinearity identification is based on the clustering-based algorithm...

  14. Memory controllers for real-time embedded systems predictable and composable real-time systems

    CERN Document Server

    Akesson, Benny

    2012-01-01

      Verification of real-time requirements in systems-on-chip becomes more complex as more applications are integrated. Predictable and composable systems can manage the increasing complexity using formal verification and simulation.  This book explains the concepts of predictability and composability and shows how to apply them to the design and analysis of a memory controller, which is a key component in any real-time system. This book is generally intended for readers interested in Systems-on-Chips with real-time applications.   It is especially well-suited for readers looking to use SDRAM memories in systems with hard or firm real-time requirements. There is a strong focus on real-time concepts, such as predictability and composability, as well as a brief discussion about memory controller architectures for high-performance computing. Readers will learn step-by-step how to go from an unpredictable SDRAM memory, offering highly variable bandwidth and latency, to a predictable and composable shared memory...

  15. A General Framework for Flow Control in Wireless Networks

    Science.gov (United States)

    2006-12-22

    algorithms proposed by Low and Lapsley [36], Paganini et. al. [41], Yaiche et. al. [54] belong to this class. The stability properties of various dual...updated dynamically by routers and users, respectively. The algorithms proposed by Low and Lapsley [36], Kunniyur and Srikant [28], Paganini et. al [41...Aug. 2003. [36] S. H. Low and D. E. Lapsley , “Optimization flow control, I: Basic algorithm and con- vergence,” vol. 7, no. 6, pp. 861–875, Dec

  16. Dietary Sodium Consumption Predicts Future Blood Pressure and Incident Hypertension in the Japanese Normotensive General Population

    Science.gov (United States)

    Takase, Hiroyuki; Sugiura, Tomonori; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki

    2015-01-01

    Background Although there is a close relationship between dietary sodium and hypertension, the concept that persons with relatively high dietary sodium are at increased risk of developing hypertension compared with those with relatively low dietary sodium has not been studied intensively in a cohort. Methods and Results We conducted an observational study to investigate whether dietary sodium intake predicts future blood pressure and the onset of hypertension in the general population. Individual sodium intake was estimated by calculating 24-hour urinary sodium excretion from spot urine in 4523 normotensive participants who visited our hospital for a health checkup. After a baseline examination, they were followed for a median of 1143 days, with the end point being development of hypertension. During the follow-up period, hypertension developed in 1027 participants (22.7%). The risk of developing hypertension was higher in those with higher rather than lower sodium intake (hazard ratio 1.25, 95% CI 1.04 to 1.50). In multivariate Cox proportional hazards regression analysis, baseline sodium intake and the yearly change in sodium intake during the follow-up period (as continuous variables) correlated with the incidence of hypertension. Furthermore, both the yearly increase in sodium intake and baseline sodium intake showed significant correlations with the yearly increase in systolic blood pressure in multivariate regression analysis after adjustment for possible risk factors. Conclusions Both relatively high levels of dietary sodium intake and gradual increases in dietary sodium are associated with future increases in blood pressure and the incidence of hypertension in the Japanese general population. PMID:26224048

  17. Dietary Sodium Consumption Predicts Future Blood Pressure and Incident Hypertension in the Japanese Normotensive General Population.

    Science.gov (United States)

    Takase, Hiroyuki; Sugiura, Tomonori; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki

    2015-07-29

    Although there is a close relationship between dietary sodium and hypertension, the concept that persons with relatively high dietary sodium are at increased risk of developing hypertension compared with those with relatively low dietary sodium has not been studied intensively in a cohort. We conducted an observational study to investigate whether dietary sodium intake predicts future blood pressure and the onset of hypertension in the general population. Individual sodium intake was estimated by calculating 24-hour urinary sodium excretion from spot urine in 4523 normotensive participants who visited our hospital for a health checkup. After a baseline examination, they were followed for a median of 1143 days, with the end point being development of hypertension. During the follow-up period, hypertension developed in 1027 participants (22.7%). The risk of developing hypertension was higher in those with higher rather than lower sodium intake (hazard ratio 1.25, 95% CI 1.04 to 1.50). In multivariate Cox proportional hazards regression analysis, baseline sodium intake and the yearly change in sodium intake during the follow-up period (as continuous variables) correlated with the incidence of hypertension. Furthermore, both the yearly increase in sodium intake and baseline sodium intake showed significant correlations with the yearly increase in systolic blood pressure in multivariate regression analysis after adjustment for possible risk factors. Both relatively high levels of dietary sodium intake and gradual increases in dietary sodium are associated with future increases in blood pressure and the incidence of hypertension in the Japanese general population. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

  18. A Framework for a General Purpose Intelligent Control System for Particle Accelerators. Phase II Final Report

    International Nuclear Information System (INIS)

    Westervelt, Robert; Klein, William; Kroupa, Michael; Olsson, Eric; Rothrock, Rick

    1999-01-01

    Vista Control Systems, Inc. has developed a portable system for intelligent accelerator control. The design is general in scope and is thus configurable to a wide range of accelerator facilities and control problems. The control system employs a multi-layer organization in which knowledge-based decision making is used to dynamically configure lower level optimization and control algorithms

  19. Using a cognitive architecture for general purpose service robot control

    Science.gov (United States)

    Puigbo, Jordi-Ysard; Pumarola, Albert; Angulo, Cecilio; Tellez, Ricardo

    2015-04-01

    A humanoid service robot equipped with a set of simple action skills including navigating, grasping, recognising objects or people, among others, is considered in this paper. By using those skills the robot should complete a voice command expressed in natural language encoding a complex task (defined as the concatenation of a number of those basic skills). As a main feature, no traditional planner has been used to decide skills to be activated, as well as in which sequence. Instead, the SOAR cognitive architecture acts as the reasoner by selecting which action the robot should complete, addressing it towards the goal. Our proposal allows to include new goals for the robot just by adding new skills (without the need to encode new plans). The proposed architecture has been tested on a human-sized humanoid robot, REEM, acting as a general purpose service robot.

  20. Comparisons of Prediction Models of Myofascial Pain Control after Dry Needling: A Prospective Study

    Directory of Open Access Journals (Sweden)

    Yuan-Ting Huang

    2013-01-01

    Full Text Available Background. This study purposed to validate the use of artificial neural network (ANN models for predicting myofascial pain control after dry needling and to compare the predictive capability of ANNs with that of support vector machine (SVM and multiple linear regression (MLR. Methods. Totally 400 patients who have received dry needling treatments completed the Brief Pain Inventory (BPI at baseline and at 1 year postoperatively. Results. Compared to the MLR and SVM models, the ANN model generally had smaller mean square error (MSE and mean absolute percentage error (MAPE values in the training dataset and testing dataset. Most ANN models had MAPE values ranging from 3.4% to 4.6% and most had high prediction accuracy. The global sensitivity analysis also showed that pretreatment BPI score was the best parameter for predicting pain after dry needling. Conclusion. Compared with the MLR and SVM models, the ANN model in this study was more accurate in predicting patient-reported BPI scores and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data.

  1. Transforming the ASDEX Upgrade discharge control system to a general-purpose plasma control platform

    International Nuclear Information System (INIS)

    Treutterer, Wolfgang; Cole, Richard; Gräter, Alexander; Lüddecke, Klaus; Neu, Gregor; Rapson, Christopher; Raupp, Gerhard; Zasche, Dieter; Zehetbauer, Thomas

    2015-01-01

    Highlights: • Control framework split in core and custom part. • Core framework deployable in other fusion device environments. • Adaptible through customizable modules, plug-in support and generic interfaces. - Abstract: The ASDEX Upgrade Discharge Control System DCS is a modern and mature product, originally designed to regulate and supervise ASDEX Upgrade Tokamak plasma operation. In its core DCS is based on a generic, versatile real-time software framework with a plugin architecture that allows to easily combine, modify and extend control function modules in order to tailor the system to required features and let it continuously evolve with the progress of an experimental fusion device. Due to these properties other fusion experiments like the WEST project have expressed interest in adopting DCS. For this purpose, essential parts of DCS must be unpinned from the ASDEX Upgrade environment by exposure or introduction of generalised interfaces. Re-organisation of DCS modules allows distinguishing between intrinsic framework core functions and device-specific applications. In particular, DCS must be prepared for deployment in different system environments with their own realisations for user interface, pulse schedule preparation, parameter server, time and event distribution, diagnostic and actuator systems, network communication and data archiving. The article explains the principles of the revised DCS structure, derives the necessary interface definitions and describes major steps to achieve the separation between general-purpose framework and fusion device specific components.

  2. Towards a General Theory of Financial Control for Organisations

    OpenAIRE

    Östman, Lars

    2009-01-01

    In this paper, a theory of accounting, control and accounting-related areas is outlined.It is based on a number of previous research-oriented books published over several decades and the author´s specific own experiences from internal and external processes with organisations in focus.Consistency and integrative power of the ideas have been tested in relation to certain books in various fields outside the core of the subject:theatre,sociology, applied systems theory,economic history, institut...

  3. Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

    Science.gov (United States)

    Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

    2017-09-11

    Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

  4. General fugacity-based model to predict the environmental fate of multiple chemical species.

    Science.gov (United States)

    Cahill, Thomas M; Cousins, Ian; Mackay, Donald

    2003-03-01

    A general multimedia environmental fate model is presented that is capable of simulating the fate of up to four interconverting chemical species. It is an extension of the existing equilibrium criterion (EQC) fugacity model, which is limited to single-species assessments. It is suggested that multispecies chemical assessments are warranted when a degradation product of a released chemical is either more toxic or more persistent than the parent chemical or where there is cycling between species, as occurs with association, disassociation, or ionization. The model is illustratively applied to three chemicals, namely chlorpyrifos, pentachlorophenol, and perfluorooctane sulfonate, for which multispecies assessments are advisable. The model results compare favorably with field data for chlorpyrifos and pentachlorophenol, while the perfluorooctane sulfonate simulation is more speculative due to uncertainty in input parameters and the paucity of field data to validate the predictions. The model thus provides a tool for assessing the environmental fate and behavior of a group of chemicals that hitherto have not been addressed by evaluative models such as EQC.

  5. NUTRITIONAL ASSESSMENT IN PATIENTS PREDICTED TO MAJOR ABDOMINAL SURGERY AT THE GENERAL HOSPITAL CELJE

    Directory of Open Access Journals (Sweden)

    Ernest Novak

    2001-12-01

    Full Text Available Background. Malnutrition has serious implications for recovery after surgery. Early detection of malnutrition with nutritional support minimizes postoperative complications. Nutritional assessment tools need to be simple and suitable for use in everyday practice. In our study we wanted to determine, how many patients might benefit from nutritional support.Methods. From April to August 1999 fifty consecutively admitted patients predicted to major abdominal surgery have been examined. We used Mini nutritional assessment (MNA, Buzby’s nutrition risk index (NRI, blood albumin level and weight loss in the last 3 months period prior to the examination, to assess nutritional status.Results. We examined 50 patients (27 males and 23 females, age 76.5 ± 16.5 and confirmed malnutrition in 40% of patients with MNA and serum albumin level. The increased risk for nutrition-associated complications was confirmed by NRI and weight loss in 44%.Conclusions. A confident diagnosis of malnutrition and increased risk for nutrition-associated complications can be established by using a combination of simple methods like MNA, NRI, weight loss and serum albumin level. Almost half of the patients admitted for major abdominal surgery in General hospital Celje suffer from malnutrition and they may benefit with early nutritional intervention.

  6. Finite Control Set Model Predictive Speed Control of a DC Motor

    Directory of Open Access Journals (Sweden)

    Viktor Šlapák

    2016-01-01

    Full Text Available The paper describes the design procedure for a finite control set model predictive control (FCS-MPC of brushed permanent magnet DC (PMDC machine supplied from DC-DC converter. Full order linear Kalman filter is used for estimation of an unmeasured load torque and reduction of speed measurement noise. A new cost function has been introduced with a feedforward dynamic current component and a feedforward static load current component. The performance of the proposed control strategy is compared to the conventional PI-PWM cascade speed control through the experimental verification on the 250 W laboratory prototype. Obtained results show excellent dynamic behaviour and indicate possible energy savings of the proposed speed control.

  7. Predicting and controlling the reactivity of immune cell populations against cancer

    Science.gov (United States)

    Oved, Kfir; Eden, Eran; Akerman, Martin; Noy, Roy; Wolchinsky, Ron; Izhaki, Orit; Schallmach, Ester; Kubi, Adva; Zabari, Naama; Schachter, Jacob; Alon, Uri; Mandel-Gutfreund, Yael; Besser, Michal J; Reiter, Yoram

    2009-01-01

    Heterogeneous cell populations form an interconnected network that determine their collective output. One example of such a heterogeneous immune population is tumor-infiltrating lymphocytes (TILs), whose output can be measured in terms of its reactivity against tumors. While the degree of reactivity varies considerably between different TILs, ranging from null to a potent response, the underlying network that governs the reactivity is poorly understood. Here, we asked whether one can predict and even control this reactivity. To address this we measured the subpopulation compositions of 91 TILs surgically removed from 27 metastatic melanoma patients. Despite the large number of subpopulations compositions, we were able to computationally extract a simple set of subpopulation-based rules that accurately predict the degree of reactivity. This raised the conjecture of whether one could control reactivity of TILs by manipulating their subpopulation composition. Remarkably, by rationally enriching and depleting selected subsets of subpopulations, we were able to restore anti-tumor reactivity to nonreactive TILs. Altogether, this work describes a general framework for predicting and controlling the output of a cell mixture. PMID:19401677

  8. Scintillation camera-computer systems: General principles of quality control

    International Nuclear Information System (INIS)

    Ganatra, R.D.

    1992-01-01

    Scintillation camera-computer systems are designed to allow the collection, digital analysis and display of the image data from a scintillation camera. The components of the computer in such a system are essentially the same as those of a computer used in any other application, i.e. a central processing unit (CPU), memory and magnetic storage. Additional hardware items necessary for nuclear medicine applications are an analogue-to-digital converter (ADC), which converts the analogue signals from the camera to digital numbers, and an image display. It is possible that the transfer of data from camera to computer degrades the information to some extent. The computer can generate the image for display, but it also provides the capability of manipulating the primary data to improve the display of the image. The first function of conversion from analogue to digital mode is not within the control of the operator, but the second type of manipulation is in the control of the operator. These type of manipulations should be done carefully without sacrificing the integrity of the incoming information

  9. Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

    Science.gov (United States)

    Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

    2016-02-01

    A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration.

  10. Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

    Science.gov (United States)

    Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

    1997-01-01

    One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

  11. Development and Validation of an International Risk Prediction Algorithm for Episodes of Major Depression in General Practice Attendees The PredictD Study

    NARCIS (Netherlands)

    King, Michael; Walker, Carl; Levy, Gus; Bottomley, Christian; Royston, Patrick; Weich, Scott; Bellon-Saameno, Juan Angel; Moreno, Berta; Svab, Igor; Rotar, Danica; Rifel, J.; Maaroos, Heidi-Ingrid; Aluoja, Anu; Kalda, Ruth; Neeleman, Jan; Geerlings, Mirjam I.; Xavier, Miguel; Carraca, Idalmiro; Goncalves-Pereira, Manuel; Vicente, Benjamin; Saldivia, Sandra; Melipillan, Roberto; Torres-Gonzalez, Francisco; Nazareth, Irwin

    2008-01-01

    Context: Strategies for prevention of depression are hindered by lack of evidence about the combined predictive effect of known risk factors. Objectives: To develop a risk algorithm for onset of major depression. Design: Cohort of adult general practice attendees followed up at 6 and 12 months. We

  12. Predictive powertrain control using powertrain history and GPS data

    Science.gov (United States)

    Weslati, Feisel; Krupadanam, Ashish A

    2015-03-03

    A method and powertrain apparatus that predicts a route of travel for a vehicle and uses historical powertrain loads and speeds for the predicted route of travel to optimize at least one powertrain operation for the vehicle.

  13. Improving prediction of ischemic cardiovascular disease in the general population using apolipoprotein B

    DEFF Research Database (Denmark)

    Benn, Marianne; Nordestgaard, Børge G; Jensen, Gorm Boje

    2007-01-01

    Apolipoprotein B (apoB) levels predict fatal myocardial infarction. Whether apoB also predicts nonfatal ischemic cardiovascular events is unclear. We tested the following hypotheses: apoB predicts ischemic cardiovascular events, and apoB is a better predictor of ischemic cardiovascular events than...

  14. Hybrid model predictive control applied to switching control of burner load for a compact marine boiler design

    DEFF Research Database (Denmark)

    Solberg, Brian; Andersen, Palle; Maciejowski, Jan

    2008-01-01

    This paper discusses the application of hybrid model predictive control to control switching between different burner modes in a novel compact marine boiler design. A further purpose of the present work is to point out problems with finite horizon model predictive control applied to systems for w...

  15. Autonomous formation flight of helicopters: Model predictive control approach

    Science.gov (United States)

    Chung, Hoam

    Formation flight is the primary movement technique for teams of helicopters. However, the potential for accidents is greatly increased when helicopter teams are required to fly in tight formations and under harsh conditions. This dissertation proposes that the automation of helicopter formations is a realistic solution capable of alleviating risks. Helicopter formation flight operations in battlefield situations are highly dynamic and dangerous, and, therefore, we maintain that both a high-level formation management system and a distributed coordinated control algorithm should be implemented to help ensure safe formations. The starting point for safe autonomous formation flights is to design a distributed control law attenuating external disturbances coming into a formation, so that each vehicle can safely maintain sufficient clearance between it and all other vehicles. While conventional methods are limited to homogeneous formations, our decentralized model predictive control (MPC) approach allows for heterogeneity in a formation. In order to avoid the conservative nature inherent in distributed MPC algorithms, we begin by designing a stable MPC for individual vehicles, and then introducing carefully designed inter-agent coupling terms in a performance index. Thus the proposed algorithm works in a decentralized manner, and can be applied to the problem of helicopter formations comprised of heterogenous vehicles. Individual vehicles in a team may be confronted by various emerging situations that will require the capability for in-flight reconfiguration. We propose the concept of a formation manager to manage separation, join, and synchronization of flight course changes. The formation manager accepts an operator's commands, information from neighboring vehicles, and its own vehicle states. Inside the formation manager, there are multiple modes and complex mode switchings represented as a finite state machine (FSM). Based on the current mode and collected

  16. A General Purpose Experiment Controller for low cost Space Application

    Science.gov (United States)

    Guzman-Garcia, D.; Rowland, D. E.; Uribe, P.; Nieves-Chinchilla, T.

    2012-12-01

    Space activities are very expensive and include a high degree of risk. Nowadays, CubeSat missions represent a fast and inexpensive way to conduct scientific space research. These platforms are less expensive to develop and build than conventional satellites. There are ample demonstration that these platforms are well suited for a wide range of science missions in different fields, such as astrobiology, astronomy, atmospheric science, space weather and biology. This paper presents a hybrid "processor in an Field Programmable Gate Array (FPGA)" experiment/spacecraft controller for Cubesat missions. The system has two objectives, first is to obtain a multipurpose and easily customizable system aimed at processing the data from the widest kind of instruments and second, to provide the system with the highest processing capabilities in order to be able to perform complex onboard algorithms. Due to the versatility of the system and its reduced dimensions, it can be employed in different space platforms. The system is envisioned to be employed for the first time as the smart radio receiver for the upcoming NASA FireStation instrument. It is one of four experiments manifested to fly on an experiment pallet the U.S Department of Defense plans to deploy on the International Space Station in 2013. FireStation will continue analyzing the link between the Lightning and the Terrestrial Gamma Rays initiated by the FireFly Cubesat. The system is responsible for the management of a set of small Heliophysics instrumentats, including a photometer, magnetometer, and electric and magnetic field antennas. A description of the system architecture and its main features are presented. The main functional and performance tests during the integration and calibration phase of the instruments are also discussed.

  17. Predicting norm enforcement: The individual and joint predictive power of economic preferences, personality, and self-control

    OpenAIRE

    Friehe, Tim; Schildberg-Hörisch, Hannah

    2017-01-01

    This paper explores the individual and joint predictive power of concepts from economics, psychology, and criminology for individual norm enforcement behavior. More specifically, we consider economic preferences (patience and attitudes towards risk), personality traits from psychology (Big Five and locus of control), and a self-control scale from criminology. Using survey data, we show that the various concepts complement each other in predicting self-reported norm enforcement behavior. The m...

  18. The concept of damage control: extending the paradigm to emergency general surgery.

    Science.gov (United States)

    Stawicki, S Peter; Brooks, Adam; Bilski, Tracy; Scaff, David; Gupta, Rajan; Schwab, C William; Gracias, Vicente H

    2008-01-01

    A damage control (DC) approach was developed to improve survival in severely injured trauma patients. The role of DC in acute surgery (AS) patients who are critically ill, as a result of sepsis or overwhelming haemorrhage continues to evolve. The goal of this study was to assess morbidity and mortality of AS patients who underwent DC, and to compare observed and predicted morbidity and mortality as calculated from APACHE II and physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM) scores. Consecutive acute surgery patients who underwent DC from 2002 to 2004 were included. Retrospectively collected data included patient demographics, physiological parameters, surgical indications and procedures, mortality, morbidity, as well as volumes of crystalloid and colloid (plasma and red blood cell) resuscitation. Observed mortality and complications were compared to those calculated from APACHE II and POSSUM scores. Data were analysed using the Mann-Whitney test for median values, chi-square and Fisher's exact tests for proportions. Sixteen patients (mean age 53 years, seven men, nine women) underwent DC. The most common indications for DC included abdominal sepsis (6/15), intraoperative bleeding (5/15), and bowel ischaemia (3/15). The mean intraoperative blood loss during the index procedure was 2060mL. There were 2.4 average procedures per patient. At the end of DC II (36.5h), mean infusion of crystalloid was 17L, packed red blood cells was 3.6L, and plasma was 3L. Eight of 16 patients required vasopressor administration during resuscitation. At 28 days, there were five unexpected survivors as predicted by POSSUM and three by APACHE II (observed mortality seven, predicted mortality by the two methods: 12 (P=0.074), and 10 (P=0.24), respectively). Five patients died prior to definitive abdominal closure. Split thickness skin grafting (4/16) and primary fascial closure (4/16) constituted the most common methods of abdominal

  19. Open-Delta Three-Phase Inverter Current Control Using Predictive Control For PV System Connected To The Grid

    OpenAIRE

    ABBASİ, Zohre; FESHKİ FARAHANİ, Hassan

    2015-01-01

    Abstract. Predictive control method has advantages such as simple structure, functional and follow the simple mathematical. In this paper, a new method is provided for controlling the open-Delta three-phase inverter . Model-based predictive control system is used for controlling the current of a open-Delta three-phase inverter, which is in the process of converting the photovoltaic energy conversion plays a three-phase network. The controller at any time, the next period current are estimated...

  20. Use of Electrocardiography to Predict Future Development of Hypertension in the General Population.

    Science.gov (United States)

    Takase, Hiroyuki; Sugiura, Tomonori; Murai, Shunsuke; Yamashita, Sumiyo; Ohte, Nobuyuki; Dohi, Yasuaki

    2016-04-01

    Cardiac muscle responds to increased afterload by developing hypertrophy. During the early stages of hypertension, the heart can be transiently, but frequently, exposed to increased afterload. This study was designed to test the hypothesis that left ventricular hypertrophy (LVH) assessed by electrocardiography (ECG) can be used to predict future development of hypertension.Sokolow-Lyon voltage and Cornell product were calculated using ECG in 5770 normotensive participants who visited our hospital for a physical checkup (age 52.7 ± 11.3 years). LVH was defined as a Sokolow-Lyon voltage of >3.8 mV or a Cornell product of >2440 mm × ms. After baseline examination, participants were followed up with the endpoint being the development of hypertension.During the median follow-up period of 1089 days (15,789 person-years), hypertension developed in 1029 participants (65.2/1000 person-years). A Kaplan-Meier analysis demonstrated a significantly higher incidence of hypertension in participants with LVH than in those without LVH as assessed by Sokolow-Lyon voltage or Cornell product (P < 0.0001 for both). The hazard ratios for incident hypertension in participants with LVH defined by Sokolow-Lyon voltage and Cornell product were 1.49 (95% confidence interval [CI] 1.16-1.90, P < 0.01) and 1.34 (95% CI 1.09-1.65, P < 0.01), respectively, after adjustment for possible risk factors. Furthermore, in multivariable Cox hazard analysis, where Sokolow-Lyon voltage and Cornell product were taken as continuous variables, both indices were independent predictors of future hypertension (P < 0.0001).Both Sokolow-Lyon voltage and Cornell product are novel predictors of future development of hypertension in the general population.

  1. Degradation Mechanisms and Lifetime Prediction for Lithium-Ion Batteries -- A Control Perspective: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Kandler; Shi, Ying; Santhanagopalan, Shriram

    2015-07-29

    Predictive models of Li-ion battery lifetime must consider a multiplicity of electrochemical, thermal, and mechanical degradation modes experienced by batteries in application environments. To complicate matters, Li-ion batteries can experience different degradation trajectories that depend on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. We present a generalized battery life prognostic model framework for battery systems design and control. The model framework consists of trial functions that are statistically regressed to Li-ion cell life datasets wherein the cells have been aged under different levels of stress. Degradation mechanisms and rate laws dependent on temperature, storage, and cycling condition are regressed to the data, with multiple model hypotheses evaluated and the best model down-selected based on statistics. The resulting life prognostic model, implemented in state variable form, is extensible to arbitrary real-world scenarios. The model is applicable in real-time control algorithms to maximize battery life and performance. We discuss efforts to reduce lifetime prediction error and accommodate its inevitable impact in controller design.

  2. Differences in treatment approach between Dutch paediatric dentists and general practitioners, a case control study

    NARCIS (Netherlands)

    Kuin, D.; Veerkamp, J.S.J.

    2012-01-01

    AIM: This case control study was to assess whether paediatric dentists perform significantly more diagnostic, preventive and curative care in a clinical setting then do general dental practitioners. METHODS: 16 paediatric dentists were approached and a matching control group of 16 general dental

  3. A Generalized Approach to Soil Strength Prediction With Machine Learning Methods

    National Research Council Canada - National Science Library

    Semen, Peter M

    2006-01-01

    .... However, methods to accurately predict strength from other fundamental geotechnical parameters are lacking, especially for a broad range of soil types under widely-varying environmental conditions...

  4. Less Is More: Using Static-2002R Subscales to Predict Violent and General Recidivism Among Sexual Offenders.

    Science.gov (United States)

    Babchishin, Kelly M; Hanson, R Karl; Blais, Julie

    2016-04-01

    Given that sexual offenders are more likely to reoffend with a nonsexual offense than a sexual offense, it is useful to have risk scales that predict general recidivism among sexual offenders. In the current study, we examined the extent to which two commonly used risk scales for sexual offenders (Static-99R and Static-2002R) predict violent and general recidivism, and whether it would be possible to improve predictive accuracy for these outcomes by revising their items. Based on an aggregated sample of 3,536 adult male sex offenders from Canada, the United States, and Europe (average age of 39 years), we found that a scale created from the Age at Release item and the General Criminality subscale of Static-2002R predicted nonsexual violent, any violent, and general recidivism significantly better than Static-99R or Static-2002R total scores. The convergent validity of this new scale (Brief Assessment of Recidivism Risk-2002R [BARR-2002R]) was examined in a new, independent data set of Canadian high-risk adult male sex offenders (N = 360) where it was found to be highly correlated with other risk assessment tools for general recidivism and the Psychopathy Checklist-Revised (PCL-R), as well as demonstrated similar discrimination and calibration as in the development sample. Instead of using total scores from the Static-99R or Static-2002R, we recommend that evaluators use the BARR-2002R for predicting violent and general recidivism among sex offenders, and for screening for the psychological dimension of antisocial orientation. © The Author(s) 2015.

  5. Subjective memory complaints in general practice predicts future dementia: a 4-year follow-up study

    DEFF Research Database (Denmark)

    Waldorff, Frans Boch; Vogel, Asmus Mejling; Siersma, Volkert Dirk

    2012-01-01

    Many older patients in general practice have subjective memory complaints (SMC); however, not all share this information with their general practitioner (GP). The association between SMC and future cognitive decline or dementia is not clear, especially in a general practice population. The aim...

  6. Experimental evaluation of model predictive control and inverse dynamics control for spacecraft proximity and docking maneuvers

    Science.gov (United States)

    Virgili-Llop, Josep; Zagaris, Costantinos; Park, Hyeongjun; Zappulla, Richard; Romano, Marcello

    2018-03-01

    An experimental campaign has been conducted to evaluate the performance of two different guidance and control algorithms on a multi-constrained docking maneuver. The evaluated algorithms are model predictive control (MPC) and inverse dynamics in the virtual domain (IDVD). A linear-quadratic approach with a quadratic programming solver is used for the MPC approach. A nonconvex optimization problem results from the IDVD approach, and a nonlinear programming solver is used. The docking scenario is constrained by the presence of a keep-out zone, an entry cone, and by the chaser's maximum actuation level. The performance metrics for the experiments and numerical simulations include the required control effort and time to dock. The experiments have been conducted in a ground-based air-bearing test bed, using spacecraft simulators that float over a granite table.

  7. Prediction of periodontal disease: modelling and validation in different general German populations.

    Science.gov (United States)

    Zhan, Yiqiang; Holtfreter, Birte; Meisel, Peter; Hoffmann, Thomas; Micheelis, Wolfgang; Dietrich, Thomas; Kocher, Thomas

    2014-03-01

    To develop models for periodontitis using self-reported questions and to validate them externally. The Study of Health in Pomerania (SHIP-0) was used for model development. Periodontitis was defined according to the definitions of the Center for Disease Control and Prevention-American Academy of Periodontology, the 5th European Workshop in Periodontology, and Dietrich et al. (≥2 teeth with inter-proximal clinical attachment loss of ≥4 mm and 6 mm as moderate and severe periodontitis) respectively. These models were validated in SHIP-Trend and the Fourth German Oral Health Study (DMS IV). Final models included age, gender, education, smoking, bleeding on brushing and self-reported presence of mobile teeth. Concordance-statistics (C-statistics) of the final models from SHIP-0 were 0.84, 0.82 and 0.85 for the three definitions respectively. Validation in SHIP-Trend revealed C-statistics of 0.82, 0.81 and 0.82 respectively. As bleeding on brushing and presence of mobile teeth were unavailable in DMS IV, reduced models were developed. C-statistics of reduced models were 0.82, 0.81 and 0.83 respectively. Validation in DMS IV revealed C-statistics of 0.72, 0.78 and 0.72 for the three definitions respectively. All p values of the goodness-of-fit tests were >0.05. The models yielded a moderate usefulness for prediction of periodontitis. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  8. Gain-Scheduled Model Predictive Control of Wind Turbines using Laguerre Functions

    DEFF Research Database (Denmark)

    Adegas, Fabiano Daher; Wisniewski, Rafal; Larsen, Lars Finn Sloth

    2014-01-01

    This paper presents a systematic approach to design gain-scheduled predictive controllers for wind turbines. The predictive control law is based on Laguerre functions to parameterize control signals and a parameter-dependent cost function that is analytically determined from turbine data....... The approach can be utilized to the design of new controllers and to represent existing gain-scheduled controllers as predictive controllers. The numerical example and simulations illustrate the design of a speed controller augmented with active damping of the tower fore-aft displacement....

  9. Decision Styles and Rationality: An Analysis of the Predictive Validity of the General Decision-Making Style Inventory

    Science.gov (United States)

    Curseu, Petru Lucian; Schruijer, Sandra G. L.

    2012-01-01

    This study investigates the relationship between the five decision-making styles evaluated by the General Decision-Making Style Inventory, indecisiveness, and rationality in decision making. Using a sample of 102 middle-level managers, the results show that the rational style positively predicts rationality in decision making and negatively…

  10. Tail biting behaviour and tail damage in pigs and the relationship with general behaviour: Predicting the inevitable?

    NARCIS (Netherlands)

    Ursinus, W.W.; Reenen, van C.G.; Kemp, B.; Bolhuis, J.E.

    2014-01-01

    Tail biting behaviour in pigs is a common problem in conventional housing systems. Our study examined the consistency over time in tail biting and tail damage and it explored the predictive value of general behaviours observed in individual pigs and in pens as a whole. Pigs (n = 480), reared in

  11. Predicting the multi-domain progression of Parkinson's disease: a Bayesian multivariate generalized linear mixed-effect model.

    Science.gov (United States)

    Wang, Ming; Li, Zheng; Lee, Eun Young; Lewis, Mechelle M; Zhang, Lijun; Sterling, Nicholas W; Wagner, Daymond; Eslinger, Paul; Du, Guangwei; Huang, Xuemei

    2017-09-25

    It is challenging for current statistical models to predict clinical progression of Parkinson's disease (PD) because of the involvement of multi-domains and longitudinal data. Past univariate longitudinal or multivariate analyses from cross-sectional trials have limited power to predict individual outcomes or a single moment. The multivariate generalized linear mixed-effect model (GLMM) under the Bayesian framework was proposed to study multi-domain longitudinal outcomes obtained at baseline, 18-, and 36-month. The outcomes included motor, non-motor, and postural instability scores from the MDS-UPDRS, and demographic and standardized clinical data were utilized as covariates. The dynamic prediction was performed for both internal and external subjects using the samples from the posterior distributions of the parameter estimates and random effects, and also the predictive accuracy was evaluated based on the root of mean square error (RMSE), absolute bias (AB) and the area under the receiver operating characteristic (ROC) curve. First, our prediction model identified clinical data that were differentially associated with motor, non-motor, and postural stability scores. Second, the predictive accuracy of our model for the training data was assessed, and improved prediction was gained in particularly for non-motor (RMSE and AB: 2.89 and 2.20) compared to univariate analysis (RMSE and AB: 3.04 and 2.35). Third, the individual-level predictions of longitudinal trajectories for the testing data were performed, with ~80% observed values falling within the 95% credible intervals. Multivariate general mixed models hold promise to predict clinical progression of individual outcomes in PD. The data was obtained from Dr. Xuemei Huang's NIH grant R01 NS060722 , part of NINDS PD Biomarker Program (PDBP). All data was entered within 24 h of collection to the Data Management Repository (DMR), which is publically available ( https://pdbp.ninds.nih.gov/data-management ).

  12. Accuracy of diagnoses predicted from a simple patient questionnaire stratified by the duration of general ambulatory training: an observational study

    Directory of Open Access Journals (Sweden)

    Uehara T

    2013-12-01

    Full Text Available Takanori Uehara,1,2 Masatomi Ikusaka,1 Yoshiyuki Ohira,1 Mitsuyasu Ohta,1,2 Kazutaka Noda,1 Tomoko Tsukamoto,1 Toshihiko Takada,1 Masahito Miyahara11Department of General Medicine, Chiba University Hospital, 2Division of Rotated Collaboration Systems for Local Healthcare, Graduate School of Medicine, Chiba University, Chiba, JapanPurpose: To compare the diagnostic accuracy of diseases predicted from patient responses to a simple questionnaire completed prior to examination by doctors with different levels of ambulatory training in general medicine.Participants and methods: Before patient examination, five trained physicians, four short-term-trained residents, and four untrained residents examined patient responses to a simple questionnaire and then indicated, in rank order according to their subjective confidence level, the diseases they predicted. Final diagnosis was subsequently determined from hospital records by mentor physicians 3 months after the first patient visit. Predicted diseases and final diagnoses were codified using the International Classification of Diseases version 10. A “correct” diagnosis was one where the predicted disease matched the final diagnosis code.Results: A total of 148 patient questionnaires were evaluated. The Herfindahl index was 0.024, indicating a high degree of diversity in final diagnoses. The proportion of correct diagnoses was high in the trained group (96 of 148, 65%; residual analysis, 4.4 and low in the untrained group (56 of 148, 38%; residual analysis, -3.6 (χ2=22.27, P<0.001. In cases of correct diagnosis, the cumulative number of correct diagnoses showed almost no improvement, even when doctors in the three groups predicted ≥4 diseases.Conclusion: Doctors who completed ambulatory training in general medicine while treating a diverse range of diseases accurately predicted diagnosis in 65% of cases from limited written information provided by a simple patient questionnaire, which proved useful

  13. A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making.

    Science.gov (United States)

    van der Lee, J H; Svrcek, W Y; Young, B R

    2008-01-01

    Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.

  14. Jet Engine Noise Generation, Prediction and Control. Chapter 86

    Science.gov (United States)

    Huff, Dennis L.; Envia, Edmane

    2004-01-01

    Aircraft noise has been a problem near airports for many years. It is a quality of life issue that impacts millions of people around the world. Solving this problem has been the principal goal of noise reduction research that began when commercial jet travel became a reality. While progress has been made in reducing both airframe and engine noise, historically, most of the aircraft noise reduction efforts have concentrated on the engines. This was most evident during the 1950 s and 1960 s when turbojet engines were in wide use. This type of engine produces high velocity hot exhaust jets during takeoff generating a great deal of noise. While there are fewer commercial aircraft flying today with turbojet engines, supersonic aircraft including high performance military aircraft use engines with similar exhaust flow characteristics. The Pratt & Whitney F100-PW-229, pictured in Figure la, is an example of an engine that powers the F-15 and F-16 fighter jets. The turbofan engine was developed for subsonic transports, which in addition to better fuel efficiency also helped mitigate engine noise by reducing the jet exhaust velocity. These engines were introduced in the late 1960 s and power most of the commercial fleet today. Over the years, the bypass ratio (that is the ratio of the mass flow through the fan bypass duct to the mass flow through the engine core) has increased to values approaching 9 for modern turbofans such as the General Electric s GE-90 engine (Figure lb). The benefits to noise reduction for high bypass ratio (HPBR) engines are derived from lowering the core jet velocity and temperature, and lowering the tip speed and pressure ratio of the fan, both of which are the consequences of the increase in bypass ratio. The HBPR engines are typically very large in diameter and can produce over 100,000 pounds of thrust for the largest engines. A third type of engine flying today is the turbo-shaft which is mainly used to power turboprop aircraft and helicopters

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

    Science.gov (United States)

    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.

  16. Energy Optimal Tracking Control with Discrete Fluid Power Systems using Model Predictive Control

    DEFF Research Database (Denmark)

    Hansen, Anders Hedegaard; Asmussen, Magnus Færing; Bech, Michael Møller

    2017-01-01

    For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated by a...... and compared to a PID like tracking controller combined with a FSA. The results indicate that the energy efficiency of position tracking DDC systems may be improved significantly by using the MPC algorithm.......For Discrete Displacement Cylinder (DDC) drives the control task lies in choosing force level. Hence, which force level to apply and thereby which pressure level each cylinder chambers shall be connected to. The DDC system is inherently a force system why often a force reference is generated...... by a tracking controller and translated into a discrete force level in a Force Shifting Algorithm (FSA). In the current paper the tracking controller and the FSA are combined in a Model Predictive Control algorithm solving the tracking problem while minimizing the energy use. Two MPC algorithms are investigated...

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

    Science.gov (United States)

    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

  18. Predicting persistent disabling low back pain in general practice: a prospective cohort study.

    Science.gov (United States)

    Jones, Gareth T; Johnson, Ruth E; Wiles, Nicola J; Chaddock, Carol; Potter, Richard G; Roberts, Chris; Symmons, Deborah P M; Macfarlane, Gary J

    2006-05-01

    Patients may adopt active and/or passive coping strategies in response to pain. However, it is not known whether these strategies may also precede the onset of chronic symptoms and, if so, whether they are independent predictors of prognosis. To examine, in patients with low back pain in general practice, the prognostic value of active and passive coping styles, in the context of baseline levels of pain, disability and pain duration. Prospective cohort study. Nine general practices in north west England. Patients consulting their GP with a new episode of low back pain were recruited to the study. Information on coping styles, pain severity, disability, duration, and a brief history of other chronic pain symptoms was recorded using a self-completion postal questionnaire. Participants were then sent a follow-up questionnaire, 3 months after their initial consultation, to assess the occurrence of low back pain. The primary outcome was persistent disabling low back pain, that is, low back pain at 3-month follow-up self-rated as >or=20 mm on a 100 mm visual analogue scale, and >or=5 on the Roland and Morris Disability Questionnaire. A total of 974 patients took part in the baseline survey, of whom 922 (95%) completed a follow-up questionnaire; 363 individuals (39%) reported persistent disabling pain at follow-up. Persons who reported high levels of passive coping experienced a threefold increase in the risk of persistent disabling low back pain (relative risk [RR] = 3.0; 95% confidence interval [CI] = 2.3 to 4.0). In contrast, active coping was associated with neither an increase nor a decrease in the risk of a poor prognosis. After adjusting for baseline pain severity, disability, and other measures of pain and pain history, persons who reported a high passive coping score were still at 50% increased risk of a poor outcome (RR = 1.5; 95% CI = 1.1 to 2.0). Patients who report passive coping strategies experience a significant increase in the risk of persistent symptoms

  19. Predicting macropores in space and time by earthworms and abiotic controls

    Science.gov (United States)

    Hohenbrink, Tobias Ludwig; Schneider, Anne-Kathrin; Zangerlé, Anne; Reck, Arne; Schröder, Boris; van Schaik, Loes

    2017-04-01

    Macropore flow increases infiltration and solute leaching. The macropore density and connectivity, and thereby the hydrological effectiveness, vary in space and time due to earthworms' burrowing activity and their ability to refill their burrows in order to survive drought periods. The aim of our study was to predict the spatiotemporal variability of macropore distributions by a set of potentially controlling abiotic variables and abundances of different earthworm species. We measured earthworm abundances and effective macropore distributions using tracer rainfall infiltration experiments in six measurement campaigns during one year at six field sites in Luxembourg. Hydrologically effective macropores were counted in three soil depths (3, 10, 30 cm) and distinguished into three diameter classes (6 mm). Earthworms were sampled and determined to species-level. In a generalized linear modelling framework, we related macropores to potential spatial and temporal controlling factors. Earthworm species such as Lumbricus terrestris and Aporrectodea longa, local abiotic site conditions (land use, TWI, slope), temporally varying weather conditions (temperature, humidity, precipitation) and soil moisture affected the number of effective macropores. Main controlling factors and explanatory power of the models (uncertainty and model performance) varied depending on the depth and diameter class of macropores. We present spatiotemporal predictions of macropore density by daily-resolved, one year time series of macropore numbers and maps of macropore distributions at specific dates in a small-scale catchment with 5 m resolution.

  20. Predictive control of irrigation canals – robust design and real-time implementation

    NARCIS (Netherlands)

    Aguilar, José V.; Langarita, Pedro; Rodellar, José; Linares, Lorenzo; Horváth, K.

    2016-01-01

    Predictive control is one of the most commonly used control methods in a variety of application areas, including hydraulic processes such as water distribution canals for irrigation. This article presents the design and application of predictive control for the water discharge entering into an

  1. Testing the main prediction of the Interpersonal Theory of Suicide in a representative sample of the German general population.

    Science.gov (United States)

    Glaesmer, Heide; Hallensleben, Nina; Forkmann, Thomas; Spangenberg, Lena; Kapusta, Nestor; Teismann, Tobias

    2017-03-15

    To evaluate the main prediction of the Interpersonal Theory of Suicide (IPTS): 3-way-interaction of perceived burdensomeness (PB), thwarted belongingness (TB), and acquired capability (AC) for the prediction of suicidal behavior in a representative population sample. A total of 2513 participants completed measures of suicidal behavior, TB, PB, acquired capability (AC-FAD), and symptoms of depression and anxiety. The two-way-interaction of TB and PB, and the three-way interaction of TB, PB and AC-FAD predict suicidality. Given the cross-sectional nature of the data, conclusions on causality should be handled carefully. The main prediction of the IPTS has been proven in a general population sample. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Economic Model Predictive Control for Building Climate Control in a Smart Grid

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2012-01-01

    and electricity price. Simulation studies demonstrate the capabilities of the proposed model and algorithm. Compared to traditional operation of heat pumps with constant electricity prices, the optimized operating strategy saves 25-33% of the electricity cost.......Model Predictive Control (MPC) can be used to control a system of energy producers and consumers in a Smart Grid. In this paper, we use heat pumps for heating residential buildings with a floor heating system. We use the thermal capacity of the building to shift the electricity consumptions...... to periods with low energy prices. In this way the heating system of the house becomes a flexible power consumer in the Smart Grid. This scenario is relevant for systems with a significant share of stochastic energy producers, e.g. wind turbines, where the ability to shift power consumption according...

  3. General life satisfaction predicts dementia in community living older adults: a prospective cohort study.

    Science.gov (United States)

    Peitsch, Lorraine; Tyas, Suzanne L; Menec, Verena H; St John, Philip D

    2016-07-01

    Low life satisfaction predicts adverse outcomes, and may predict dementia. The objectives were: (1) to determine if life satisfaction predicts dementia over a five year period in those with normal cognition at baseline; and (2) to determine if different aspects of life satisfaction differentially predict dementia. Secondary analysis of an existing population-based cohort study with initial assessment in 1991 and follow-up five years later. Initially, 1,751 adults age 65+ living in the community were sampled from a representative sampling frame. Of these, 1,024 were alive and had complete data at time 2, of whom 96 were diagnosed with dementia. Life satisfaction was measured using the Terrible-Delightful scale, which measures overall life satisfaction on a 7-point scale, as well as various aspects of life satisfaction (e.g. friendships, finances, etc.) Dementia was diagnosed by clinical examination using DSM-IIIR criteria. Logistic regression models were constructed for the outcome of dementia at time 2, and adjusted for age, gender, education, and comorbidities. Overall life satisfaction predicted dementia five years later, at time 2. The unadjusted Odds Ratio (OR; 95% confidence interval) for dementia at time 2 was 0.72 (0.55, 0.95) per point. The adjusted OR for dementia was 0.70 (0.51, 0.96). No individual item on the life satisfaction scale predicted dementia. However, the competing risk of mortality was very high for some items. A global single-item measure of life satisfaction predicts dementia over a five year period in older adults without cognitive impairment.

  4. Image-Based Visual Servoing for Manipulation Via Predictive Control – A Survey of Some Results

    Directory of Open Access Journals (Sweden)

    Corneliu Lazăr

    2016-09-01

    Full Text Available In this paper, a review of predictive control algorithms developed by the authors for visual servoing of robots in manipulation applications is presented. Using these algorithms, a control predictive framework was created for image-based visual servoing (IBVS systems. Firstly, considering the point features, in the year 2008 we introduced an internal model predictor based on the interaction matrix. Secondly, distinctly from the set-point trajectory, we introduced in 2011 the reference trajectory using the concept from predictive control. Finally, minimizing a sum of squares of predicted errors, the optimal input trajectory was obtained. The new concept of predictive control for IBVS systems was employed to develop a cascade structure for motion control of robot arms. Simulation results obtained with a simulator for predictive IBVS systems are also presented.

  5. A double-blind placebo-controlled study of controlled release fluvoxamine for the treatment of generalized social anxiety disorder

    NARCIS (Netherlands)

    Westenberg, HGM; Stein, DJ; Yang, HC; Li, D; Barbato, LM

    This was a randomized double-blind placebo-controlled multicenter study to assess the efficacy, safety, and tolerability of fluvoxamine in a controlled release (CR) formulation for treatment of generalized social anxiety disorder (GSAD). A total of 300 subjects with GSAD were randomly assigned to

  6. Implementation of the Dutch low back pain guideline for general practitioners: a cluster randomized controlled trial

    NARCIS (Netherlands)

    Engers, AJ; Wensing, M.; van Tulder, M.; Timmermans, A.; Oostendorp, R.A.B.; Koes, B.W.; Grol, R.P.T.M.

    2005-01-01

    STUDY DESIGN.: Cluster randomized controlled trial for a multifaceted implementation strategy. OBJECTIVES.: To assess the effectiveness of tailored interventions (multifaceted implementation strategy) to implement the Dutch low back pain guideline for general practitioners with regard to adherence

  7. Implementation of the Dutch low back pain guideline for general practitioners: a cluster randomized controlled trial.

    NARCIS (Netherlands)

    Engers, A.J.; Wensing, M.J.P.; Tulder, M.W. van; Timmermans, A.; Oostendorp, R.A.B.; Koes, B.W.; Grol, R.P.T.M.

    2005-01-01

    STUDY DESIGN: Cluster randomized controlled trial for a multifaceted implementation strategy. OBJECTIVES: To assess the effectiveness of tailored interventions (multifaceted implementation strategy) to implement the Dutch low back pain guideline for general practitioners with regard to adherence to

  8. Soft landing on an irregular shape asteroid using Multiple-Horizon Multiple-Model Predictive Control

    Science.gov (United States)

    AlandiHallaj, MohammadAmin; Assadian, Nima

    2017-11-01

    This study has introduced a predictive framework including a heuristic guidance law named Predictive Path Planning and Multiple-Horizon Multiple-Model Predictive Control as the control scheme for soft landing on an irregular-shaped asteroid. The dynamical model of spacecraft trajectory around an asteroid is introduced. The reference-landing trajectory is generated using Predictive Path Planning. Not only does the presented guidance law satisfy the collision avoidance constraint, but also guarantees the landing accuracy and vertical landing condition. Multiple-Horizon Multiple-Model Predictive Control is employed to make the spacecraft track the designed reference trajectory. The proposed control approach, which is a Model Predictive Control scheme, utilizes several prediction models instead of one. In this manner, it heritages the advantages of optimality and tackling external disturbances and model uncertainties from classical Model Predictive Control and at the same time has the advantage of lower computational burden than Model Predictive Control. Finally, numerical simulations are carried out to demonstrate the feasibility and effectiveness of the proposed control approach in achieving the desired conditions in presence of uncertainties and disturbances.

  9. A quality control method for nuclear instrumentation and control systems based on software safety prediction

    Science.gov (United States)

    Son, Han Seong; Seong, Poong Hyun

    2000-04-01

    In the case of safety-related applications like nuclear instrumentation and control (NI&C), safety-oriented quality control is required. The objective of this paper is to present a software safety classification method as a safety-oriented quality control tool. Based on this method, we predict the risk (and thus safety) of software items that are at the core of NI&C systems. Then we classify the software items according to the degree of the risk. The method can be used earlier than at the detailed design phase. Furthermore, the method can also be used in all the development phases without major changes. The proposed method seeks to utilize the measures that can be obtained from the safety analysis and requirements analysis. Using the measures proved to be desirable in a few aspects. The authors have introduced fuzzy approximate reasoning to the classification method because experts' knowledge covers the vague frontiers between good quality and bad quality with linguistic uncertainty and fuzziness. Fuzzy Colored Petri Net (FCPN) is introduced in order to offer a formal framework for the classification method and facilitate the knowledge representation, modification, or verification. Through the proposed quality control method, high-quality NI&C systems can be developed effectively and used safely.

  10. Los principios generales del derecho en el control jurisdiccional de las ordenanzas fiscales

    OpenAIRE

    Hernández Guijarro, Fernando

    2014-01-01

    El presente trabajo de tesis doctoral tiene por objeto comprobar cómo o de qué manera actúan los Principios Generales del Derecho en el control jurisdiccional de las Ordenanzas Fiscales. A tal efecto, se planta un primer capítulo sobre los principios generales donde analizamos su historia, concepto, naturaleza y funciones. Seguidamente se estudian los instrumentos procesales para el ejercicio de ese control jurisdiccional y, concretamente, se analiza el recurso directo, el recurso indirecto -...

  11. Sound Zones: On Performance Prediction of Contrast Control Methods

    DEFF Research Database (Denmark)

    Møller, Martin Bo; Olsen, Martin

    2016-01-01

    Low frequency personal sound zones can be created by controlling the squared sound pressure in separate spatial confined control regions. Several methods have been proposed for realizing this scenario, with different constraints and performance. Extrapolating knowledge of the resulting acoustic...... frequency sound zones are compared in an experimental study with eight woofers surrounding two control zones....

  12. Positive experience, self-efficacy, and action control predict physical activity changes: a moderated mediation analysis.

    Science.gov (United States)

    Parschau, Linda; Fleig, Lena; Koring, Milena; Lange, Daniela; Knoll, Nina; Schwarzer, Ralf; Lippke, Sonia

    2013-05-01

    Experiencing positive consequences of one's physical activity is supposed to facilitate further activity. This motivational outcome might be generated by an increase in perceived self-efficacy. In addition to such a mediator effect, we examine whether this applies generally or only under conditions of volitional control. For this purpose, perceived action control was considered as a putative moderator. N = 193 students participated in a study with three measurement points in time. At baseline, positive experience with previous physical activity was measured as a predictor of physical activity. Two weeks later, self-efficacy and action control variables were assessed as putative mediator and moderator, respectively. After another 2 weeks, physical activity was measured as the outcome. A moderated mediation model was specified with baseline physical activity and sex as covariates. Self-efficacy was found to mediate between initial positive experience and later physical activity, and this mediation was moderated by action control. Participants' perceptions of positive experience were associated with their subsequent self-efficacy fostering physical activity. However, persons with low levels of action control did not translate positive experience into physical activity via self-efficacy. What is already known on this subject? Numerous studies have shown that exercise-specific self-efficacy predicts subsequent physical activity. Prior positive experience with physical activity is suggested to be associated with exercise-specific self-efficacy. Furthermore, action control was found to be beneficial for the maintenance of physical activity. What does this study add? This study unveils the mechanisms between these social-cognitive determinants: our longitudinal results suggest that the mediation of positive experience and subsequent physical activity via self-efficacy is moderated by action control. Persons with low levels of action control did not translate positive

  13. Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models

    International Nuclear Information System (INIS)

    Yock, Adam D.; Kudchadker, Rajat J.; Rao, Arvind; Dong, Lei; Beadle, Beth M.; Garden, Adam S.; Court, Laurence E.

    2014-01-01

    Purpose: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Methods: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. Results: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: −11.6%–23.8%) and 14.6% (range: −7.3%–27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: −6.8%–40.3%) and 13.1% (range: −1.5%–52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: −11.1%–20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. Conclusions: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography

  14. Validation of a predictive model for smart control of electrical energy storage

    NARCIS (Netherlands)

    Homan, Bart; van Leeuwen, Richard Pieter; Smit, Gerardus Johannes Maria; Zhu, Lei; de Wit, Jan B.

    2016-01-01

    The purpose of this paper is to investigate the applicability of a relatively simple model which is based on energy conservation for model predictions as part of smart control of thermal and electric storage. The paper reviews commonly used predictive models. Model predictions of charging and

  15. Double product reflects the predictive power of systolic pressure in the general population

    DEFF Research Database (Denmark)

    Schutte, Rudolph; Thijs, Lutgarde; Asayama, Kei

    2013-01-01

    The double product (DP), consisting of the systolic blood pressure (SBP) multiplied by the pulse rate (PR), is an index of myocardial oxygen consumption, but its prognostic value in the general population remains unknown....

  16. Prediction in Partial Duration Series With Generalized Pareto-Distributed Exceedances

    DEFF Research Database (Denmark)

    Rosbjerg, Dan; Madsen, Henrik; Rasmussen, Peter Funder

    1992-01-01

    As a generalization of the common assumption of exponential distribution of the exceedances in Partial duration series the generalized Pareto distribution has been adopted. Estimators for the parameters are presented using estimation by both method of moments and probability-weighted moments......-weighted moments. Maintaining the generalized Pareto distribution as the parent exceedance distribution the T-year event is estimated assuming the exceedances to be exponentially distributed. For moderately long-tailed exceedance distributions and small to moderate sample sizes it is found, by comparing mean...... square errors of the T-year event estimators, that the exponential distribution is preferable to the correct generalized Pareto distribution despite the introduced model error and despite a possible rejection of the exponential hypothesis by a test of significance. For moderately short-tailed exceedance...

  17. Genetic variation in ABCA1 predicts ischemic heart disease in the general population

    DEFF Research Database (Denmark)

    Frikke-Schmidt, Ruth; Nordestgaard, BG; Jensen, Gorm B

    2008-01-01

    We tested the hypothesis that 6 nonsynonymous single nucleotide polymorphisms (SNPs) in ATP-Binding-Cassette transporter A1 (ABCA1) affect risk of ischemic heart disease (IHD) in the general population....

  18. Design of a new PID controller using predictive functional control optimization for chamber pressure in a coke furnace.

    Science.gov (United States)

    Zhang, Jianming

    2017-03-01

    An improved proportional-integral-derivative (PID) controller based on predictive functional control (PFC) is proposed and tested on the chamber pressure in an industrial coke furnace. The proposed design is motivated by the fact that PID controllers for industrial processes with time delay may not achieve the desired control performance because of the unavoidable model/plant mismatches, while model predictive control (MPC) is suitable for such situations. In this paper, PID control and PFC algorithm are combined to form a new PID controller that has the basic characteristic of PFC algorithm and at the same time, the simple structure of traditional PID controller. The proposed controller was tested in terms of set-point tracking and disturbance rejection, where the obtained results showed that the proposed controller had the better ensemble performance compared with traditional PID controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Immediate and proactive effects of controllability and predictability on plasma cortisol responses to shocks in dogs.

    Science.gov (United States)

    Dess, N K; Linwick, D; Patterson, J; Overmier, J B; Levine, S

    1983-12-01

    Controllability and predictability are important modulators of the behavioral effects of aversive stimulation on animals. An experiment was conducted to further investigate both the immediate and proactive effects of controllability and predictability of shocks on adrenocortical responsivity. In an initial stress induction phase, the controllability and predictability of electric shocks were independently varied in groups of dogs, and plasma cortisol responses were measured. In a subsequent test phase, all groups of dogs received identical shocks in a novel situation. Cortisol responses to these test shocks were analyzed as a function of the controllability and predictability of previous induction shocks. The results showed that during stress induction, uncontrollable shocks produced significantly greater cortisol elevations that controllable shocks but that predictability had no significant effect on cortisol responses. However, unpredictable shocks during stress induction acted proactively to significantly increase cortisol response to novel test shocks, whereas prior controllability did not modulate subsequent responsivity to novel shocks.

  20. Factors predicting team climate, and its relationship with quality of care in general practice

    OpenAIRE

    Goh, Teik T; Eccles, Martin P; Steen, Nick

    2009-01-01

    Abstract Background Quality of care in general practice may be affected by the team climate perceived by its health and non-health professionals. Better team working is thought to lead to higher effectiveness and quality of care. However, there is limited evidence available on what affects team functioning and its relationship with quality of care in general practice. This study aimed to explore individual and practice factors that were associated with team climate, and to explore the relatio...

  1. Hierarchical Control of Droop-Controlled DC and AC Microgrids - A General Approach Towards Standardization

    DEFF Research Database (Denmark)

    Guerrero, Josep M.; Vásquez, Juan V.; Teodorescu, Remus

    2009-01-01

    from ISA-95 and electrical dispatching standards to endow smartness and flexibility to microgrids. The hierarchical control proposed consist of three levels: i) the primary control is based on the droop method, including an output impedance virtual loop; ii) the secondary control allows restoring...

  2. Amygdala Reactivity to Emotional Faces in the Prediction of General and Medication-Specific Responses to Antidepressant Treatment in the Randomized iSPOT-D Trial.

    Science.gov (United States)

    Williams, Leanne M; Korgaonkar, Mayuresh S; Song, Yun C; Paton, Rebecca; Eagles, Sarah; Goldstein-Piekarski, Andrea; Grieve, Stuart M; Harris, Anthony W F; Usherwood, Tim; Etkin, Amit

    2015-09-01

    Although the cost of poor treatment outcomes of depression is staggering, we do not yet have clinically useful methods for selecting the most effective antidepressant for each depressed person. Emotional brain activation is altered in major depressive disorder (MDD) and implicated in treatment response. Identifying which aspects of emotional brain activation are predictive of general and specific responses to antidepressants may help clinicians and patients when making treatment decisions. We examined whether amygdala activation probed by emotion stimuli is a general or differential predictor of response to three commonly prescribed antidepressants, using functional magnetic resonance imaging (fMRI). A test-retest design was used to assess patients with MDD in an academic setting as part of the International Study to Predict Optimized Treatment in Depression. A total of 80 MDD outpatients were scanned prior to treatment and 8 weeks after randomization to the selective serotonin reuptake inhibitors escitalopram and sertraline and the serotonin-norepinephrine reuptake inhibitor, venlafaxine-extended release (XR). A total of 34 matched controls were scanned at the same timepoints. We quantified the blood oxygen level-dependent signal of the amygdala during subliminal and supraliminal viewing of facial expressions of emotion. Response to treatment was defined by ⩾50% symptom improvement on the 17-item Hamilton Depression Rating Scale. Pre-treatment amygdala hypo-reactivity to subliminal happy and threat was a general predictor of treatment response, regardless of medication type (Cohen's d effect size 0.63 to 0.77; classification accuracy, 75%). Responders showed hypo-reactivity compared to controls at baseline, and an increase toward 'normalization' post-treatment. Pre-treatment amygdala reactivity to subliminal sadness was a differential moderator of non-response to venlafaxine-XR (Cohen's d effect size 1.5; classification accuracy, 81%). Non-responders to

  3. Mechanisms of Intentional Binding and Sensory Attenuation: The Role of Temporal Prediction, Temporal Control, Identity Prediction, and Motor Prediction

    Science.gov (United States)

    Hughes, Gethin; Desantis, Andrea; Waszak, Florian

    2013-01-01

    Sensory processing of action effects has been shown to differ from that of externally triggered stimuli, with respect both to the perceived timing of their occurrence (intentional binding) and to their intensity (sensory attenuation). These phenomena are normally attributed to forward action models, such that when action prediction is consistent…

  4. Anorexic self-control and bulimic self-hate: differential outcome prediction from initial self-image.

    Science.gov (United States)

    Birgegård, Andreas; Björck, Caroline; Norring, Claes; Sohlberg, Staffan; Clinton, David

    2009-09-01

    The study investigated initial self-image (structural analysis of social behavior) and its relation to 36-month outcome, among patients with anorexia nervosa and bulimia nervosa. Hypotheses were that degree of different aspects of self-image would predict outcome in the groups. Participants were 52 patients with anorexia and 91 with bulimia from a longitudinal naturalistic database, and outcome measures included eating disorder and psychiatric symptoms and a general outcome index. Stepwise regression was used to investigate which self-image variables were related to outcome, and multiple regression contrasted the groups directly on each obtained predictor. Consistent with hypotheses, in bulimia degree of self-hate/self-love moderately predicted outcome, whereas self-control-related variables powerfully predicted outcome in anorexia. It is important to focus on self-image in the treatment of both diagnostic groups, but especially in anorexia nervosa, where control-submission interactions between patient and therapist should be handled with care.

  5. Reliable NonLinear Model-Predictive Control via Validated Simulation

    OpenAIRE

    Alexandre dit Sandretto, Julien

    2017-01-01

    Model-Predictive Control (MPC) is one of the most advanced control technique nowadays. Indeed,MPC approaches are well known for their robustness and stability properties. Nevertheless, NonlinearModel-Predictive Control (NMPC), the extension of MPC in the nonlinear world, still poses challenging theoretical, computationaland implementation issues. By the help of validated simulation, which can handle nonlinear models, a new algorithmfor a robust by-construction control strategy based on NMPC i...

  6. Motivational "spill-over" during weight control: increased self-determination and exercise intrinsic motivation predict eating self-regulation.

    Science.gov (United States)

    Mata, Jutta; Silva, Marlene N; Vieira, Paulo N; Carraça, Eliana V; Andrade, Ana M; Coutinho, Sílvia R; Sardinha, Luis B; Teixeira, Pedro J

    2009-11-01

    Successful weight management relies on at least two health behaviors, eating and exercise. However, little is known about their interaction on a motivational and behavioral level. Based on the Hierarchical Model of Motivation the authors examined whether exercise-specific motivation can transfer to eating regulation during a lifestyle weight control program. The authors further investigated whether general, treatment-related, and exercise motivation underlie the relation between increased exercise and improved eating regulation. Overweight/obese women participated in a 1-year randomized controlled trial (N = 239). The intervention focused on promoting physical activity and internal motivation for exercise and weight loss, following Self-Determination Theory. The control group received general health education. General and exercise specific self-determination, eating self-regulation variables, and physical activity behavior. General self-determination and more autonomous exercise motivation predicted eating self-regulation over 12 months. Additionally, general and exercise self-determination fully mediated the relation between physical activity and eating self-regulation. Increased general self-determination and exercise motivation seem to facilitate improvements in eating self-regulation during weight control in women. These motivational mechanisms also underlie the relationship between improvements in exercise behavior and eating regulation. PsycINFO Database Record (c) 2009 APA, all rights reserved.

  7. Feedback min-max model predictive control using robust one-step sets

    Science.gov (United States)

    Cychowski, Marcin T.; O'Mahony, Tom

    2010-07-01

    A solution to the infinite-horizon min-max model predictive control (MPC) problem of constrained polytopic systems has recently been defined in terms of a sequence of free control moves over a fixed horizon and a state feedback law in the terminal region using a time-varying terminal cost. The advantage of this formulation is the enlargement of the admissible set of initial states without sacrificing local optimality, but this comes at the expense of higher computational complexity. This article, by means of a counterexample, shows that the robust feasibility and stability properties of such algorithms are not, in general, guaranteed when more than one control move is adopted. For this reason, this work presents a novel formulation of min-max MPC based on the concept of within-horizon feedback and robust contractive set theory that ensures robust stability for any choice of the control horizon. A parameter-dependent feedback extension is also proposed and analysed. The effectiveness of the algorithms is demonstrated with two numerical examples.

  8. Predictive Models and Tools for Assessing Chemicals under the Toxic Substances Control Act (TSCA)

    Science.gov (United States)

    EPA has developed databases and predictive models to help evaluate the hazard, exposure, and risk of chemicals released to the environment and how workers, the general public, and the environment may be exposed to and affected by them.

  9. The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies.

    Science.gov (United States)

    Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

    2013-11-01

    The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. A three-part longitudinal predictive validity study of selection into training for UK general practice. In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered.

  10. The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies

    Science.gov (United States)

    Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

    2013-01-01

    Background The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study Aim To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. Design and setting A three-part longitudinal predictive validity study of selection into training for UK general practice. Method In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Results Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. Conclusion In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered. PMID:24267856

  11. Generalized bottom-tau unification, neutrino oscillations and dark matter: Predictions from a lepton quarticity flavor approach

    Science.gov (United States)

    Centelles Chuliá, Salvador; Srivastava, Rahul; Valle, José W. F.

    2017-10-01

    We propose an A4 extension of the Standard Model with a Lepton Quarticity symmetry correlating dark matter stability with the Dirac nature of neutrinos. The flavor symmetry predicts (i) a generalized bottom-tau mass relation involving all families, (ii) small neutrino masses are induced a la seesaw, (iii) CP must be significantly violated in neutrino oscillations, (iv) the atmospheric angle θ23 lies in the second octant, and (v) only the normal neutrino mass ordering is realized.

  12. Generalized bottom-tau unification, neutrino oscillations and dark matter: Predictions from a lepton quarticity flavor approach

    Directory of Open Access Journals (Sweden)

    Salvador Centelles Chuliá

    2017-10-01

    Full Text Available We propose an A4 extension of the Standard Model with a Lepton Quarticity symmetry correlating dark matter stability with the Dirac nature of neutrinos. The flavor symmetry predicts (i a generalized bottom-tau mass relation involving all families, (ii small neutrino masses are induced a la seesaw, (iii CP must be significantly violated in neutrino oscillations, (iv the atmospheric angle θ23 lies in the second octant, and (v only the normal neutrino mass ordering is realized.

  13. Prediction of elders' general health based on positive and negative perfectionism and type-d personality.

    Science.gov (United States)

    Karaminia, Reza; Soltani, Mohsen Ahmadi Tahour; Bagherian-Sararoudi, Reza

    2013-06-01

    Multiple factors such as retirement, work disability, social rejection, physical illness and etc., have an impact on general health of the elders. One factor among others is the role of psychological variables. The study is intended to assess the effect of positive and negative perfectionism and type-D personality (distressed) on general health of the elders. In this descriptive-correlation study, 80 people (47 male and 33 female) were selected from residents of Nursing Home in Hamadan and Malayer using non-probability (accessible) sampling method. They responded to the questionnaires of type-D Personality, Goldberg and Hillier's General Health and Positive and Negative Perfectionism of Terry-Short et al. Positive perfectionism (r = 0.30) and type-D personality (r = 0.32) had significant correlation with general health. Multiple regression analysis revealed that positive perfectionism and type-D personality could explain at least 49% of the variance in general health. Concerning the variables of negative affectivity, social inhibition and social function, the females' mean was higher than that of males and considering the variables of positive perfectionism, and social functioning, the males' mean was higher than that of females. Positive perfectionism decreases mental disorder of the elders by creating optimistic attitudes and enhancing social functions. On the other hand, type-D personality, unlike positive perfectionism, makes elders susceptible to physical illness and mental disorder.

  14. Predicting homophobic behavior among heterosexual youth: domain general and sexual orientation-specific factors at the individual and contextual level.

    Science.gov (United States)

    Poteat, V Paul; DiGiovanni, Craig D; Scheer, Jillian R

    2013-03-01

    As a form of bias-based harassment, homophobic behavior remains prominent in schools. Yet, little attention has been given to factors that underlie it, aside from bullying and sexual prejudice. Thus, we examined multiple domain general (empathy, perspective-taking, classroom respect norms) and sexual orientation-specific factors (sexual orientation identity importance, number of sexual minority friends, parents' sexual minority attitudes, media messages). We documented support for a model in which these sets of factors converged to predict homophobic behavior, mediated through bullying and prejudice, among 581 students in grades 9-12 (55 % female). The structural equation model indicated that, with the exception of media messages, these additional factors predicted levels of prejudice and bullying, which in turn predicted the likelihood of students to engage in homophobic behavior. These findings highlight the importance of addressing multiple interrelated factors in efforts to reduce bullying, prejudice, and discrimination among youth.

  15. PID and predictive control of electrical drives and power converters using MATLAB/Simulink

    CERN Document Server

    Wang, Liuping; Yoo, Dae; Gan, Lu; Ng, Ki

    2015-01-01

    A timely introduction to current research on PID and predictive control by one of the leading authors on the subject PID and Predictive Control of Electric Drives and Power Supplies using MATLAB/Simulink examines the classical control system strategies, such as PID control, feed-forward control and cascade control, which are widely used in current practice.  The authors share their experiences in actual design and implementation of the control systems on laboratory test-beds, taking the reader from the fundamentals through to more sophisticated design and analysis.    The book contains secti

  16. Prediction of User Preference over Shared Control Paradigms for a Robotic Wheelchair

    Science.gov (United States)

    2017-07-20

    control number. 15-08-2017 Conference paper Prediction of User Preference over Shared-Control Paradigms for a Robotic Wheelchair N00014-16-1-2247...22217, United States. ONR IEEE green open access. Author final manuscript. Presented at the 2017 International Conference on Rehabilitation Robotics ...Smart wheelchair; Robotics autonomy; Prediction of User Preference; Machine Learning U U U 6 Brenna D. Argall +1 847 467 0862 Prediction of User

  17. Just-In-Time predictive control for a two-wheeled robot

    OpenAIRE

    Nakpong, Nuttapun; Yamamoto, Shigeru

    2012-01-01

    In this paper, we introduce the use of Just-In-Time predictive control to enhance the stability of a two-wheeled robot. Just-In-Time predictive control uses a database which includes a huge amounts of input-output data of the two-wheeled robot and predicts its future movements based on a Just-In-Time algorithm. © 2012 IEEE.

  18. Predictive power of task orientation, general self-efficacy and self-determined motivation on fun and boredom

    Directory of Open Access Journals (Sweden)

    Lorena Ruiz-González

    2015-12-01

    Full Text Available Abstract The aim of this study was to test the predictive power of dispositional orientations, general self-efficacy and self-determined motivation on fun and boredom in physical education classes, with a sample of 459 adolescents between 13 and 18 with a mean age of 15 years (SD = 0.88. The adolescents responded to four Likert scales: Perceptions of Success Questionnaire, General Self-Efficacy Scale, Sport Motivation Scale and Intrinsic Satisfaction Questionnaire in Sport. The results showed the structural regression model showed that task orientation and general self-efficacy positively predicted self-determined motivation and this in turn positively predicted more fun and less boredom in physical education classes. Consequently, the promotion of an educational task-oriented environment where learners perceive their progress and make them feel more competent, will allow them to overcome the intrinsically motivated tasks, and therefore they will have more fun. Pedagogical implications for less boredom and more fun in physical education classes are discussed.

  19. Load-following Operation for PWRs Using Fuzzy Model Predictive Control

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sim Won; Kim, Jae Hwan; Na, Man Gyun; Yu, Keuk Jong [Chosun University, Gwangju (Korea, Republic of)

    2011-05-15

    In this study, a fuzzy model predictive control method is applied to design an automatic controller for thermal power and axial shape index (ASI) in pressurized water reactors. The future reactor power and ASI are predicted by using the fuzzy model identified by a subtractive clustering method of a fast and robust algorithm. The genetic algorithm that is useful to accomplish multiple objectives is used to optimize the fuzzy model predictive controller. A 3-dimensional nuclear reactor analysis code is used to verify the proposed controller for a nuclear reactor. From results of numerical simulation to check the performance of the proposed controller at the increase or decrease of a desired load (rapid change, load follow), it was found that the nuclear power level and ASI controlled by the proposed fuzzy model predictive controller could track the desired power level and ASI very well

  20. 18 CFR 1304.202 - General sediment and erosion control provisions.

    Science.gov (United States)

    2010-04-01

    ... erosion control provisions. 1304.202 Section 1304.202 Conservation of Power and Water Resources TENNESSEE... OTHER ALTERATIONS TVA-Owned Residential Access Shoreland § 1304.202 General sediment and erosion control provisions. (a) During construction activities, TVA shall require that appropriate erosion and sediment...

  1. Self-organization of critical behavior in controlled general queueing models

    International Nuclear Information System (INIS)

    Blanchard, Ph.; Hongler, M.-O.

    2004-01-01

    We consider general queueing models of the (G/G/1) type with service times controlled by the busy period. For feedback control mechanisms driving the system to very high traffic load, it is shown the busy period probability density exhibits a generic -((3)/(2)) power law which is a typical mean field behavior of SOC models

  2. Coordinated model predictive reach control for irrigation canals

    NARCIS (Netherlands)

    Negenborn, R.R.; Van Overloop, P.J.; De Schutter, B.

    2009-01-01

    Irrigation canals are large-scale systems, covering vast geographical areas, and consisting of many interconnected canal reaches that interact with control structures such as pumps and gates. The control of such irrigation canals is usually done in a manual way, in which a human operator travels

  3. Application of Predictive Control in District Heating Systems

    DEFF Research Database (Denmark)

    Palsson, Olafur Petur; Madsen, Henrik; Søgaard, Henning Tangen

    1993-01-01

    In district heating systems, and in particular if the heat production cakes place at a combined heat and power (CHP) plant, a reasonable control strategy is to keep the supply temperature from the district heating plant as low as possible. However, the control is subject to some restrictions...

  4. Core Engine Noise Control Program. Volume III. Prediction Methods

    Science.gov (United States)

    1974-08-01

    JET dOISE 2.1 OBJECTIVES The objective of this work effort was to develop a jet noise prediction procedure based on detailed acoustic experiments on...RD-71-1Ol-Volumne 1, 1971, Wyle Laboratories, Inc., El Segundo, California. 2.2.1-4 Williams , T.J., Ali, M.R.M., and Anderson, J.S.; "Noise and Flow

  5. Nonlinear model predictive control for chemical looping process

    Energy Technology Data Exchange (ETDEWEB)

    Joshi, Abhinaya; Lei, Hao; Lou, Xinsheng

    2017-08-22

    A control system for optimizing a chemical looping ("CL") plant includes a reduced order mathematical model ("ROM") that is designed by eliminating mathematical terms that have minimal effect on the outcome. A non-linear optimizer provides various inputs to the ROM and monitors the outputs to determine the optimum inputs that are then provided to the CL plant. An estimator estimates the values of various internal state variables of the CL plant. The system has one structure adapted to control a CL plant that only provides pressure measurements in the CL loops A and B, a second structure adapted to a CL plant that provides pressure measurements and solid levels in both loops A, and B, and a third structure adapted to control a CL plant that provides full information on internal state variables. A final structure provides a neural network NMPC controller to control operation of loops A and B.

  6. Modeling generalized interline power-flow controller (GIPFC using 48-pulse voltage source converters

    Directory of Open Access Journals (Sweden)

    Amir Ghorbani

    2018-05-01

    Full Text Available Generalized interline power-flow controller (GIPFC is one of the voltage-source controller (VSC-based flexible AC transmission system (FACTS controllers that can independently regulate the power-flow over each transmission line of a multiline system. This paper presents the modeling and performance analysis of GIPFC based on 48-pulsed voltage-source converters. This paper deals with a cascaded multilevel converter model, which is a 48-pulse (three levels voltage source converter. The voltage source converter described in this paper is a harmonic neutralized, 48-pulse GTO converter. The GIPFC controller is based on d-q orthogonal coordinates. The algorithm is verified using simulations in MATLAB/Simulink environment. Comparisons between unified power flow controller (UPFC and GIPFC are also included. Keywords: Generalized interline power-flow controller (GIPFC, Voltage source converter (VCS, 48-pulse GTO converter

  7. An estimator-based distributed voltage-predictive control strategy for ac islanded microgrids

    DEFF Research Database (Denmark)

    Wang, Yanbo; Chen, Zhe; Wang, Xiongfei

    2015-01-01

    distributed generator, where the voltage estimator serves as an essential tool to obtain network voltages response without using communication links, while the voltage predictive controller is able to implement offset-free voltage control for a specified bus. The dynamic performance of the proposed voltage......This paper presents an estimator-based voltage predictive control strategy for AC islanded microgrids, which is able to perform voltage control without any communication facilities. The proposed control strategy is composed of a network voltage estimator and a voltage predictive controller for each...... control strategy is analyzed through small signal analysis method, from which the design guideline for the controller parameters is formulated. Furthermore, the robustness of the proposed voltage control strategy is investigated under a series of parameters uncertainties, including the line parameters...

  8. Improving prediction of ischemic cardiovascular disease in the general population using apolipoprotein B

    DEFF Research Database (Denmark)

    Benn, M; Nordestgaard, B; Jensen, Gorm Boje

    2007-01-01

    events than low-density lipoprotein cholesterol. Methods and Results- We studied 9231 asymptomatic women and men from the Danish general population followed prospectively for 8 years and observed the following incident events: ischemic heart disease 591, myocardial infarction 278, ischemic...

  9. A Genetically Optimized Predictive System for Success in General Chemistry Using a Diagnostic Algebra Test

    Science.gov (United States)

    Cooper, Cameron I.; Pearson, Paul T.

    2012-01-01

    In higher education, many high-enrollment introductory courses have evolved into "gatekeeper" courses due to their high failure rates. These courses prevent many students from attaining their educational goals and often become graduation roadblocks. At the authors' home institution, general chemistry has become a gatekeeper course in which…

  10. The General Factor of Personality (GFP) and parental support: testing a prediction from Life History Theory

    NARCIS (Netherlands)

    Linden, D. van der; Figueredo, A.J.; Leeuw, R.N.H. de; Scholte, R.H.J.; Engels, R.C.M.E.

    2012-01-01

    In the present study, we tested whether the General Factor of Personality (GFP) is related to the level of parental support. The GFP is assumed to occupy the apex of the hierarchy of human personality structure and is believed to reflect a socially and sexually selected aggregate of behavioral

  11. Factors predicting team climate, and its relationship with quality of care in general practice

    Directory of Open Access Journals (Sweden)

    Eccles Martin P

    2009-08-01

    Full Text Available Abstract Background Quality of care in general practice may be affected by the team climate perceived by its health and non-health professionals. Better team working is thought to lead to higher effectiveness and quality of care. However, there is limited evidence available on what affects team functioning and its relationship with quality of care in general practice. This study aimed to explore individual and practice factors that were associated with team climate, and to explore the relationship between team climate and quality of care. Methods Cross sectional survey of a convenience sample of 14 general practices and their staff in South Tyneside in the northeast of England. Team climate was measured using the short version of Team Climate Inventory (TCI questionnaire. Practice characteristics were collected during a structured interview with practice managers. Quality was measured using the practice Quality and Outcome Framework (QOF scores. Results General Practitioners (GP had a higher team climate scores compared to other professionals. Individual's gender and tenure, and number of GPs in the practice were significantly predictors of a higher team climate. There was no significant correlation between mean practice team climate scores (or subscales with QOF scores. Conclusion The absence of a relationship between a measure of team climate and quality of care in this exploratory study may be due to a number of methodological problems. Further research is required to explore how to best measure team functioning and its relationship with quality of care.

  12. Factors predicting team climate, and its relationship with quality of care in general practice.

    Science.gov (United States)

    Goh, Teik T; Eccles, Martin P; Steen, Nick

    2009-08-04

    Quality of care in general practice may be affected by the team climate perceived by its health and non-health professionals. Better team working is thought to lead to higher effectiveness and quality of care. However, there is limited evidence available on what affects team functioning and its relationship with quality of care in general practice. This study aimed to explore individual and practice factors that were associated with team climate, and to explore the relationship between team climate and quality of care. Cross sectional survey of a convenience sample of 14 general practices and their staff in South Tyneside in the northeast of England. Team climate was measured using the short version of Team Climate Inventory (TCI) questionnaire. Practice characteristics were collected during a structured interview with practice managers. Quality was measured using the practice Quality and Outcome Framework (QOF) scores. General Practitioners (GP) had a higher team climate scores compared to other professionals. Individual's gender and tenure, and number of GPs in the practice were significantly predictors of a higher team climate. There was no significant correlation between mean practice team climate scores (or subscales) with QOF scores. The absence of a relationship between a measure of team climate and quality of care in this exploratory study may be due to a number of methodological problems. Further research is required to explore how to best measure team functioning and its relationship with quality of care.

  13. Does Empathy Predict Instructional Assignment-Related Stress? A Study in Special and General Education Teachers

    Science.gov (United States)

    Platsidou, Maria; Agaliotis, Ioannis

    2017-01-01

    The role of empathy in the teaching profession has been vastly investigated in relation to its effect on students, but research on how teachers' empathy affects their own well-being at work is limited. This study investigated empathy and instructional assignment-related stress factors of primary school teachers serving in general or special…

  14. SIMULATION AND PREDICTION OF THE PROCESS BASED ON THE GENERAL LOGISTIC MAPPING

    Directory of Open Access Journals (Sweden)

    V. V. Skalozub

    2013-11-01

    Full Text Available Purpose. The aim of the research is to build a model of the generalzed logistic mapping and assessment of the possibilities of its use for the formation of the mathematical description, as well as operational forecasts of parameters of complex dynamic processes described by the time series. Methodology. The research results are obtained on the basis of mathematical modeling and simulation of nonlinear systems using the tools of chaotic dynamics. Findings. A model of the generalized logistic mapping, which is used to interpret the characteristics of dynamic processes was proposed. We consider some examples of representations of processes based on enhanced logistic mapping varying the values of model parameters. The procedures of modeling and interpretation of the data on the investigated processes, represented by the time series, as well as the operational forecasting of parameters using the generalized model of logistic mapping were proposed. Originality. The paper proposes an improved mathematical model, generalized logistic mapping, designed for the study of nonlinear discrete dynamic processes. Practical value. The carried out research using the generalized logistic mapping of railway transport processes, in particular, according to assessment of the parameters of traffic volumes, indicate the great potential of its application in practice for solving problems of analysis, modeling and forecasting complex nonlinear discrete dynamical processes. The proposed model can be used, taking into account the conditions of uncertainty, irregularity, the manifestations of the chaotic nature of the technical, economic and other processes, including the railway ones.

  15. Does Preschool Self-Regulation Predict Later Behavior Problems in General or Specific Problem Behaviors?

    Science.gov (United States)

    Lonigan, Christopher J; Spiegel, Jamie A; Goodrich, J Marc; Morris, Brittany M; Osborne, Colleen M; Lerner, Matthew D; Phillips, Beth M

    2017-11-01

    Findings from prior research have consistently indicated significant associations between self-regulation and externalizing behaviors. Significant associations have also been reported between children's language skills and both externalizing behaviors and self-regulation. Few studies to date, however, have examined these relations longitudinally, simultaneously, or with respect to unique clusters of externalizing problems. The current study examined the influence of preschool self-regulation on general and specific externalizing behavior problems in early elementary school and whether these relations were independent of associations between language, self-regulation, and externalizing behaviors in a sample of 815 children (44% female). Additionally, given a general pattern of sex differences in the presentations of externalizing behavior problems, self-regulation, and language skills, sex differences for these associations were examined. Results indicated unique relations of preschool self-regulation and language with both general externalizing behavior problems and specific problems of inattention. In general, self-regulation was a stronger longitudinal correlate of externalizing behavior for boys than it was for girls, and language was a stronger longitudinal predictor of hyperactive/impulsive behavior for girls than it was for boys.

  16. Predictive Duty Cycle Control of Three-Phase Active-Front-End Rectifiers

    DEFF Research Database (Denmark)

    Song, Zhanfeng; Tian, Yanjun; Chen, Wei

    2016-01-01

    This paper proposed an on-line optimizing duty cycle control approach for three-phase active-front-end rectifiers, aiming to obtain the optimal control actions under different operating conditions. Similar to finite control set model predictive control strategy, a cost function previously...

  17. High Quality Model Predictive Control for Single Phase Grid Connected Photovoltaic Inverters

    DEFF Research Database (Denmark)

    Zangeneh Bighash, Esmaeil; Sadeghzadeh, Seyed Mohammad; Ebrahimzadeh, Esmaeil

    2018-01-01

    Single phase grid-connected inverters with LCL filter are widely used to connect the photovoltaic systems to the utility grid. Among the presented control schemes, predictive control methods are faster and more accurate but are more complex to implement. Recently, the model-predictive control...... is low, the inverter output current has a high total harmonic distortions. In order to reduce the total harmonic distortions of the injected current, this paper presents a high-quality model-predictive control for one of the newest structure of the grid connected photovoltaic inverter, i.e., HERIC...

  18. Automated Clutch of AMT Vehicle Based on Adaptive Generalized Minimum Variance Controller

    Directory of Open Access Journals (Sweden)

    Ze Li

    2014-11-01

    Full Text Available Due to the influence of non-linear dynamic characteristic of clutch, external disturbance and parameter variation, the automated clutch is hard to control precisely during the engaging process of the automated clutch of automatic mechanical transmission vehicle. In this paper, adaptive generalized minimum variance controller is applied to the automated clutch which is driven by a brushless DC motor. The simulation results showed that the proposed controller is effective and robust to the parametric variation and external disturbance.

  19. Optimal Control of Generalized Quasi-Variational Hemivariational Inequalities and Its Applications

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Zhenhai, E-mail: zhhliu@hotmail.com; Zeng, Biao, E-mail: zengbiao316711602@163.com [Guangxi University for Nationalities, Guangxi Key Laboratory of Universities Optimization Control and Engineering Calculation, and College of Sciences (China)

    2015-10-15

    The purpose of this paper is to study optimal control of generalized quasi-variational hemivariational inequalities involving multivalued mapping. Under some suitable conditions, we give existence results of the optimal control. We also consider the convergence behavior of the optimal control when the data for the underlying quasi-variational hemivariational inequalities is contaminated by some noise. In the last section, we give an example to illustrate our main results.

  20. Outpatient Closed-Loop Control with Unannounced Moderate Exercise in Adolescents Using Zone Model Predictive Control.

    Science.gov (United States)

    Huyett, Lauren M; Ly, Trang T; Forlenza, Gregory P; Reuschel-DiVirgilio, Suzette; Messer, Laurel H; Wadwa, R Paul; Gondhalekar, Ravi; Doyle, Francis J; Pinsker, Jordan E; Maahs, David M; Buckingham, Bruce A; Dassau, Eyal

    2017-06-01

    The artificial pancreas (AP) has the potential to improve glycemic control in adolescents. This article presents the first evaluation in adolescents of the Zone Model Predictive Control and Health Monitoring System (ZMPC+HMS) AP algorithms, and their first evaluation in a supervised outpatient setting with frequent exercise. Adolescents with type 1 diabetes underwent 3 days of closed-loop control (CLC) in a hotel setting with the ZMPC+HMS algorithms on the Diabetes Assistant platform. Subjects engaged in twice-daily exercise, including soccer, tennis, and bicycling. Meal size (unrestricted) was estimated and entered into the system by subjects to trigger a bolus, but exercise was not announced. Ten adolescents (11.9-17.7 years) completed 72 h of CLC, with data on 95 ± 14 h of sensor-augmented pump (SAP) therapy before CLC as a comparison to usual therapy. The percentage of time with continuous glucose monitor (CGM) 70-180 mg/dL was 71% ± 10% during CLC, compared to 57% ± 16% during SAP (P = 0.012). Nocturnal control during CLC was safe, with 0% (0%, 0.6%) of time with CGM 250 mg/dL (16% ± 14% during SAP). The system remained connected in CLC for 97% ± 2% of the total study time. No adverse events or severe hypoglycemia occurred. The use of the ZMPC+HMS algorithms is feasible in the adolescent outpatient environment and achieved significantly more time in the desired glycemic range than SAP in the face of unannounced exercise and large announced meal challenges.

  1. A load-following controller for PWRs using fuzzy model predictive method

    Energy Technology Data Exchange (ETDEWEB)

    Man Gyun, Na; In Joon, Hwang [Chosun Univ., Dept. of Nuclear Engineering, Gwangju (Korea, Republic of); Yoon Joon, Lee [Cheju National Univ., Dept. of Nuclear and Energy Engineering (Korea, Republic of)

    2007-07-01

    In this paper, a fuzzy model predictive control (MPC) method is applied to design an automatic controller for power level and axial power distribution controls in pressurized water reactors. The future reactor power and axial shape index (ASI) are predicted by using the fuzzy model identified by a subtractive clustering method of a fast and robust algorithm. The proposed controller is applied to the integrated power level and axial power distribution controls for a Korea Standard Nuclear Power Plant (KSNP). The power level and the ASI are controlled by two kinds of the 5 regulating control rod banks and the 2 part-strength control rod banks together with the automatic adjustment of boric acid concentration. The 3-dimensional reactor analysis code, MASTER, which models the KSNP, is interfaced to the proposed controller to verify the proposed controller for controlling the reactor power level and the ASI. It is known from numerical simulations that the proposed controller exhibits very fast tracking responses. (authors)

  2. Generalized-Disturbance Rejection Control for Vibration Suppression of Piezoelectric Laminated Flexible Structures

    Directory of Open Access Journals (Sweden)

    Xiao-Yu Zhang

    2018-01-01

    Full Text Available In the framework of disturbance rejection (DR control, the paper proposes a generalized-disturbance rejection (GDR control with proportional-integral (PI observer for vibration suppression of smart structures under any unknown continuous disturbances. In the proposed GDR-PI control, a refined state space model is first constructed, and a generalized disturbance including the disturbance influence matrices, unknown physical disturbances, and state variables is defined. In the closed loop of GDR-PI control, physical disturbances can be counteracted indirectly by feeding back estimated generalized disturbances. By this means, the GDR-PI control remedies most of the defects in conventional DR control and has excellent performances especially in the following situations: (i the disturbances are completely unknown; (ii the number of sensor signals is less than the number of disturbances; (iii the unknown disturbances vary fast. Finally, the GDR-PI control is validated and compared with H∞ state feedback control and conventional DR control available in the literature for vibration suppression of smart beams.

  3. Investigation of energy management strategies for photovoltaic systems - A predictive control algorithm

    Science.gov (United States)

    Cull, R. C.; Eltimsahy, A. H.

    1983-01-01

    The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.

  4. Hierarchical Model Predictive Control for Plug-and-Play Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2012-01-01

    This chapter deals with hierarchical model predictive control (MPC) of distributed systems. A three level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonom......This chapter deals with hierarchical model predictive control (MPC) of distributed systems. A three level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level...

  5. Predictive Characteristics of Diabetes-Associated Autoantibodies Among Children With HLA-Conferred Disease Susceptibility in the General Population

    Science.gov (United States)

    Siljander, Heli T.A.; Simell, Satu; Hekkala, Anne; Lähde, Jyrki; Simell, Tuula; Vähäsalo, Paula; Veijola, Riitta; Ilonen, Jorma; Simell, Olli; Knip, Mikael

    2009-01-01

    OBJECTIVE As data on the predictive characteristics of diabetes-associated autoantibodies for type 1 diabetes in the general population are scarce, we assessed the predictive performance of islet cell autoantibodies (ICAs) in combination with autoantibodies against insulin (IAAs), autoantibodies against GAD, and/or islet antigen 2 for type 1 diabetes in children with HLA-defined disease predisposition recruited from the general population. RESEARCH DESIGN AND METHODS We observed 7,410 children from birth (median 9.2 years) for β-cell autoimmunity and diabetes. If a child developed ICA positivity or diabetes, the three other antibodies were measured in all samples available from that individual. Persistent autoantibody positivity was defined as continued positivity in at least two sequential samples including the last available sample. RESULTS Pre-diabetic ICA positivity was observed in 1,173 subjects (15.8%), 155 of whom developed type 1 diabetes. With ICA screening, 86% of 180 progressors (median age at diagnosis 5.0 years) were identified. Positivity for four antibodies was associated with the highest disease sensitivity (54.4%) and negative predictive values (98.3%) and the lowest negative likelihood ratio (0.5). The combination of persistent ICA and IAA positivity resulted in the highest positive predictive value (91.7%), positive likelihood ratio (441.8), cumulative disease risk (100%), and specificity (100%). Young age at seroconversion, high ICA level, multipositivity, and persistent positivity for IAA were significant risk markers for type 1 diabetes. CONCLUSIONS Within the general population, the combination of HLA and autoantibody screening resulted in disease risks that are likely to be as high as those reported among autoantibody-positive siblings of children with type 1 diabetes. PMID:19755526

  6. Do depressive traits and hostility predict age-related decline in general intelligence?

    DEFF Research Database (Denmark)

    Mortensen, Erik Lykke; Barefoot, John Calvin; Avlund, Kirsten

    2012-01-01

    on decline in general intelligence over a 30-year period. The Minnesota Multiphasic Personality Inventory was administered at a 50-year baseline exam, and from this inventory the Obvious Depression Scale and an abbreviated version of the Cook-Medley Hostility Scale were derived. At the 50-year baseline...... and at the 60-, 70-, and 80-year followups the full version of Wechsler's Adult Intelligence Scale (WAIS) was administered to 673, 513, 136, and 184 participants. Mixed effects statistical models were used to evaluate both the effect of the personality scores on level of intelligence and the interaction between...... the personality scores and the time since followup. Analyses were adjusted for demographic background and a wide range of lifestyle factors. Both obvious depression and hostility were negatively associated with level of intelligence, but personality scores did not influence rate of decline in general intelligence....

  7. Natriuretic peptides: prediction of cardiovascular disease in the general population and high risk populations

    DEFF Research Database (Denmark)

    Hildebrandt, Per

    2009-01-01

    The natriuretic peptides, especially the B-type peptide (BNP) and its inactive split-product N-terminal proBNP (Nt-proBNP) are increasingly used in screening for heart failure, primarily with reduced systolic function, in patients with symptoms suggestive of heart failure, as well in the stable...... (General Practitioner) setting as in the acute setting. Supporting this use is a very strong prognostic value of the natriuretic peptides. This has been shown in as well heart failure as acute coronary syndromes, but also in the general population and in high-risk groups as patients with diabetes......, hypertension and coronary artery disease. This has of course raised interest for the use of the natriuretic peptides as a risk marker and for screening for heart failure with reduced systolic function in these populations. In symptomatic persons and in high risk populations, the natriuretic peptides have...

  8. A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

    Science.gov (United States)

    2014-07-01

    times, issues of interruptions and multitasking have become mainstream concerns. For example, Time magazine (Wallis, 2006) and the New York Times...Thompson, 2005) both reported stories about interruptions and multitasking and how they affect performance. The information technology research firm...talking to a friend, it is easy to collect data. Second, providing ordered information to another person is a general class of problems that include

  9. Application of model predictive control strategy based on fuzzy identification to an SP-100 space reactor

    Energy Technology Data Exchange (ETDEWEB)

    Na, Man Gyun [Department of Nuclear Engineering, Chosun University, 375 Seosuk-dong, Dong-gu, Gwangju 501-759 (Korea, Republic of)]. E-mail: magyna@chosun.ac.kr; Upadhyaya, Belle R. [Department of Nuclear Engineering, University of Tennessee, Knoxville, TN 37996-2300 (United States)

    2006-11-15

    In this work, a model predictive control method combined with fuzzy identification, is applied to the design of the thermoelectric (TE) power control in the SP-100 space reactor. The future TE power is predicted by using the fuzzy model identified by a subtractive clustering method of a fast and robust algorithm. The objectives of the proposed fuzzy model predictive controller are to minimize both the difference between the predicted TE power and the desired power, and the variation of control drum angle that adjusts the control reactivity. Also, the objectives are subject to maximum and minimum control drum angle and maximum drum angle variation speed. The genetic algorithm that is effective in accomplishing multiple objectives is used to optimize the fuzzy model predictive controller. A lumped parameter simulation model of the SP-100 nuclear space reactor is used to verify the proposed controller. The results of numerical simulations to check the performance of the proposed controller show that the TE generator power level controlled by the proposed controller could track the target power level effectively, satisfying all control constraints.

  10. Office and 24-h ambulatory blood pressure control by treatment in general practice: the 'Monitoraggio della pressione ARteriosa nella medicina TErritoriale' study.

    Science.gov (United States)

    Zaninelli, Augusto; Parati, Gianfranco; Cricelli, Claudio; Bignamini, Angelo A; Modesti, Pietro A; Pamparana, Franco; Bilo, Grzegorz; Mancia, Giuseppe; Gensini, Gian F

    2010-05-01

    Guidelines recommend that blood pressure (BP) should be lowered in hypertensive patients to prevent cardiovascular accidents. Management of antihypertensive treatment by general practitioners is usually based on office measurements, which may not allow an assessment of BP control over 24 h, which requires ambulatory BP monitoring (ABPM) to be implemented. This is rarely done in general practice, and limited information is available on the consistency between the evaluations of the response to treatment provided by office measurement and by ABPM in this setting. To assess concordance between office BP measurements and ABPM-based estimates of hypertension control in a general practice setting. Prospective, comparative between techniques. General practice. Seventy-eight general practices, representative of all Italian regions, participated in this study by recruiting sequential hypertensive adults on stabilized treatment, who were subdivided into even groups with office BP, respectively, controlled or noncontrolled by treatment. In each individual, ABPM was applied by the general practitioner after appropriate training, and 24-h ABP values were defined as controlled or not according to current guidelines. Concordance between office and ABPM evaluation of BP control was assessed with kappa statistics. Positive and negative predictive values of office measurement versus ABPM were estimated. Between July 2005 and November 2006, 190 general practitioners recruited 2059 hypertensive patients based on office BP measurements; in 1728 patients, a 24-h ABPM was performed, yielding 1524 recordings considered as valid for further analysis. The agreement between the assessment of BP control by office measurement and by ABPM was poor (kappa = 0.120), with office measurements showing a satisfactory positive predictive value (0.842) and a poor negative predictive value (0.278); the situation was worse in patients with three or more among the following features: male sex, age of at

  11. Predictive Event Triggered Control based on Heuristic Dynamic Programming for Nonlinear Continuous Time Systems

    Science.gov (United States)

    2015-08-17

    Control based on Heuristic Dynamic Programming for Nonlinear Continuous-Time Systems In this paper, a novel predictive event-triggered control...method based on heuristic dynamic programming (HDP) algorithm is developed for nonlinear continuous-time systems. A model network is used to estimate...College Road, Suite II Kingston, RI 02881 -1967 ABSTRACT Predictive Event-Triggered Control based on Heuristic Dynamic Programming for Nonlinear

  12. Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking

    Science.gov (United States)

    2015-07-01

    Traditional path- tracking controllers would represent the robot using a bicycle model (Figure 8) with steering angle, δcmd,k, and linear velocity...Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking Chris J. Ostafew Institute for Aerospace Studies...paper presents a Learning-based Nonlinear Model Predictive Control (LB-NMPC) algorithm to achieve high-performance path tracking in challenging off-road

  13. Metabolic syndrome and atypical antipsychotics: Possibility of prediction and control.

    Science.gov (United States)

    Franch Pato, Clara M; Molina Rodríguez, Vicente; Franch Valverde, Juan I

    Schizophrenia and other psychotic disorders are associated with high morbidity and mortality, due to inherent health factors, genetic factors, and factors related to psychopharmacological treatment. Antipsychotics, like other drugs, have side-effects that can substantially affect the physical health of patients, with substantive differences in the side-effect profile and in the patients in which these side-effects occur. To understand and identify these risk groups could help to prevent the occurrence of the undesired effects. A prospective study, with 24 months follow-up, was conducted in order to analyse the physical health of severe mental patients under maintenance treatment with atypical antipsychotics, as well as to determine any predictive parameters at anthropometric and/or analytical level for good/bad outcome of metabolic syndrome in these patients. There were no significant changes in the physical and biochemical parameters individually analysed throughout the different visits. The baseline abdominal circumference (lambda Wilks P=.013) and baseline HDL-cholesterol levels (lambda Wilks P=.000) were the parameters that seem to be more relevant above the rest of the metabolic syndrome constituents diagnosis criteria as predictors in the long-term. In the search for predictive factors of metabolic syndrome, HDL-cholesterol and abdominal circumference at the time of inclusion were selected, as such that the worst the baseline results were, the higher probability of long-term improvement. Copyright © 2016 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

  14. Predicting first-grade mathematics achievement: The contributions of domain-general cognitive abilities, nonverbal number sense, and early number competence.

    Directory of Open Access Journals (Sweden)

    Caroline eHornung

    2014-04-01

    Full Text Available Early number competence, grounded in number-specific and domain-general cognitive abilities, is theorized to lay the foundation for later math achievement. Few longitudinal studies have tested a comprehensive model for early math development. Using structural equation modeling and mediation analyses, the present work examined the influence of kindergarteners’ nonverbal number sense and domain-general abilities i.e., working memory, fluid intelligence, and receptive vocabulary and their early number competence (i.e., symbolic number skills on first grade math achievement (arithmetic, shape and space skills, and number line estimation assessed one year later. Latent regression models revealed that nonverbal number sense and working memory are central building blocks for developing early number competence in kindergarten and that early number competence is key for first grade math achievement. After controlling for early number competence, fluid intelligence significantly predicted arithmetic and number line estimation while receptive vocabulary significantly predicted shape and space skills. In sum we suggest that early math achievement draws on different constellations of number-specific and domain-general mechanisms.

  15. Modeling Smart Energy Systems for Model Predictive Control

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik

    2012-01-01

    Integrating large amounts of renewable energy sources like wind and solar power introduces large uctuations in the power production. Either this energy must be stored or consumed right away. Storage solutions are very expensive and not applicable everywhere. So utilizing all of this green energy...... as it is produced requires a very exible and controllable power consumption. Examples of controllable electric loads are heat pumps in buildings and Electric Vehicles (EVs) that are expected to play a large role in the future danish energy system. These units in a smart energy system can potentially oer exibility...... with green and cheap electricity. This situation occurs when there is a lot of excess wind power in the system which is re ected in the electricity price and in turn creates an incentive to absorb the energy. In this paper a decentralized control strategy is investigated where prices indirectly in uence...

  16. Meditation-induced states predict attentional control over time.

    Science.gov (United States)

    Colzato, Lorenza S; Sellaro, Roberta; Samara, Iliana; Baas, Matthijs; Hommel, Bernhard

    2015-12-01

    Meditation is becoming an increasingly popular topic for scientific research and various effects of extensive meditation practice (ranging from weeks to several years) on cognitive processes have been demonstrated. Here we show that extensive practice may not be necessary to achieve those effects. Healthy adult non-meditators underwent a brief single session of either focused attention meditation (FAM), which is assumed to increase top-down control, or open monitoring meditation (OMM), which is assumed to weaken top-down control, before performing an Attentional Blink (AB) task - which assesses the efficiency of allocating attention over time. The size of the AB was considerably smaller after OMM than after FAM, which suggests that engaging in meditation immediately creates a cognitive-control state that has a specific impact on how people allocate their attention over time. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Development of the predictive maintenance system prototype for the rod control system

    International Nuclear Information System (INIS)

    Lim, H. S.; Hong, H. P.; Koo, J. M.; Kim, Y. B.; Han, H. W.

    2003-01-01

    The demand for safety and reliability of Nuclear Power Plants (NPPs) has been constantly increasing and economical operation is also an important issue. Developing and adopting predictive maintenance technology for the major systems or equipment is considered as a way to achieve these goals. This paper describes the development of a predictive maintenance system prototype for the Rod Control System, which adopts an advanced methodology. Bayesian Belief Networks (BBN) has been adopted for the real time fault diagnosis and prediction of the system. Through a simulation test, it was confirmed that the prototype monitors and secures sound operability of rod drive mechanism and its control system, and also provides the predictive maintenance information

  18. Predictability problems of global change as seen through natural systems complexity description. 1. General Statements

    Directory of Open Access Journals (Sweden)

    Vladimir V. Kozoderov

    1998-01-01

    Full Text Available The overall problem of global change is considered as the mathematical discrete dynamics discipline that deals with the sets, measures and metrics (SMM categories in information sub-spaces. The SMM conception enables to unify techniques of data interpretation and analysis and to explain how effectively the giant amounts of information from multispectral satellite radiometers and ground-based instruments are to be processed. It is shown that Prigogine's chaos/order theory and Kolmogorov's probability space are two milestones in understanding the predictability problems of global change. The essence of the problems is maintained to be in filtering out a “useful signal” that would spread from key regions of the globe as compared to their background. Global analysis, interpretation and modelling issues are outlined in the framework of incorrect mathematical problems and of the SMM categories, which contribute to solving the comparability problem for different sets of observations.

  19. Motion Planning and Posture Control of the General 3-Trailer System

    OpenAIRE

    K. Raghuwaiya; B. Sharma; J. Vanualailai

    2014-01-01

    This paper presents a set of artificial potential field functions that improves upon, in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dyn...

  20. New technologies in predicting, preventing and controlling emerging infectious diseases.

    Science.gov (United States)

    Christaki, Eirini

    2015-01-01

    Surveillance of emerging infectious diseases is vital for the early identification of public health threats. Emergence of novel infections is linked to human factors such as population density, travel and trade and ecological factors like climate change and agricultural practices. A wealth of new technologies is becoming increasingly available for the rapid molecular identification of pathogens but also for the more accurate monitoring of infectious disease activity. Web-based surveillance tools and epidemic intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely outbreak detection. In this review, we present new methods for regional and global infectious disease surveillance and advances in epidemic modeling aimed to predict and prevent future infectious diseases threats.