WorldWideScience

Sample records for non-predictive control model

  1. Nominal model predictive control

    OpenAIRE

    Grüne, Lars

    2013-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  2. Nominal Model Predictive Control

    OpenAIRE

    Grüne, Lars

    2014-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  3. Stochastic Control - External Models

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad

    2005-01-01

    This note is devoted to control of stochastic systems described in discrete time. We are concerned with external descriptions or transfer function model, where we have a dynamic model for the input output relation only (i.e.. no direct internal information). The methods are based on LTI systems...

  4. Aeroservoelasticity modeling and control

    CERN Document Server

    Tewari, Ashish

    2015-01-01

    This monograph presents the state of the art in aeroservoelastic (ASE) modeling and analysis and develops a systematic theoretical and computational framework for use by researchers and practicing engineers. It is the first book to focus on the mathematical modeling of structural dynamics, unsteady aerodynamics, and control systems to evolve a generic procedure to be applied for ASE synthesis. Existing robust, nonlinear, and adaptive control methodology is applied and extended to some interesting ASE problems, such as transonic flutter and buffet, post-stall buffet and maneuvers, and flapping flexible wing. The author derives a general aeroservoelastic plant via the finite-element structural dynamic model, unsteady aerodynamic models for various regimes in the frequency domain, and the associated state-space model by rational function approximations. For more advanced models, the full-potential, Euler, and Navier-Stokes methods for treating transonic and separated flows are also briefly addressed. Essential A...

  5. Evaluation of air pollution control policies in Mexico City using finite Markov chain observation model

    OpenAIRE

    Luis Hoyos; Pedro Lara; Elba Ortiz; Rafael López; Jesús González

    2009-01-01

    This paper proposes a Markov observation based model, where the transition matrix is formulated using air quality monitoring data for specific pollutant emissions, with the primary objective to analyze the corresponding stationary distributions and evaluate sceneries for the air quality impact of pollution control policies. The model is non predictive and could be applied to every source of pollutant emissions included in air monitoring data. Two cases of study are presented, ozone and sulfur...

  6. Model-free control

    Science.gov (United States)

    Fliess, Michel; Join, Cédric

    2013-12-01

    'Model-free control'and the corresponding 'intelligent' PID controllers (iPIDs), which already had many successful concrete applications, are presented here for the first time in an unified manner, where the new advances are taken into account. The basics of model-free control is now employing some old functional analysis and some elementary differential algebra. The estimation techniques become quite straightforward via a recent online parameter identification approach. The importance of iPIs and especially of iPs is deduced from the presence of friction. The strange industrial ubiquity of classic PIDs and the great difficulty for tuning them in complex situations is deduced, via an elementary sampling, from their connections with iPIDs. Several numerical simulations are presented which include some infinite-dimensional systems. They demonstrate not only the power of our intelligent controllers but also the great simplicity for tuning them.

  7. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... paper, we will present an introduction to the theory and application of MPC with Matlab codes written to ... model predictive control, linear systems, discrete-time systems, ... and then compute very rapidly for this open-loop con-.

  8. Modelling, controlling, predicting blackouts

    CERN Document Server

    Wang, Chengwei; Baptista, Murilo S

    2016-01-01

    The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids, and another one for smart grids. The control strategie...

  9. SMC: SCENIC Model Control

    Science.gov (United States)

    Srivastava, Priyaka; Kraus, Jeff; Murawski, Robert; Golden, Bertsel, Jr.

    2015-01-01

    NASAs Space Communications and Navigation (SCaN) program manages three active networks: the Near Earth Network, the Space Network, and the Deep Space Network. These networks simultaneously support NASA missions and provide communications services to customers worldwide. To efficiently manage these resources and their capabilities, a team of student interns at the NASA Glenn Research Center is developing a distributed system to model the SCaN networks. Once complete, the system shall provide a platform that enables users to perform capacity modeling of current and prospective missions with finer-grained control of information between several simulation and modeling tools. This will enable the SCaN program to access a holistic view of its networks and simulate the effects of modifications in order to provide NASA with decisional information. The development of this capacity modeling system is managed by NASAs Strategic Center for Education, Networking, Integration, and Communication (SCENIC). Three primary third-party software tools offer their unique abilities in different stages of the simulation process. MagicDraw provides UMLSysML modeling, AGIs Systems Tool Kit simulates the physical transmission parameters and de-conflicts scheduled communication, and Riverbed Modeler (formerly OPNET) simulates communication protocols and packet-based networking. SCENIC developers are building custom software extensions to integrate these components in an end-to-end space communications modeling platform. A central control module acts as the hub for report-based messaging between client wrappers. Backend databases provide information related to mission parameters and ground station configurations, while the end user defines scenario-specific attributes for the model. The eight SCENIC interns are working under the direction of their mentors to complete an initial version of this capacity modeling system during the summer of 2015. The intern team is composed of four students in

  10. Modeling and control of thermostatically controlled loads

    OpenAIRE

    2011-01-01

    As the penetration of intermittent energy sources grows substantially, loads will be required to play an increasingly important role in compensating the fast time-scale fluctuations in generated power. Recent numerical modeling of thermostatically controlled loads (TCLs) has demonstrated that such load following is feasible, but analytical models that satisfactorily quantify the aggregate power consumption of a group of TCLs are desired to enable controller design. We develop such a model for...

  11. Active control: Wind turbine model

    Energy Technology Data Exchange (ETDEWEB)

    Bindner, Henrik

    1999-07-01

    This report is a part of the reporting of the work done in the project `Active Control of Wind Turbines`. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to design controllers. This report describes the model developed for controller design and analysis. Emphasis has been put on establishment of simple models describing the dynamic behavior of the wind turbine in adequate details for controller design. This has been done with extensive use of measurements as the basis for selection of model complexity and model validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending, a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models. The models are all formulated as linear differential equations. The models are validated through comparisons with measurements performed on a Vestas WD 34 400 kW wind turbine. It is shown from a control point of view simple linear models can be used to describe the dynamic behavior of a pitch controlled wind turbine. The model and the measurements corresponds well in the relevant frequency range. The developed model is therefore applicable for controller design. (au) EFP-91. 18 ills., 22 refs.

  12. Active control: Wind turbine model

    DEFF Research Database (Denmark)

    Bindner, H.

    1999-01-01

    This report is a part of the reporting of the work done in the project 'Active Control of Wind Turbines'. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to designcontrollers. This report describes the model...... developed for controller design and analysis. Emphasis has been put on establishment of simple models describing the dynamic behavior of the wind turbine in adequate details for controller design. This hasbeen done with extensive use of measurements as the basis for selection of model complexity and model...... validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending,a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models...

  13. Modeling and control of thermostatically controlled loads

    Energy Technology Data Exchange (ETDEWEB)

    Backhaus, Scott N [Los Alamos National Laboratory; Sinitsyn, Nikolai [Los Alamos National Laboratory; Kundu, S. [UNIV OF MICHIGAN; Hiskens, I. [UNIV OF MICHIGAN

    2011-01-04

    As the penetration of intermittent energy sources grows substantially, loads will be required to play an increasingly important role in compensating the fast time-scale fluctuations in generated power. Recent numerical modeling of thermostatically controlled loads (TCLs) has demonstrated that such load following is feasible, but analytical models that satisfactorily quantify the aggregate power consumption of a group of TCLs are desired to enable controller design. We develop such a model for the aggregate power response of a homogeneous population of TCLs to uniform variation of all TCL setpoints. A linearized model of the response is derived, and a linear quadratic regulator (LQR) has been designed. Using the TCL setpoint as the control input, the LQR enables aggregate power to track reference signals that exhibit step, ramp and sinusoidal variations. Although much of the work assumes a homogeneous population of TCLs with deterministic dynamics, we also propose a method for probing the dynamics of systems where load characteristics are not well known.

  14. Controlling Modelling Artifacts

    DEFF Research Database (Denmark)

    Smith, Michael James Andrew; Nielson, Flemming; Nielson, Hanne Riis

    2011-01-01

    the possible configurations of the system (for example, by counting the number of components in a certain state). We motivate our methodology with a case study of the LMAC protocol for wireless sensor networks. In particular, we investigate the accuracy of a recently proposed high-level model of LMAC......When analysing the performance of a complex system, we typically build abstract models that are small enough to analyse, but still capture the relevant details of the system. But it is difficult to know whether the model accurately describes the real system, or if its behaviour is due to modelling...... artifacts that were inadvertently introduced. In this paper, we propose a novel methodology to reason about modelling artifacts, given a detailed model and a highlevel (more abstract) model of the same system. By a series of automated abstraction steps, we lift the detailed model to the same state space...

  15. Modelling and controlling hydropower plants

    CERN Document Server

    Munoz-Hernandez, German Ardul; Jones, Dewi Ieuan

    2013-01-01

    Hydroelectric power stations are a major source of electricity around the world; understanding their dynamics is crucial to achieving good performance.  Modelling and Controlling Hydropower Plants discusses practical and well-documented cases of modelling and controlling hydropower station modelling and control, focussing on a pumped storage scheme based in Dinorwig, North Wales.  Single-input-single-output and multiple-input-multiple-output models, which cover the linear and nonlinear characteristics of pump-storage hydroelectric power stations, are reviewed. The most important dynamic features are discussed, and the verification of these models by hardware in the loop simulation is described. To show how the performance of a pump-storage hydroelectric power station can be improved, classical and modern controllers are applied to simulated models of the Dinorwig power plant. These include PID, fuzzy approximation, feed-forward and model-based predictive control with linear and hybrid prediction models. Mod...

  16. Controlling Modelling Artifacts

    DEFF Research Database (Denmark)

    Smith, Michael James Andrew; Nielson, Flemming; Nielson, Hanne Riis

    2011-01-01

    as the high-level model, so that they can be directly compared. There are two key ideas in our approach — a temporal abstraction, where we only look at the state of the system at certain observable points in time, and a spatial abstraction, where we project onto a smaller state space that summarises...... artifacts that were inadvertently introduced. In this paper, we propose a novel methodology to reason about modelling artifacts, given a detailed model and a highlevel (more abstract) model of the same system. By a series of automated abstraction steps, we lift the detailed model to the same state space...

  17. Engine Modelling for Control Applications

    DEFF Research Database (Denmark)

    Hendricks, Elbert

    1997-01-01

    In earlier work published by the author and co-authors, a dynamic engine model called a Mean Value Engine Model (MVEM) was developed. This model is physically based and is intended mainly for control applications. In its newer form, it is easy to fit to many different engines and requires little...... engine data for this purpose. It is especially well suited to embedded model applications in engine controllers, such as nonlinear observer based air/fuel ratio and advanced idle speed control. After a brief review of this model, it will be compared with other similar models which can be found...

  18. Modelling and Control of TCV

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, A.S.; Limebeer, D.J.N.; Jaimoukha, I.M.; Lister, J.B

    2001-11-01

    A new approach to the modelling and control of tokamak fusion reactors is presented. A nonlinear model is derived using the classical arguments of Hamiltonian mechanics and a low-order linear model is derived from it. The modelling process used here addresses flux and energy conservation issues explicitly and self-consistently. The model is of particular value, because it shows the relationship between the initial modelling assumptions and the resulting predictions. The mechanisms behind the creation of uncontrollable modes in tokamak models are discussed. A normalised coprime factorisation controller is developed for the TCV tokamak using the verified linear model. Recent theory is applied to reduce the controller order significantly whilst guaranteeing a priori bounds on the robust stability and performance. The controller is shown to track successfully reference signals that dictate the plasma's shape, position and current. The tests used to verify this were carried out on linear and nonlinear models. (author)

  19. Modeling and Control for Microgrids

    Science.gov (United States)

    Steenis, Joel

    Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating range. In this document a linear model is derived for an inverter connected to the Thevenin equivalent of a microgrid. This model is then compared to a nonlinear simulation model and analyzed using the open and closed loop systems in both the time and frequency domains. The modeling error is quantified with emphasis on its use for controller design purposes. Control design examples are given using a Glover McFarlane controller, gain scheduled Glover McFarlane controller, and bumpless transfer controller which are compared to the standard droop control approach. These examples serve as a guide to illustrate the use of multi-variable modeling techniques in the context of robust controller design and show that gain scheduled MIMO control techniques can extend the operating range of a microgrid. A hardware implementation is used to compare constant gain droop controllers with Glover McFarlane controllers and shows a clear advantage of the Glover McFarlane approach.

  20. Combustion Process Modelling and Control

    Directory of Open Access Journals (Sweden)

    Vladimír Maduda

    2007-10-01

    Full Text Available This paper deals with realization of combustion control system on programmable logic controllers. Control system design is based on analysis of the current state of combustion control systems in technological device of raw material processing area. Control system design is composed of two subsystems. First subsystem is represented by software system for measured data processing and for data processing from simulation of the combustion mathematical model. Outputs are parameters for setting of controller algorithms. Second subsystem consists from programme modules. The programme module is presented by specific control algorithm, for example proportional regulation, programmed proportional regulation, proportional regulation with correction on the oxygen in waste gas, and so on. According to the specific combustion control requirements it is possible built-up concrete control system by programme modules. The programme modules were programmed by Automation studio that is used for development, debugging and testing software for B&R controllers.

  1. Wind Farms: Modeling and Control

    DEFF Research Database (Denmark)

    Soleimanzadeh, Maryam

    2012-01-01

    provides the state space form of the dynamic wind farm model. The model provides an approximation of the behavior of the flow in wind farms, and obtains the wind speed in the vicinity of each wind turbine. The control algorithms in this work are mostly on the basis of the developed wind farm model......The primary purpose of this work is to develop control algorithms for wind farms to optimize the power production and augment the lifetime of wind turbines in wind farms. In this regard, a dynamical model for wind farms was required to be the basis of the controller design. In the first stage......, a dynamical model has been developed for the wind flow in wind farms. The model is based on the spatial discretization of the linearized Navier-Stokes equation combined with the vortex cylinder theory. The spatial discretization of the model is performed using the Finite Difference Method (FDM), which...

  2. Multiple Model Approaches to Modelling and Control,

    DEFF Research Database (Denmark)

    Why Multiple Models?This book presents a variety of approaches which produce complex models or controllers by piecing together a number of simpler subsystems. Thisdivide-and-conquer strategy is a long-standing and general way of copingwith complexity in engineering systems, nature and human probl...

  3. Multiple Model Approaches to Modelling and Control,

    DEFF Research Database (Denmark)

    on the ease with which prior knowledge can be incorporated. It is interesting to note that researchers in Control Theory, Neural Networks,Statistics, Artificial Intelligence and Fuzzy Logic have more or less independently developed very similar modelling methods, calling them Local ModelNetworks, Operating...... of introduction of existing knowledge, as well as the ease of model interpretation. This book attempts to outlinemuch of the common ground between the various approaches, encouraging the transfer of ideas.Recent progress in algorithms and analysis is presented, with constructive algorithms for automated model...

  4. Nonlinear Control of Heartbeat Models

    Directory of Open Access Journals (Sweden)

    Witt Thanom

    2011-02-01

    Full Text Available This paper presents a novel application of nonlinear control theory to heartbeat models. Existing heartbeat models are investigated and modified by incorporating the control input as a pacemaker to provide the control channel. A nonlinear feedback linearization technique is applied to force the output of the systems to generate artificial electrocardiogram (ECG signal using discrete data as the reference inputs. The synthetic ECG may serve as a flexible signal source to assess the effectiveness of a diagnostic ECG signal-processing device.

  5. Global nuclear material control model

    Energy Technology Data Exchange (ETDEWEB)

    Dreicer, J.S.; Rutherford, D.A.

    1996-05-01

    The nuclear danger can be reduced by a system for global management, protection, control, and accounting as part of a disposition program for special nuclear materials. The development of an international fissile material management and control regime requires conceptual research supported by an analytical and modeling tool that treats the nuclear fuel cycle as a complete system. Such a tool must represent the fundamental data, information, and capabilities of the fuel cycle including an assessment of the global distribution of military and civilian fissile material inventories, a representation of the proliferation pertinent physical processes, and a framework supportive of national or international perspective. They have developed a prototype global nuclear material management and control systems analysis capability, the Global Nuclear Material Control (GNMC) model. The GNMC model establishes the framework for evaluating the global production, disposition, and safeguards and security requirements for fissile nuclear material.

  6. Modelling on fuzzy control systems

    Institute of Scientific and Technical Information of China (English)

    LI; Hongxing(李洪兴); WANG; Jiayin(王加银); MIAO; Zhihong(苗志宏)

    2002-01-01

    A kind of modelling method for fuzzy control systems is first proposed here, which is calledmodelling method based on fuzzy inference (MMFI). It should be regarded as the third modelling method thatis different from two well-known modelling methods, that is, the first modelling method, mechanism modellingmethod (MMM), and the second modelling method, system identification modelling method (SlMM). Thismethod can, based on the interpolation mechanism on fuzzy logic system, transfer a group of fuzzy inferencerules describing a practice system into a kind of nonlinear differential equation with variable coefficients, calledHX equations, so that the mathematical model of the system can be obtained. This means that we solve thedifficult problem of how to get a model represented as differential equations on a complicated or fuzzy controlsystem.

  7. Hot Strip Laminar Cooling Control Model

    Institute of Scientific and Technical Information of China (English)

    WANG Jun; WANG Guo-dong; LIU Xiang-hua

    2004-01-01

    The control model of laminar cooling system for hot strip, including air-cooling model, water-cooling model, temperature distribution model along thickness direction, feedforward control model, feedback control model and self-learning model, was introduced. PID arithmetic and Smith predictor controller were applied to feedback control. The sample of model parameter classification was given. The calculation process was shown by flow chart. The model has been proved to be simple, effective and of high precision.

  8. The Control System Modeling Language

    CERN Document Server

    Zagar, K; Sekoranja, M; Tkacik, G; Vodovnik, A; Zagar, Klemen; Plesko, Mark; Sekoranja, Matej; Tkacik, Gasper; Vodovnik, Anze

    2001-01-01

    The well-known Unified Modeling Language (UML) describes software entities, such as interfaces, classes, operations and attributes, as well as relationships among them, e.g. inheritance, containment and dependency. The power of UML lies in Computer Aided Software Engineering (CASE) tools such as Rational Rose, which are also capable of generating software structures from visual object definitions and relations. UML also allows add-ons that define specific structures and patterns in order to steer and automate the design process. We have developed an add-on called Control System Modeling Language (CSML). It introduces entities and relationships that we know from control systems, such as "property" representing a single controllable point/channel, or an "event" specifying that a device is capable of notifying its clients through events. Entities can also possess CSML-specific characteristics, such as physical units and valid ranges for input parameters. CSML is independent of any specific language or technology...

  9. Modeling and Controlling Interstate Conflict

    CERN Document Server

    Marwala, Tshilidzi

    2007-01-01

    Bayesian neural networks were used to model the relationship between input parameters, Democracy, Allies, Contingency, Distance, Capability, Dependency and Major Power, and the output parameter which is either peace or conflict. The automatic relevance determination was used to rank the importance of input variables. Control theory approach was used to identify input variables that would give a peaceful outcome. It was found that using all four controllable variables Democracy, Allies, Capability and Dependency; or using only Dependency or only Capabilities avoids all the predicted conflicts.

  10. The integrated environmental control model

    Energy Technology Data Exchange (ETDEWEB)

    Rubin, E.S.; Berkenpas, M.B.; Kalagnanam, J.R. [Carnegie Mellon Univ., Pittsburgh, PA (United States)

    1995-11-01

    The capability to estimate the performance and cost of emission control systems is critical to a variety of planning and analysis requirements faced by utilities, regulators, researchers and analysts in the public and private sectors. The computer model described in this paper has been developed for DOe to provide an up-to-date capability for analyzing a variety of pre-combustion, combustion, and post-combustion options in an integrated framework. A unique capability allows performance and costs to be modeled probabilistically, which allows explicit characterization of uncertainties and risks.

  11. Planning the unknown: the simultaneity of predictive and non-predictive entrepreneurial strategies

    NARCIS (Netherlands)

    Kraaijenbrink, Jeroen; Ratinho, Tiago; Groen, Arend J.

    2012-01-01

    Two distinct approaches have emerged to categorize entrepreneurial strategies. While some argue that planning is beneficial for entrepreneurs, a growing body of literature argues that non-predictive strategies can also lead to successful outcomes. The effectuation framework gained attention and it i

  12. Correlations and Non-predictability in the Time Evolution of Earthquake Ruptures

    Science.gov (United States)

    Elkhoury, J. E.; Knopoff, L.

    2007-12-01

    The characterization of the time evolution of ruptures is one of the important aspects of the earthquake process. What makes a rupture, that starts small, to become a big one or end very quickly resulting in a small earthquake is central to understanding the physics of the time evolution of ruptures. Establishing whether there are any correlations in time, between the initiation of the rupture and its ultimate size, is a step in the right direction. Here, we analyze three source-time function data sets. The first is produced by the generation of repeated rupture events on a 2D heterogeneous, in-plane, dynamical model, while the second is produced by an-age dependent critical branching model. The third is the source-time function data base of Ruff [1]. We formulate the problem in terms of two questions. 1) Are there any correlations between the moment release at the beginning of the rupture and the total moment release during the entire rupture? 2) Can we predict the final size of an earthquake, once it has started and without any a posteriori information, by just knowing the moment release up to a certain time τ? Using the three data bases, the answer to the first question is yes and no to the second. The longer τ is, the stronger the correlations are between what goes on at the initiation and the final size. But, for τ fixed, and not a major fraction of the rupture time, there is no predictability of the rupture size. In particular, if a rupture starts with a very large moment release during time τ, it becomes a large earthquake. On the other hand, large earthquakes might start with very small moment release during τ; the non-predictability is due to the heterogeneities. The randomness in the critical branching model mimics the effect of the heterogeneities in the crust and in the 2D model. \\begin{thebibliography}{99} \\bibitem{ruff} Ruff, L. J., http://www.geo.lsa.umich.edu/SeismoObs/STF.html

  13. Path modeling and process control

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar; Rodionova, O.; Pomerantsev, A.

    2007-01-01

    and having three or more stages. The methods are applied to a process control of a multi-stage production process having 25 variables and one output variable. When moving along the process, variables change their roles. It is shown how the methods of path modeling can be applied to estimate variables...... of the next stage with the purpose of obtaining optimal or almost optimal quality of the output variable. An important aspect of the methods presented is the possibility of extensive graphic analysis of data that can provide the engineer with a detailed view of the multi-variate variation in data.......Many production processes are carried out in stages. At the end of each stage, the production engineer can analyze the intermediate results and correct process parameters (variables) of the next stage. Both analysis of the process and correction to process parameters at next stage should...

  14. A MODEL AND CONTROLLER REDUCTION METHOD FOR ROBUST CONTROL DESIGN.

    Energy Technology Data Exchange (ETDEWEB)

    YUE,M.; SCHLUETER,R.

    2003-10-20

    A bifurcation subsystem based model and controller reduction approach is presented. Using this approach a robust {micro}-synthesis SVC control is designed for interarea oscillation and voltage control based on a small reduced order bifurcation subsystem model of the full system. The control synthesis problem is posed by structured uncertainty modeling and control configuration formulation using the bifurcation subsystem knowledge of the nature of the interarea oscillation caused by a specific uncertainty parameter. Bifurcation subsystem method plays a key role in this paper because it provides (1) a bifurcation parameter for uncertainty modeling; (2) a criterion to reduce the order of the resulting MSVC control; and (3) a low order model for a bifurcation subsystem based SVC (BMSVC) design. The use of the model of the bifurcation subsystem to produce a low order controller simplifies the control design and reduces the computation efforts so significantly that the robust {micro}-synthesis control can be applied to large system where the computation makes robust control design impractical. The RGA analysis and time simulation show that the reduced BMSVC control design captures the center manifold dynamics and uncertainty structure of the full system model and is capable of stabilizing the full system and achieving satisfactory control performance.

  15. Multiplicity Control in Structural Equation Modeling

    Science.gov (United States)

    Cribbie, Robert A.

    2007-01-01

    Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

  16. A pinned polymer model of posture control

    CERN Document Server

    Chow, C C; Chow, Carson C; Collins, J J

    1995-01-01

    A phenomenological model of human posture control is posited. The dynamics are modelled as an elastically pinned polymer under the influence of noise. The model accurately reproduces the two-point correlation functions of experimental posture data and makes predictions for the response function of the postural control system. The physiological and clinical significance of the model is discussed.

  17. CONTROL SYSTEM IDENTIFICATION THROUGH MODEL MODULATION METHODS

    Science.gov (United States)

    identification has been achieved by using model modulation techniques to drive dynamic models into correspondence with operating control systems. The system ... identification then proceeded from examination of the model and the adaptive loop. The model modulation techniques applied to adaptive control

  18. Modeling and robust control of wind turbine

    Science.gov (United States)

    Gilev, Bogdan

    2016-12-01

    In this paper a model of a wind turbine is evaluated, consisting of: wind speed model, mechanical and electrical model of generator and tower oscillation model. This model is linearized around of a nominal point. By using the linear model with uncertainties is synthesized a uncertain model. By using the uncertain model and robust control theory is developed a robust controller, which provide mode of stabilizing the rotor frequency and damping the tower oscillations. Finally is simulated work of nonlinear system and robust controller

  19. 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 temperat......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...

  20. Stochastic models, estimation, and control

    CERN Document Server

    Maybeck, Peter S

    1982-01-01

    This volume builds upon the foundations set in Volumes 1 and 2. Chapter 13 introduces the basic concepts of stochastic control and dynamic programming as the fundamental means of synthesizing optimal stochastic control laws.

  1. Modelling and Control of a Mobile Robot

    DEFF Research Database (Denmark)

    Christensen, Georg Kronborg

    1998-01-01

    In order to control a mobile robot, kinematic odels as well as dynamic models are required. This parer describes these basic models for an experimental mobile robot under construction at the Department of Control and Engineering Design. A description of a set of trajectory control rules is given...

  2. Basic Research on Adaptive Model Algorithmic Control

    Science.gov (United States)

    1985-12-01

    Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes

  3. Modeling and position control of tethered octocopters

    Directory of Open Access Journals (Sweden)

    de Castro Davi Ferreira

    2016-01-01

    Full Text Available This work presents the modeling and control of a multirotor aerial vehicle with tethered configuration. It is considered an octocopter with a saturated proportional-plus-derivative position control. A viscoelastic model is considered for the tether, which has a tension control. Numerical simulations are carried out to compare the performance of the tethred configuration with the vehicle in free flight.

  4. Managing Delegation in Access Control Models

    CERN Document Server

    Ghorbel-Talbi, Meriam Ben; Cuppens-Boulahia, Nora; Bouhoula, Adel; 10.1109/ADCOM.2007.105

    2010-01-01

    In the field of access control, delegation is an important aspect that is considered as a part of the administration mechanism. Thus, a complete access control must provide a flexible administration model to manage delegation. Unfortunately, to our best knowledge, there is no complete model for describing all delegation requirements for role-based access control. Therefore, proposed models are often extended to consider new delegation characteristics, which is a complex task to manage and necessitate the redefinition of these models. In this paper we describe a new delegation approach for extended role-based access control models. We show that our approach is flexible and is sufficient to manage all delegation requirements.

  5. Modelling onchocerciasis transmission and control

    NARCIS (Netherlands)

    A.P. Plaisier (Anton)

    1996-01-01

    textabstractIn 1990 the World Health Organization (WHO) coordinated Onchocerciasis Control Programme in West Africa (OCP) used this slogan for evaluating fifteen years of control of the parasitic disease onchocerciasis and for expressing its optimism about the future. Based on the obvious success of

  6. Modeling Control Situations in Power System Operations

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten; Singh, Sri Niwas

    2010-01-01

    Increased interconnection and loading of the power system along with deregulation has brought new challenges for electric power system operation, control and automation. Traditional power system models used in intelligent operation and control are highly dependent on the task purpose. Thus, a model...... for intelligent operation and control must represent system features, so that information from measurements can be related to possible system states and to control actions. These general modeling requirements are well understood, but it is, in general, difficult to translate them into a model because of the lack...... of explicit principles for model construction. This paper presents a work on using explicit means-ends model based reasoning about complex control situations which results in maintaining consistent perspectives and selecting appropriate control action for goal driven agents. An example of power system...

  7. Modeling Control Situations in Power System Operations

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten; Singh, Sri Niwas

    2010-01-01

    Increased interconnection and loading of the power system along with deregulation has brought new challenges for electric power system operation, control and automation. Traditional power system models used in intelligent operation and control are highly dependent on the task purpose. Thus, a model...... for intelligent operation and control must represent system features, so that information from measurements can be related to possible system states and to control actions. These general modeling requirements are well understood, but it is, in general, difficult to translate them into a model because of the lack...... of explicit principles for model construction. This paper presents a work on using explicit means-ends model based reasoning about complex control situations which results in maintaining consistent perspectives and selecting appropriate control action for goal driven agents. An example of power system...

  8. Modeling and control of greenhouse crop growth

    CERN Document Server

    Rodríguez, Francisco; Guzmán, José Luis; Ramírez-Arias, Armando

    2015-01-01

    A discussion of challenges related to the modeling and control of greenhouse crop growth, this book presents state-of-the-art answers to those challenges. The authors model the subsystems involved in successful greenhouse control using different techniques and show how the models obtained can be exploited for simulation or control design; they suggest ideas for the development of physical and/or black-box models for this purpose. Strategies for the control of climate- and irrigation-related variables are brought forward. The uses of PID control and feedforward compensators, both widely used in commercial tools, are summarized. The benefits of advanced control techniques—event-based, robust, and predictive control, for example—are used to improve on the performance of those basic methods. A hierarchical control architecture is developed governed by a high-level multiobjective optimization approach rather than traditional constrained optimization and artificial intelligence techniques.  Reference trajector...

  9. Optimal Control Design with Limited Model Information

    CERN Document Server

    Farokhi, F; Johansson, K H

    2011-01-01

    We introduce the family of limited model information control design methods, which construct controllers by accessing the plant's model in a constrained way, according to a given design graph. We investigate the achievable closed-loop performance of discrete-time linear time-invariant plants under a separable quadratic cost performance measure with structured static state-feedback controllers. We find the optimal control design strategy (in terms of the competitive ratio and domination metrics) when the control designer has access to the local model information and the global interconnection structure of the plant-to-be-controlled. At last, we study the trade-off between the amount of model information exploited by a control design method and the best closed-loop performance (in terms of the competitive ratio) of controllers it can produce.

  10. Nonlinear control of the Salnikov model reaction

    DEFF Research Database (Denmark)

    Recke, Bodil; Jørgensen, Sten Bay

    1999-01-01

    This paper explores different nonlinear control schemes, applied to a simple model reaction. The model is the Salnikov model, consisting of two ordinary differential equations. The control strategies investigated are I/O-linearisation, Exact linearisation, exact linearisation combined with LQR...... and Control Lyapunov Functions (CLF's). The results show that based on the lowest possible cost function and shortest settling time, the exact linearisation performs marginally better than the other methods....

  11. Fractional Order Models of Industrial Pneumatic Controllers

    Directory of Open Access Journals (Sweden)

    Abolhassan Razminia

    2014-01-01

    Full Text Available This paper addresses a new approach for modeling of versatile controllers in industrial automation and process control systems such as pneumatic controllers. Some fractional order dynamical models are developed for pressure and pneumatic systems with bellows-nozzle-flapper configuration. In the light of fractional calculus, a fractional order derivative-derivative (FrDD controller and integral-derivative (FrID are remodeled. Numerical simulations illustrate the application of the obtained theoretical results in simple examples.

  12. Application of Model Predictive Control to BESS for Microgrid Control

    Directory of Open Access Journals (Sweden)

    Thai-Thanh Nguyen

    2015-08-01

    Full Text Available Battery energy storage systems (BESSs have been widely used for microgrid control. Generally, BESS control systems are based on proportional-integral (PI control techniques with the outer and inner control loops based on PI regulators. Recently, model predictive control (MPC has attracted attention for application to future energy processing and control systems because it can easily deal with multivariable cases, system constraints, and nonlinearities. This study considers the application of MPC-based BESSs to microgrid control. Two types of MPC are presented in this study: MPC based on predictive power control (PPC and MPC based on PI control in the outer and predictive current control (PCC in the inner control loops. In particular, the effective application of MPC for microgrids with multiple BESSs should be considered because of the differences in their control performance. In this study, microgrids with two BESSs based on two MPC techniques are considered as an example. The control performance of the MPC used for the control microgrid is compared to that of the PI control. The proposed control strategy is investigated through simulations using MATLAB/Simulink software. The simulation results show that the response time, power and voltage ripples, and frequency spectrum could be improved significantly by using MPC.

  13. Modelling command and control teams

    NARCIS (Netherlands)

    Broek, J. van den; Essens, P.J.M.D.; Post, W.M.

    2001-01-01

    This paper describes a computational approach to modelling and simulating C2-team behaviour. Within this approach team models may be used to develop, test, and compare different C2-architectures, that is different structures and processes, without the need for real teams. The advantage of this metho

  14. Modeling and biological control of mosquitoes.

    Science.gov (United States)

    Lord, Cynthia C

    2007-01-01

    Models can be useful at many different levels when considering complex issues such as biological control of mosquitoes. At an early stage, exploratory models are valuable in exploring the characteristics of an ideal biological control agent and for guidance in data collection. When more data are available, models can be used to explore alternative control strategies and the likelihood of success. There are few modeling studies that explicitly consider biological control in mosquitoes; however, there have been many theoretical studies of biological control in other insect systems and of mosquitoes and mosquito-borne diseases in general. Examples are used here to illustrate important aspects of designing, using and interpreting models. The stability properties of a model are valuable in assessing the potential of a biological control agent, but may not be relevant to a mosquito population with frequent environmental perturbations. The time scale and goal of proposed control strategies are important considerations when analyzing a model. The underlying biology of the mosquito host and the biological control agent must be carefully considered when deciding what to include in a model. Factors such as density dependent population growth in the host, the searching efficiency and aggregation of a natural enemy, and the resource base of both have been shown to influence the stability and dynamics of the interaction. Including existing mosquito control practices into a model is useful if biological control is proposed for locations with current insecticidal control. The development of Integrated Pest Management (IPM) strategies can be enhanced using modeling techniques, as a wide variety of options can be simulated and examined. Models can also be valuable in comparing alternate routes of disease transmission and to investigate the level of control needed to reduce transmission.

  15. Modeling, Control and Coordination of Helicopter Systems

    CERN Document Server

    Ren, Beibei; Chen, Chang; Fua, Cheng-Heng; Lee, Tong Heng

    2012-01-01

    Modeling, Control and Coordination of Helicopter Systems provides a comprehensive treatment of helicopter systems, ranging from related nonlinear flight dynamic modeling and stability analysis to advanced control design for single helicopter systems, and also covers issues related to the coordination and formation control of multiple helicopter systems to achieve high performance tasks. Ensuring stability in helicopter flight is a challenging problem for nonlinear control design and development. This book is a valuable reference on modeling, control and coordination of helicopter systems,providing readers with practical solutions for the problems that still plague helicopter system design and implementation. Readers will gain a complete picture of helicopters at the systems level, as well as a better understanding of the technical intricacies involved. This book also: Presents a complete picture of modeling, control and coordination for helicopter systems Provides a modeling platform for a general class of ro...

  16. THE INTERNAL CONTROL MODELS IN ROMANIA

    OpenAIRE

    2015-01-01

    Internal control is indissolubly linked to business and accounting. Throughout history, domestic and international trade has grown exponentially, which has led to an increasing complexity of internal control, to new methods and techniques to control the business. The literature has presented the first models of internal control in the Sumerian period (3600 - 3200 BC), and the emergence and development of internal control in Egypt, Persia, Greek and Roman Empire, in the Middle Ages...

  17. THE INTERNAL CONTROL MODELS IN ROMANIA

    OpenAIRE

    TEODORESCU CRISTIAN DRAGOS

    2015-01-01

    Internal control is indissolubly linked to business and accounting. Throughout history, domestic and international trade has grown exponentially, which has led to an increasing complexity of internal control, to new methods and techniques to control the business. The literature has presented the first models of internal control in the Sumerian period (3600 - 3200 BC), and the emergence and development of internal control in Egypt, Persia, Greek and Roman Empire, in the Middle Ages till modern...

  18. Model-Based Power Plant Master Control

    Energy Technology Data Exchange (ETDEWEB)

    Boman, Katarina; Thomas, Jean; Funkquist, Jonas

    2010-08-15

    The main goal of the project has been to evaluate the potential of a coordinated master control for a solid fuel power plant in terms of tracking capability, stability and robustness. The control strategy has been model-based predictive control (MPC) and the plant used in the case study has been the Vattenfall power plant Idbaecken in Nykoeping. A dynamic plant model based on nonlinear physical models was used to imitate the true plant in MATLAB/SIMULINK simulations. The basis for this model was already developed in previous Vattenfall internal projects, along with a simulation model of the existing control implementation with traditional PID controllers. The existing PID control is used as a reference performance, and it has been thoroughly studied and tuned in these previous Vattenfall internal projects. A turbine model was developed with characteristics based on the results of steady-state simulations of the plant using the software EBSILON. Using the derived model as a representative for the actual process, an MPC control strategy was developed using linearization and gain-scheduling. The control signal constraints (rate of change) and constraints on outputs were implemented to comply with plant constraints. After tuning the MPC control parameters, a number of simulation scenarios were performed to compare the MPC strategy with the existing PID control structure. The simulation scenarios also included cases highlighting the robustness properties of the MPC strategy. From the study, the main conclusions are: - The proposed Master MPC controller shows excellent set-point tracking performance even though the plant has strong interactions and non-linearity, and the controls and their rate of change are bounded. - The proposed Master MPC controller is robust, stable in the presence of disturbances and parameter variations. Even though the current study only considered a very small number of the possible disturbances and modelling errors, the considered cases are

  19. THE INTERNAL CONTROL MODELS IN ROMANIA

    Directory of Open Access Journals (Sweden)

    TEODORESCU CRISTIAN DRAGOȘ

    2015-06-01

    Full Text Available Internal control is indissolubly linked to business and accounting. Throughout history, domestic and international trade has grown exponentially, which has led to an increasing complexity of internal control, to new methods and techniques to control the business. The literature has presented the first models of internal control in the Sumerian period (3600 - 3200 BC, and the emergence and development of internal control in Egypt, Persia, Greek and Roman Empire, in the Middle Ages till modern times. The purpose of this article is to present the models of internal control in Romania, starting from the principles of the classical model of internal control (COSO model. For a better understanding of the implication of internal control in terms of public and private sector, I have structured the article in the following parts: (a the definition of internal control in the literature; (b the presentation of the COSO model; (c internal control and internal audit in public institutions; (d internal control issues in accounting regulations on the individual and consolidated annual financial statements; (e internal / managerial control; (f conclusions.

  20. ROBUST INTERNAL MODEL CONTROL STRATEGY BASED PID CONTROLLER FOR BLDCM

    Directory of Open Access Journals (Sweden)

    A.PURNA CHANDRA RAO

    2010-11-01

    Full Text Available All the closed loop control system requires the controller for improvement of transient response of the error signal. Though the tuning of PID controller in real time is bit difficult and moreover it lacks the disturbance rejection capability. This paper presents a tuning of PID parameters based on internal model strategy. The advantageous of the proposed control strategy is well described in the paper. To test the validity of the proposed control, it is implemented in brushless dc motor drive. The mathematical model of brushless dc motor (BLDC is presented for control design. In addition the robustness of the control strategy is discussed. The proposed control strategy possesses good transient responses and good load disturbance response. In addition, the proposed control strategy possesses good tracking ability. To test the effectiveness of the proposed strategy, the BLDC is represented in transfer function model and later implemented in test system. The results are presented to validate the proposed control strategy for BLDC drive.

  1. 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.

  2. Model predictive control of MSMPR crystallizers

    Science.gov (United States)

    Moldoványi, Nóra; Lakatos, Béla G.; Szeifert, Ferenc

    2005-02-01

    A multi-input-multi-output (MIMO) control problem of isothermal continuous crystallizers is addressed in order to create an adequate model-based control system. The moment equation model of mixed suspension, mixed product removal (MSMPR) crystallizers that forms a dynamical system is used, the state of which is represented by the vector of six variables: the first four leading moments of the crystal size, solute concentration and solvent concentration. Hence, the time evolution of the system occurs in a bounded region of the six-dimensional phase space. The controlled variables are the mean size of the grain; the crystal size-distribution and the manipulated variables are the input concentration of the solute and the flow rate. The controllability and observability as well as the coupling between the inputs and the outputs was analyzed by simulation using the linearized model. It is shown that the crystallizer is a nonlinear MIMO system with strong coupling between the state variables. Considering the possibilities of the model reduction, a third-order model was found quite adequate for the model estimation in model predictive control (MPC). The mean crystal size and the variance of the size distribution can be nearly separately controlled by the residence time and the inlet solute concentration, respectively. By seeding, the controllability of the crystallizer increases significantly, and the overshoots and the oscillations become smaller. The results of the controlling study have shown that the linear MPC is an adaptable and feasible controller of continuous crystallizers.

  3. Flexible AC transmission systems modelling and control

    CERN Document Server

    Zhang, Xiao-Ping; Pal, Bikash

    2012-01-01

    The extended and revised second edition of this successful monograph presents advanced modeling, analysis and control techniques of Flexible AC Transmission Systems (FACTS). The book covers comprehensively a range of power-system control problems: from steady-state voltage and power flow control, to voltage and reactive power control, to voltage stability control, to small signal stability control using FACTS controllers. In the six years since the first edition of the book has been published research on the FACTS has continued to flourish while renewable energy has developed into a mature and

  4. 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.

  5. Model based development of engine control algorithms

    NARCIS (Netherlands)

    Dekker, H.J.; Sturm, W.L.

    1996-01-01

    Model based development of engine control systems has several advantages. The development time and costs are strongly reduced because much of the development and optimization work is carried out by simulating both engine and control system. After optimizing the control algorithm it can be executed b

  6. Model Predictive Control of Sewer Networks

    Science.gov (United States)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik; Poulsen, Niels K.; Falk, Anne K. V.

    2017-01-01

    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 controlled have thus become essential factors for effcient 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 benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control.

  7. Multiple models adaptive feedforward decoupling controller

    Institute of Scientific and Technical Information of China (English)

    Wang Xin; Li Shaoyuan; Wang Zhongjie

    2005-01-01

    When the parameters of the system change abruptly, a new multivariable adaptive feedforward decoupling controller using multiple models is presented to improve the transient response. The system models are composed of multiple fixed models, one free-running adaptive model and one re-initialized adaptive model. The fixed models are used to provide initial control to the process. The re-initialized adaptive model can be reinitialized as the selected model to improve the adaptation speed. The free-running adaptive controller is added to guarantee the overall system stability. At each instant, the best system model is selected according to the switching index and the corresponding controller is designed. During the controller design, the interaction is viewed as the measurable disturbance and eliminated by the choice of the weighting polynomial matrix. It not only eliminates the steady-state error but also decouples the system dynamically. The global convergence is obtained and several simulation examples are presented to illustrate the effectiveness of the proposed controller.

  8. 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...

  9. Remote control missile model test

    Science.gov (United States)

    Allen, Jerry M.; Shaw, David S.; Sawyer, Wallace C.

    1989-01-01

    An extremely large, systematic, axisymmetric body/tail fin data base was gathered through tests of an innovative missile model design which is described herein. These data were originally obtained for incorporation into a missile aerodynamics code based on engineering methods (Program MISSILE3), but can also be used as diagnostic test cases for developing computational methods because of the individual-fin data included in the data base. Detailed analysis of four sample cases from these data are presented to illustrate interesting individual-fin force and moment trends. These samples quantitatively show how bow shock, fin orientation, fin deflection, and body vortices can produce strong, unusual, and computationally challenging effects on individual fin loads. Comparisons between these data and calculations from the SWINT Euler code are also presented.

  10. Information modeling system for blast furnace control

    Science.gov (United States)

    Spirin, N. A.; Gileva, L. Y.; Lavrov, V. V.

    2016-09-01

    Modern Iron & Steel Works as a rule are equipped with powerful distributed control systems (DCS) and databases. Implementation of DSC system solves the problem of storage, control, protection, entry, editing and retrieving of information as well as generation of required reporting data. The most advanced and promising approach is to use decision support information technologies based on a complex of mathematical models. The model decision support system for control of blast furnace smelting is designed and operated. The basis of the model system is a complex of mathematical models created using the principle of natural mathematical modeling. This principle provides for construction of mathematical models of two levels. The first level model is a basic state model which makes it possible to assess the vector of system parameters using field data and blast furnace operation results. It is also used to calculate the adjustment (adaptation) coefficients of the predictive block of the system. The second-level model is a predictive model designed to assess the design parameters of the blast furnace process when there are changes in melting conditions relative to its current state. Tasks for which software is developed are described. Characteristics of the main subsystems of the blast furnace process as an object of modeling and control - thermal state of the furnace, blast, gas dynamic and slag conditions of blast furnace smelting - are presented.

  11. Wind farm models and control strategies

    Energy Technology Data Exchange (ETDEWEB)

    Soerensen, Poul; Hansen, Anca D.; Iov, F.; Blaabjerg, F.; Donovan, M.H.

    2005-08-01

    This report describes models and control strategies for 3 different concepts of wind farms. Initially, the potential in improvement of grid integration, structural loads and energy production is investigated in a survey of opportunities. Then simulation models are described, including wind turbine models for a fixed speed wind turbine with active stall control and a variable speed wind turbine with doubly-fed induction generator. After that, the 3 wind farm concepts and control strategies are described. The 3 concepts are AC connected doubly fed turbines, AC connected active stall turbines and DC connected active stall turbines. Finally, some simulation examples and conclusions are presented. (au)

  12. Development and Integration of Control System Models

    Science.gov (United States)

    Kim, Young K.

    1998-01-01

    The computer simulation tool, TREETOPS, has been upgraded and used at NASA/MSFC to model various complicated mechanical systems and to perform their dynamics and control analysis with pointing control systems. A TREETOPS model of Advanced X-ray Astrophysics Facility - Imaging (AXAF-1) dynamics and control system was developed to evaluate the AXAF-I pointing performance for Normal Pointing Mode. An optical model of Shooting Star Experiment (SSE) was also developed and its optical performance analysis was done using the MACOS software.

  13. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    to check if the network is controllable. Afterward the pressure control problem in water supply systems is formulated as an optimal control problem. The goal is to minimize the power consumption in pumps and also to regulate the pressure drop at the end-users to a desired value. The formulated optimal...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...... systems. To have better understanding of water leakage, to control pressure and leakage effectively and for optimal design of water supply system, suitable modeling is an important prerequisite. Therefore a model with the main objective of pressure control and consequently leakage reduction is presented...

  14. Modelling supervisory controller for hybrid power systems

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, A.; Bindner, H.; Lundsager, P. [Risoe National Lab., Roskilde (Denmark); Jannerup, O. [Technical Univ. of Denmark, Dept. of Automation, Lyngby (Denmark)

    1999-03-01

    Supervisory controllers are important to achieve optimal operation of hybrid power systems. The performance and economics of such systems depend mainly on the control strategy for switching on/off components. The modular concept described in this paper is an attempt to design standard supervisory controllers that could be used in different applications, such as village power and telecommunication applications. This paper presents some basic aspects of modelling and design of modular supervisory controllers using the object-oriented modelling technique. The functional abstraction hierarchy technique is used to formulate the control requirements and identify the functions of the control system. The modular algorithm is generic and flexible enough to be used with any system configuration and several goals (different applications). The modularity includes accepting modification of system configuration and goals during operation with minor or no changes in the supervisory controller. (au)

  15. Robust control of an aircraft model

    Energy Technology Data Exchange (ETDEWEB)

    Werner, H. [Bochum Univ. (Germany). Fakultaet fuer Elektrotechnik

    1999-12-01

    A new multimodel approach to robust controller design is illustrated by a practical application: for a laboratory aircraft model, a robust controller is designed simultaneously for normal operating conditions and for propeller failure. Based on a linear model for each operating mode, an LMI formulation of the problem and convex programming are used to search for a state feedback controller which achieves the objective. This state feedback design is then realized simultaneously in both operating modes by a controller which is based on fast output sampling. Robust performance is demonstrated by experimental results. (orig.)

  16. Robust control of an aircraft model

    Energy Technology Data Exchange (ETDEWEB)

    Werner, H. (Bochum Univ. (Germany). Fakultaet fuer Elektrotechnik)

    1999-01-01

    A new multimodel approach to robust controller design is illustrated by a practical application: for a laboratory aircraft model, a robust controller is designed simultaneously for normal operating conditions and for propeller failure. Based on a linear model for each operating mode, an LMI formulation of the problem and convex programming are used to search for a state feedback controller which achieves the objective. This state feedback design is then realized simultaneously in both operating modes by a controller which is based on fast output sampling. Robust performance is demonstrated by experimental results. (orig.)

  17. Contrast Gain Control Model Fits Masking Data

    Science.gov (United States)

    Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)

    1994-01-01

    We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.

  18. Improving Wind Farm Dispatchability Using Model Predictive Control for Optimal Operation of Grid-Scale Energy Storage

    Directory of Open Access Journals (Sweden)

    Douglas Halamay

    2014-09-01

    Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.

  19. 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......-domain constraints on signals. During the last decades several theoretical advances have been made, so that it can handle a wide variety of system structures. In this thesis, the focus is on handling uncertain linear system description. To this end the so-called Youla parameterizations have been used. Two methods...... are proposed: The first method exploits the modularity of the parameterizations so that the uncertainty can be identified and the MPC controller can be reconfigured in a modular setting. The second method is a robust MPC method in which the Youla parameters are used as an integral part of the online...

  20. Aspects of modelling and control of bioprocesses

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Xiachang

    1995-12-31

    The modelling and control of bioprocesses are the main subjects in this thesis. Different modelling approaches are proposed for different purposes in various bioprocesses. A conventional global model was constructed for a very complex mammalian cell culture process. A new concept of functional state and a multiple model (local models) approach were used for modelling the fed-batch baker`s yeast process for monitoring and control purposes. Finally, a combination of conventional electrical and biological models was used to simulate and to control a microbial fuel cell process. In the thesis, a yeast growth process was taken as an example to demonstrate the usefulness of the functional state concept and local models. The functional states were first defined according to the yeast metabolism. The process was then described by a set of simple local models. In different functional states, different local models were used. On the other hand, the on-line estimation of functional state and biomass of the process was discussed for process control purpose. As a consequence, both the functional state concept and the multiple model approach were applied for fuzzy logic control of yeast growth process. A fuzzy factor was calculated on the basis of a knowledge-based expert system and fuzzy logic rules. The factor was used to correct an ideal substrate feed rate. In the last part of the thesis, microbial fuel cell processes were studied. A microbial fuel cell is a device for direct conversion of chemical energy to electrical energy by using micro-organisms as catalysts. A combined model including conventional electrical and biological models was constructed for the process based on the biological and electrochemical phenomena

  1. Quantum Internal Model Principle: Decoherence Control

    CERN Document Server

    Ganesan, Narayan; 10.1109/CDC.2007.4434706

    2010-01-01

    In this article, we study the problem of Decoherence Control for quantum systems by employing a novel construction termed "the bait" and with techniques from geometric control theory, in order to successfully and completely decouple an open quantum system from its environment. We re-formulate the problem of Decoherence Control as a disturbance rejection scheme which also leads us to the idea of Internal Model Principle for quantum control systems which is first of its kind in the literature. Classical internal model principle provides the guidelines for designing linear controllers for perfect tracking in the presence of external disturbances, with the help of the internal model of the disturbance generator. The theory of Disturbance Decoupling of the output from external noises is another problem that is well studied for classical systems. The two problems focus on different aspects viz. perfect output tracking and complete decoupling of output in the presence of the noise respectively. However for quantum s...

  2. Mob control models of threshold collective behavior

    CERN Document Server

    Breer, Vladimir V; Rogatkin, Andrey D

    2017-01-01

    This book presents mathematical models of mob control with threshold (conformity) collective decision-making of the agents. Based on the results of analysis of the interconnection between the micro- and macromodels of active network structures, it considers the static (deterministic, stochastic and game-theoretic) and dynamic (discrete- and continuous-time) models of mob control, and highlights models of informational confrontation. Many of the results are applicable not only to mob control problems, but also to control problems arising in social groups, online social networks, etc. Aimed at researchers and practitioners, it is also a valuable resource for undergraduate and postgraduate students as well as doctoral candidates specializing in the field of collective behavior modeling.

  3. A Course in... Model Predictive Control.

    Science.gov (United States)

    Arkun, Yaman; And Others

    1988-01-01

    Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)

  4. 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...... facilitates plug-and-play addition of subsystems without redesign of any controllers. The method is supported by a number of simulations featuring a three-level smart-grid power control system for a small isolated power grid....

  5. Model Based Adaptive Piecewise Linear Controller for Complicated Control Systems

    Directory of Open Access Journals (Sweden)

    Tain-Sou Tsay

    2014-01-01

    Full Text Available A model based adaptive piecewise linear control scheme for industry processes with specifications on peak overshoots and rise times is proposed. It is a gain stabilized control technique. Large gain is used for large tracking error to get fast response. Small gain is used between large and small tracking error for good performance. Large gain is used again for small tracking error to cope with large disturbance. Parameters of the three-segment piecewise linear controller are found by an automatic regulating time series which is function of output characteristics of the plant and reference model. The time series will be converged to steady values after the time response of the considered system matching that of the reference model. The proposed control scheme is applied to four numerical examples which have been compensated by PID controllers. Parameters of PID controllers are found by optimization method. It gives an almost command independent response and gives significant improvements for response time and performance.

  6. Model-based control of networked systems

    CERN Document Server

    Garcia, Eloy; Montestruque, Luis A

    2014-01-01

    This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled.   The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control.   Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...

  7. Modelling and control of a flotation process

    Energy Technology Data Exchange (ETDEWEB)

    Ding, L.; Gustafsson, T. [Control Engineering Group, Lulea Univ. of Technology, Lulea (Sweden)

    1999-07-01

    A general description of a flotation process is given. The dynamic model of a MIMO nonlinear subprocess in flotation, i. e. the pulp levels in five compartments in series is developed and the model is verified with real data from a production plant. In order to reject constant disturbances five extra states are introduced and the model is modified. An exact linearization has been made for the non-linear model and a linear quadratic gaussian controller is proposed based on the linearized model. The simulation result shows an improved performance of the pulp level control when the set points are changed or a disturbance occur. In future the controller will be tested in production. (author)

  8. Modeling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.

    System concepts

    In Chapters 1 and 2 an overview of the problem formulation

  9. Modelling and (adaptive) control of greenhouse climates

    NARCIS (Netherlands)

    Udink ten Cate, A.J.

    1983-01-01

    The material presented in this thesis can be grouped around four themes, system concepts, modeling, control and adaptive control. In this summary these themes will be treated separately.System conceptsIn Chapters 1 and 2 an overview of the problem formulation is presented. It is suggested that there

  10. Model-Free Adaptive Heating Process Control

    OpenAIRE

    Ivana LUKÁČOVÁ; Piteľ, Ján

    2009-01-01

    The aim of this paper is to analyze the dynamic behaviour of a Model-Free Adaptive (MFA) heating process control. The MFA controller is designed as three layer neural network with proportional element. The method of backward propagation of errors was used for neural network training. Visualization and training of the artificial neural network was executed by Netlab in Matlab environment. Simulation of the MFA heating process control with outdoor temperature compensation has proved better resu...

  11. Controllability, Observability, and Stability of Mathematical Models

    OpenAIRE

    Iggidr, Abderrahman

    2004-01-01

    International audience; This article presents an overview of three fundamental concepts in Mathematical System Theory: controllability, stability and observability. These properties play a prominent role in the study of mathematical models and in the understanding of their behavior. They constitute the main research subject in Control Theory. Historically the tools and techniques of Automatic Control have been developed for artificial engineering systems but nowadays they are more and more ap...

  12. Development of Control Models and a Robust Multivariable Controller for Surface Shape Control

    Energy Technology Data Exchange (ETDEWEB)

    Winters, Scott Eric [Univ. of California, Davis, CA (United States)

    2003-06-18

    Surface shape control techniques are applied to many diverse disciplines, such as adaptive optics, noise control, aircraft flutter control and satellites, with an objective to achieve a desirable shape for an elastic body by the application of distributed control forces. Achieving the desirable shape is influenced by many factors, such as, actuator locations, sensor locations, surface precision and controller performance. Building prototypes to complete design optimizations or controller development can be costly or impractical. This shortfall, puts significant value in developing accurate modeling and control simulation approaches. This thesis focuses on the field of adaptive optics, although these developments have the potential for application in many other fields. A static finite element model is developed and validated using a large aperture interferometer system. This model is then integrated into a control model using a linear least squares algorithm and Shack-Hartmann sensor. The model is successfully exercised showing functionality for various wavefront aberrations. Utilizing a verified model shows significant value in simulating static surface shape control problems with quantifiable uncertainties. A new dynamic model for a seven actuator deformable mirror is presented and its accuracy is proven through experiment. Bond graph techniques are used to generate the state space model of the multi-actuator deformable mirror including piezo-electric actuator dynamics. Using this verified model, a robust multi-input multi-output (MIMO) H controller is designed and implemented. This controller proved superior performance as compared to a standard proportional-integral controller (PI) design.

  13. Wind farm models and control strategies

    DEFF Research Database (Denmark)

    Sørensen, Poul Ejnar; Hansen, Anca Daniela; Iov, F.;

    2005-01-01

    models for a fixed speed wind turbine with active stall control and a variable speed wind turbine with doubly-fed induction generator. After that, the 3 wind farm concepts and control strategies are described.The 3 concepts are AC connected doubly fed turbines, AC connected active stall turbines and DC......This report describes models and control strategies for 3 different concepts of wind farms. Initially, the potential in improvement of grid integration, structural loads and energy production is investigated in a survey of opportunities. Then simulationmodels are described, including wind turbine...

  14. Switching Control System Based on Robust Model Reference Adaptive Control

    Institute of Scientific and Technical Information of China (English)

    HU Qiong; FEI Qing; MA Hongbin; WU Qinghe; GENG Qingbo

    2016-01-01

    For conventional adaptive control,time-varying parametric uncertainty and unmodeled dynamics are ticklish problems,which will lead to undesirable performance or even instability and nonrobust behavior,respectively.In this study,a class of discrete-time switched systems with unmodeled dynamics is taken into consideration.Moreover,nonlinear systems are here supposed to be approximated with the class of switched systems considered in this paper,and thereby switching control design is investigated for both switched systems and nonlinear systems to assure stability and performance.For robustness against unmodeled dynamics and uncertainty,robust model reference aclaptive control (RMRAC) law is developed as the basis of controller design for each individual subsystem in the switched systems or nonlinear systems.Meanwhile,two different switching laws are presented for switched systems and nonlinear systems,respectively.Thereby,the authors incorporate the corresponding switching law into the RMRAC law to construct two schemes of switching control respectively for the two kinds of controlled systems.Both closed-loop analyses and simulation examples are provided to illustrate the validity of the two proposed switching control schemes.Furthermore,as to the proposed scheme for nonlinear systems,its potential for practical application is demonstrated through simulations of longitudinal control for F-16 aircraft.

  15. 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 ...

  16. Bayesian modeling of flexible cognitive control.

    Science.gov (United States)

    Jiang, Jiefeng; Heller, Katherine; Egner, Tobias

    2014-10-01

    "Cognitive control" describes endogenous guidance of behavior in situations where routine stimulus-response associations are suboptimal for achieving a desired goal. The computational and neural mechanisms underlying this capacity remain poorly understood. We examine recent advances stemming from the application of a Bayesian learner perspective that provides optimal prediction for control processes. In reviewing the application of Bayesian models to cognitive control, we note that an important limitation in current models is a lack of a plausible mechanism for the flexible adjustment of control over conflict levels changing at varying temporal scales. We then show that flexible cognitive control can be achieved by a Bayesian model with a volatility-driven learning mechanism that modulates dynamically the relative dependence on recent and remote experiences in its prediction of future control demand. We conclude that the emergent Bayesian perspective on computational mechanisms of cognitive control holds considerable promise, especially if future studies can identify neural substrates of the variables encoded by these models, and determine the nature (Bayesian or otherwise) of their neural implementation.

  17. Intelligent Mechatronic Systems Modeling, Control and Diagnosis

    CERN Document Server

    Merzouki, Rochdi; Pathak, Pushparaj Mani; Ould Bouamama, Belkacem

    2013-01-01

    Acting as a support resource for practitioners and professionals looking to advance their understanding of complex mechatronic systems, Intelligent Mechatronic Systems explains their design and recent developments from first principles to practical applications. Detailed descriptions of the mathematical models of complex mechatronic systems, developed from fundamental physical relationships, are built on to develop innovative solutions with particular emphasis on physical model-based control strategies. Following a concurrent engineering approach, supported by industrial case studies, and drawing on the practical experience of the authors, Intelligent Mechatronic Systems covers range of topic and includes:  • An explanation of a common graphical tool for integrated design and its uses from modeling and simulation to the control synthesis • Introductions to key concepts such as different means of achieving fault tolerance, robust overwhelming control and force and impedance control • Dedicated chapters ...

  18. A Simple HCCI Engine Model for Control

    Energy Technology Data Exchange (ETDEWEB)

    Killingsworth, N; Aceves, S; Flowers, D; Krstic, M

    2006-06-29

    The homogeneous charge compression ignition (HCCI) engine is an attractive technology because of its high efficiency and low emissions. However, HCCI lacks a direct combustion trigger making control of combustion timing challenging, especially during transients. To aid in HCCI engine control we present a simple model of the HCCI combustion process valid over a range of intake pressures, intake temperatures, equivalence ratios, and engine speeds. The model provides an estimate of the combustion timing on a cycle-by-cycle basis. An ignition threshold, which is a function of the in-cylinder motored temperature and pressure is used to predict start of combustion. This model allows the synthesis of nonlinear control laws, which can be utilized for control of an HCCI engine during transients.

  19. A comparison of model view controller and model view presenter

    OpenAIRE

    Qureshi, M. Rizwan Jameel; Sabir, Fatima

    2014-01-01

    Web application frameworks are managed by using different design strategies. Design strategies are applied by using different design processes. In each design process, requirement specifications are changed in to different design model that describe the detail of different data structure, system architecture, interface and components. Web application frame work is implemented by using Model View Controller (MVC) and Model View Presenter (MVP). These web application models are used to provide ...

  20. Stochastic Control Model on Rent Seeking

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A continuous-time stochastic model is constructed to analyze how to control rent seeking behaviors. Using the stochastic optimization methods based on the modern risky theory, a unique positive solution to the dynamic model is derived. The effects of preference-related parameters on the optimal control level of rent seeking are discussed, and some policy measures are given. The results show that there exists a unique solution to the stochastic dynamic model under some macroeconomic assumptions, and that raising public expenditure may have reverse effects on rent seeking in an underdeveloped or developed economic environment.

  1. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    R. G. SILVA

    1999-03-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  2. Control model for reconfigurable assembly systems

    Institute of Scientific and Technical Information of China (English)

    Yu Jianfeng; Yin Yuehong; Chen Zhaoneng

    2005-01-01

    This paper proposes knowledge based object-oriented timed colored Petri net, a modeling method for reconfigurable assembly systems. Combining knowledge and object-oriented method into timed colored Petri net, a comprehensive and powerful representation model for control of RAS is obtained. With object-oriented method the whole system can be decomposed into concrete objects explicitly, and their relationships are constructed according to the system assembly requirements. Finally, a simple assembly system modeled by the KTCOPN is presented.

  3. Chaos control in traffic flow models

    CERN Document Server

    Shahverdiev, E M; Shahverdiev, Elman Mohammed; Tadaki, Shin-ichi

    1998-01-01

    Chaos control in some of the one- and two-dimensional traffic flow dynamical models in the mean field theory is studied.One dimensional model is investigated taking into account the effect of random delay. Two dimensional model takes into account the effects of overpasses, symmetric distribution of cars and blockages of cars moving in the same direction. Chaos synchronization is performed within both replica and nonreplica approaches, and using parameter perturbation method.

  4. Modeling Robot Flexibility for Endpoint Force Control.

    Science.gov (United States)

    1988-05-01

    SIDM 19. KE9Y WORDS fCntknu. OnPVOO&O 0401 It 00041000111O ed 0000#uF 6P 1111411 amA.w) robot force control * robot control / robot dynamics flexible...no. 3, pp. 62-75. [2] Eppinger, S.D. and Seering, W.P. On Dynamic Models of Robot Force Control . In Proceedings of International Conference on...W.P. Understanding Bandwidth Limitations in Robot Force Control . In Proceedings of International Conference on Robotics and Automation. IEEE, April 1987

  5. Explicit model predictive control accuracy analysis

    OpenAIRE

    Knyazev, Andrew; Zhu, Peizhen; Di Cairano, Stefano

    2015-01-01

    Model Predictive Control (MPC) can efficiently control constrained systems in real-time applications. MPC feedback law for a linear system with linear inequality constraints can be explicitly computed off-line, which results in an off-line partition of the state space into non-overlapped convex regions, with affine control laws associated to each region of the partition. An actual implementation of this explicit MPC in low cost micro-controllers requires the data to be "quantized", i.e. repre...

  6. Modelling and simulations of controlled release fertilizer

    Science.gov (United States)

    Irfan, Sayed Ameenuddin; Razali, Radzuan; Shaari, Ku Zilati Ku; Mansor, Nurlidia

    2016-11-01

    The recent advancement in controlled release fertilizer has provided an alternative solution to the conventional urea, controlled release fertilizer has a good plant nutrient uptake they are environment friendly. To have an optimum plant intake of nutrients from controlled release fertilizer it is very essential to understand the release characteristics. A mathematical model is developed to predict the release characteristics from polymer coated granule. Numerical simulations are performed by varying the parameters radius of granule, soil water content and soil porosity to study their effect on fertilizer release. Understanding these parameters helps in the better design and improve the efficiency of controlled release fertilizer.

  7. Bayesian modeling of flexible cognitive control

    Science.gov (United States)

    Jiang, Jiefeng; Heller, Katherine; Egner, Tobias

    2014-01-01

    “Cognitive control” describes endogenous guidance of behavior in situations where routine stimulus-response associations are suboptimal for achieving a desired goal. The computational and neural mechanisms underlying this capacity remain poorly understood. We examine recent advances stemming from the application of a Bayesian learner perspective that provides optimal prediction for control processes. In reviewing the application of Bayesian models to cognitive control, we note that an important limitation in current models is a lack of a plausible mechanism for the flexible adjustment of control over conflict levels changing at varying temporal scales. We then show that flexible cognitive control can be achieved by a Bayesian model with a volatility-driven learning mechanism that modulates dynamically the relative dependence on recent and remote experiences in its prediction of future control demand. We conclude that the emergent Bayesian perspective on computational mechanisms of cognitive control holds considerable promise, especially if future studies can identify neural substrates of the variables encoded by these models, and determine the nature (Bayesian or otherwise) of their neural implementation. PMID:24929218

  8. 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...

  9. Model Predictive Control of Wind Turbines

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian

    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......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...

  10. Optimal control application to an Ebola model

    Institute of Scientific and Technical Information of China (English)

    Ebenezer Bonyah; Kingsley Badu; Samuel Kwesi Asiedu-Addo

    2016-01-01

    Ebola virus is a severe,frequently fatal illness,with a case fatality rate up to 90%.The outbreak of the disease has been acknowledged by World Health Organization as Public Health Emergency of International Concern.The threat of Ebola in West Africa is still a major setback to the socioeconomic development.Optimal control theory is applied to a system of ordinary differential equations which is modeling Ebola infection through three different routes including contact between humans and a dead body.In an attempt to reduce infection in susceptible population,a preventive control is put in the form of education and campaign and two treatment controls are applied to infected and late-stage infected(super) human population.The Pontryagins maximum principle is employed to characterize optimality control,which is then solved numerically.It is observed that time optimal control is existed in the model.The activation of each control showed a positive reduction of infection.The overall effect of activation of all the controls simultaneously reduced the effort required for the reduction of the infection quickly.The obtained results present a good framework for planning and designing cost-effective strategies for good interventions in dealing with Ebola disease.It is established that in order to reduce Ebola threat all the three controls must be taken into consideration concurrently.

  11. Mathematical modelling of leprosy and its control.

    Science.gov (United States)

    Blok, David J; de Vlas, Sake J; Fischer, Egil A J; Richardus, Jan Hendrik

    2015-03-01

    Leprosy or Hansen's disease is an infectious disease caused by the bacterium Mycobacterium leprae. The annual number of new leprosy cases registered worldwide has remained stable over the past years at over 200,000. Early case finding and multidrug therapy have not been able interrupt transmission completely. Elimination requires innovation in control and sustained commitment. Mathematical models can be used to predict the course of leprosy incidence and the effect of intervention strategies. Two compartmental models and one individual-based model have been described in the literature. Both compartmental models investigate the course of leprosy in populations and the long-term impact of control strategies. The individual-based model focusses on transmission within households and the impact of case finding among contacts of new leprosy patients. Major improvement of these models should result from a better understanding of individual differences in exposure to infection and developing leprosy after exposure. Most relevant are contact heterogeneity, heterogeneity in susceptibility and spatial heterogeneity. Furthermore, the existing models have only been applied to a limited number of countries. Parameterization of the models for other areas, in particular those with high incidence, is essential to support current initiatives for the global elimination of leprosy. Many challenges remain in understanding and dealing with leprosy. The support of mathematical models for understanding leprosy epidemiology and supporting policy decision making remains vital.

  12. Modeling and Control of Large Flexible Structures.

    Science.gov (United States)

    1984-07-31

    systems with hybrid (lumped and distributed) structure. * -3.Development of stabilizing control strategies for nonlinear distributed models, including...process, but much more needs to be done. el .It ;,, "..- ,. ,-,,o’,, .4. : ") Part I: :i: ’i" ’" Wierner-Hopf Methods for Design of Stabilizing ... Control Systems :: Z’" ..-- -~ . . . . .. . . . . . . ... . . . . .......- ~ .. . . S 5 * * .5 .. ** .*% - * 5*55 * . . . . % % ’ * . ’ % , . :.:. -A

  13. Plant Modeling for Human Supervisory Control

    DEFF Research Database (Denmark)

    Lind, Morten

    1999-01-01

    This paper provides an overview of multilevel flow modelling (MFM) and its application for design of displays for the supervisory control of industrial plant. The problem of designing the inforrrzatian content of sacpervisory displays is discussed and plant representations like MFM using levels...... is also provided by an analysis of the relations between levels of abstraction. It is also described how MFM supparts reazsonin about control actions by defining levels of intervention and by modal distinctions between function enablement and initiation....

  14. Modelling Driver Assitance Systems by Optimal Control

    OpenAIRE

    Wang, M.; Daamen, W.; Hoogendoorn, S.P.; Van Arem, B.

    2012-01-01

    Driver assistance systems support drivers in operating vehicles in a safe, comfortable and efficient way, and thus may induce changes in traffic flow characteristics. This paper put forward a receding horizon control framework to model driver assistance systems. The accelerations of automated vehicles are determined to optimise a cost function, assuming other vehicles driving at stationary conditions over a prediction horizon. The flexibility of the framework is demonstrated with controller d...

  15. Insecticide control in a Dengue epidemics model

    CERN Document Server

    Rodrigues, Helena Sofia; Torres, Delfim F M

    2010-01-01

    A model for the transmission of dengue disease is presented. It consists of eight mutually-exclusive compartments representing the human and vector dynamics. It also includes a control parameter (insecticide) in order to fight the mosquitoes. The main goal of this work is to investigate the best way to apply the control in order to effectively reduce the number of infected humans and mosquitoes. A case study, using data of the outbreak that occurred in 2009 in Cape Verde, is presented.

  16. MODELING AND CONTROL OF MULTIVARIABLE DISTILLATION COLUMN USING MODEL PREDICTIVE CONTROL USING UNISIM

    Directory of Open Access Journals (Sweden)

    Abdul Wahid

    2016-02-01

    Full Text Available Distillation columns are widely used in chemical industry as unit operation and required advance process control because it has multi input multi output (MIMO or multi-variable system, which is hard to be controlled. Model predictive control (MPC is one of alternative controller developed for MIMO system due to loops interaction to be controlled. This study aimed to obtain dynamic model of process control on a distillation column using MPC, and to get the optimum performance of MPC controller. Process control in distillation columns performed by simulating the dynamic models of distillation columns by UNISIM R390.1 software. The optimization process was carried out by tuning the MPC controller parameters such as sampling time (Ts = 1 – 240 s, prediction horizon (P = 1-400, and the control horizon (M=1-400. The comparison between the performance of MPC and PI controller is presented and Integral Absolut Error (IAE was used as comparison parameter. The results indicate that the performance of MPC was better than PI controller for set point change 0.95 to 0.94 on distillate product composition using a modified model 1 with IAE 0.0584 for MPC controller and 0.0782 for PI controller.

  17. Modelling and control of dynamic systems using gaussian process models

    CERN Document Server

    Kocijan, Juš

    2016-01-01

    This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior know...

  18. 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 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...

  19. Stochastic Optimal Control Models for Online Stores

    CERN Document Server

    Bradonjić, Milan

    2011-01-01

    We present a model for the optimal design of an online auction/store by a seller. The framework we use is a stochastic optimal control problem. In our setting, the seller wishes to maximize her average wealth level, where she can control her price per unit via her reputation level. The corresponding Hamilton-Jacobi-Bellmann equation is analyzed for an introductory case. We then turn to an empirically justified model, and present introductory analysis. In both cases, {\\em pulsing} advertising strategies are recovered for resource allocation. Further numerical and functional analysis will appear shortly.

  20. Model Based Control of Reefer Container Systems

    DEFF Research Database (Denmark)

    Sørensen, Kresten Kjær

    This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together with the Da......This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together...

  1. 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.

  2. Highly integrated digital electronic control: Digital flight control, aircraft model identification, and adaptive engine control

    Science.gov (United States)

    Baer-Riedhart, Jennifer L.; Landy, Robert J.

    1987-01-01

    The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.

  3. Atom-Role-Based Access Control Model

    Science.gov (United States)

    Cai, Weihong; Huang, Richeng; Hou, Xiaoli; Wei, Gang; Xiao, Shui; Chen, Yindong

    Role-based access control (RBAC) model has been widely recognized as an efficient access control model and becomes a hot research topic of information security at present. However, in the large-scale enterprise application environments, the traditional RBAC model based on the role hierarchy has the following deficiencies: Firstly, it is unable to reflect the role relationships in complicated cases effectively, which does not accord with practical applications. Secondly, the senior role unconditionally inherits all permissions of the junior role, thus if a user is under the supervisor role, he may accumulate all permissions, and this easily causes the abuse of permission and violates the least privilege principle, which is one of the main security principles. To deal with these problems, we, after analyzing permission types and role relationships, proposed the concept of atom role and built an atom-role-based access control model, called ATRBAC, by dividing the permission set of each regular role based on inheritance path relationships. Through the application-specific analysis, this model can well meet the access control requirements.

  4. Modelling and Control of the Wavestar Prototype

    DEFF Research Database (Denmark)

    Hansen, Rico Hjerm; Kramer, Morten M.

    2011-01-01

    In the field of wave energy it is well known that control of point absorbers is essential in order to increase energy capture from waves. Correspondingly, advanced control is an integrated part of the Wavestar design. This paper presents the control method, referred to as the Wave Power Extraction...... Algorithm (WPEA), applied to the full-scale Wavestar Prototype for maximizing energy extraction. The WPEA is optimized based on simulations of the point absorbers in different sea states. Hence, a presentation of a hydrodynamic model of the Wavestar is included in the paper. A simplified Power Take-Off (PTO...

  5. Model based control of refrigeration systems

    Energy Technology Data Exchange (ETDEWEB)

    Sloth Larsen, L.F.

    2005-11-15

    The subject for this Ph.D. thesis is model based control of refrigeration systems. Model based control covers a variety of different types of controls, that incorporates mathematical models. In this thesis the main subject therefore has been restricted to deal with system optimizing control. The optimizing control is divided into two layers, where the system oriented top layers deals with set-point optimizing control and the lower layer deals with dynamical optimizing control in the subsystems. The thesis has two main contributions, i.e. a novel approach for set-point optimization and a novel approach for desynchronization based on dynamical optimization. The focus in the development of the proposed set-point optimizing control has been on deriving a simple and general method, that with ease can be applied on various compositions of the same class of systems, such as refrigeration systems. The method is based on a set of parameter depended static equations describing the considered process. By adapting the parameters to the given process, predict the steady state and computing a steady state gradient of the cost function, the process can be driven continuously towards zero gradient, i.e. the optimum (if the cost function is convex). The method furthermore deals with system constrains by introducing barrier functions, hereby the best possible performance taking the given constrains in to account can be obtained, e.g. under extreme operational conditions. The proposed method has been applied on a test refrigeration system, placed at Aalborg University, for minimization of the energy consumption. Here it was proved that by using general static parameter depended system equations it was possible drive the set-points close to the optimum and thus reduce the power consumption with up to 20%. In the dynamical optimizing layer the idea is to optimize the operation of the subsystem or the groupings of subsystems, that limits the obtainable system performance. In systems

  6. Standard controlled vocabulary for climate models

    Science.gov (United States)

    Moine, Marie-Pierre; Pascoe, Charlotte; Guilyardi, Eric; Ford, Rupert

    2010-05-01

    The scope of climate modeling has grown tremendously in the last 10 years, resulting in a large variety of climate models, increasing complexity with more physical or chemical components and huge volumes of data sets (simulation outputs). While significant efforts to standardise the associated metadata (i.e. data describing data and models) have already been made in recent projects (e.g. CF standard names for CMIP3), detailed standards documentation of the models and experiments that created this data is still lacking. The EU METAFOR Project (http://metaforclimate.eu) is specifically addressing this issue by creating new metadata schemas in cooperation with existing standards in Earth System Modeling (Curator, GridSpec, CF convention, NumSim, etc.). Descriptions of climate simulations, of the data they produce, and of the numerical models used to perform these simulations are all within the scope of METAFOR and these descriptions are assembled in a common information model (the CIM). Of particular note is the metadata for numerical models that is found in the CIM. This paper presents the controlled vocabulary (CV) that has been collected by METAFOR to describe (in a common manner) the components of the numerical models developed by the different modeling centres. This vocabulary is used in the model part of the web-based questionnaire that METAFOR has developed in support of the upcoming IPCC exercise (the CMIP5 questionnaire). The methods to (1) establish standards for this vocabulary via interactions with climate scientists, (2) utilise the vocabulary in the web-based questionnaire and (3) process the vocabulary for ingestion in the Earth System Grid (ESG) portal, are described. Governance aspects of this new controlled vocabulary are also addressed.

  7. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

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

    2008-01-01

    steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  8. Bicycle Rider Control: Observations, Modeling & Experiments

    NARCIS (Netherlands)

    Kooijman, J.D.G.

    2012-01-01

    Bicycle designers traditionally develop bicycles based on experience and trial and error. Adopting modern engineering tools to model bicycle and rider dynamics and control is another method for developing bicycles. This method has the potential to evaluate the complete design space, and thereby dev

  9. Modeling and control of antennas and telescopes

    CERN Document Server

    Gawronski, Wodek

    2008-01-01

    The book shows, step-by-step, the design, implementation, and testing of the antenna/telescope control system, from the design stage (analytical model) to fine tuning of the RF beam pointing (monopulse and conscan). It includes wide use of Matlab and Simulink..

  10. Power system stability modelling, analysis and control

    CERN Document Server

    Sallam, Abdelhay A

    2015-01-01

    This book provides a comprehensive treatment of the subject from both a physical and mathematical perspective and covers a range of topics including modelling, computation of load flow in the transmission grid, stability analysis under both steady-state and disturbed conditions, and appropriate controls to enhance stability.

  11. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  12. Control Architecture Modeling for Future Power Systems

    DEFF Research Database (Denmark)

    Heussen, Kai

    and operation structures; and finally the application to some concrete study cases, including a present system balancing, and proposed control structures such as Microgrids and Cells. In the second part, the main contributions are the outline of a formation strategy, integrating the design and model...

  13. Modeling the Aneuploidy Control of Cancer

    Directory of Open Access Journals (Sweden)

    Wang Zhong

    2010-07-01

    Full Text Available Abstract Background Aneuploidy has long been recognized to be associated with cancer. A growing body of evidence suggests that tumorigenesis, the formation of new tumors, can be attributed to some extent to errors occurring at the mitotic checkpoint, a major cell cycle control mechanism that acts to prevent chromosome missegregation. However, so far no statistical model has been available quantify the role aneuploidy plays in determining cancer. Methods We develop a statistical model for testing the association between aneuploidy loci and cancer risk in a genome-wide association study. The model incorporates quantitative genetic principles into a mixture-model framework in which various genetic effects, including additive, dominant, imprinting, and their interactions, are estimated by implementing the EM algorithm. Results Under the new model, a series of hypotheses tests are formulated to explain the pattern of the genetic control of cancer through aneuploid loci. Simulation studies were performed to investigate the statistical behavior of the model. Conclusions The model will provide a tool for estimating the effects of genetic loci on aneuploidy abnormality in genome-wide studies of cancer cells.

  14. 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...

  15. Computer Modelling and Simulation for Inventory Control

    Directory of Open Access Journals (Sweden)

    G.K. Adegoke

    2012-07-01

    Full Text Available This study concerns the role of computer simulation as a device for conducting scientific experiments on inventory control. The stores function utilizes a bulk of physical assets and engages a bulk of financial resources in a manufacturing outfit therefore there is a need for an efficient inventory control. The reason being that inventory control reduces cost of production and thereby facilitates the effective and efficient accomplishment of production objectives of an organization. Some mathematical and statistical models were used to compute the Economic Order Quantity (EOQ. Test data were gotten from a manufacturing company and same were simulated. The results generated were used to predict a real life situation and have been presented and discussed. The language of implementation for the three models is Turbo Pascal due to its capability, generality and flexibility as a scientific programming language.

  16. Hybrid adaptive control of a dragonfly model

    Science.gov (United States)

    Couceiro, Micael S.; Ferreira, Nuno M. F.; Machado, J. A. Tenreiro

    2012-02-01

    Dragonflies show unique and superior flight performances than most of other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, it is presented an adaptive scheme controlling a nonlinear model inspired in a dragonfly-like robot. It is proposed a hybrid adaptive ( HA) law for adjusting the parameters analyzing the tracking error. At the current stage of the project it is considered essential the development of computational simulation models based in the dynamics to test whether strategies or algorithms of control, parts of the system (such as different wing configurations, tail) as well as the complete system. The performance analysis proves the superiority of the HA law over the direct adaptive ( DA) method in terms of faster and improved tracking and parameter convergence.

  17. Nonsmooth mechanics models, dynamics and control

    CERN Document Server

    Brogliato, Bernard

    2016-01-01

    Now in its third edition, this standard reference is a comprehensive treatment of nonsmooth mechanical systems refocused to give more prominence to control and modelling. It covers Lagrangian and Newton–Euler systems, detailing mathematical tools such as convex analysis and complementarity theory. The ways in which nonsmooth mechanics influence and are influenced by well-posedness analysis, numerical analysis and simulation, modelling and control are explained. Contact/impact laws, stability theory and trajectory-tracking control are given in-depth exposition connected by a framework formed from complementarity systems and measure-differential inclusions. Links are established with electrical circuits with set-valued nonsmooth elements and with other nonsmooth dynamical systems like impulsive and piecewise linear systems. Nonsmooth Mechanics (third edition) has been substantially rewritten, edited and updated to account for the significant body of results that have emerged in the twenty-first century—incl...

  18. Modelling and Control of the Wavestar Prototype

    DEFF Research Database (Denmark)

    Hansen, Rico Hjerm; Kramer, Morten M.

    2011-01-01

    Algorithm (WPEA), applied to the full-scale Wavestar Prototype for maximizing energy extraction. The WPEA is optimized based on simulations of the point absorbers in different sea states. Hence, a presentation of a hydrodynamic model of the Wavestar is included in the paper. A simplified Power Take-Off (PTO......In the field of wave energy it is well known that control of point absorbers is essential in order to increase energy capture from waves. Correspondingly, advanced control is an integrated part of the Wavestar design. This paper presents the control method, referred to as the Wave Power Extraction......) is also added to the model, enabling the optimization of the WPEA to take into account the PTO constraints of PTO bandwidth and force limitations. The predicted results of the optimized WPEA are compared to real measurements from theWavestar Prototype, showing good compliance....

  19. Mathematical modeling of Chikungunya fever control

    Science.gov (United States)

    Hincapié-Palacio, Doracelly; Ospina, Juan

    2015-05-01

    Chikungunya fever is a global concern due to the occurrence of large outbreaks, the presence of persistent arthropathy and its rapid expansion throughout various continents. Globalization and climate change have contributed to the expansion of the geographical areas where mosquitoes Aedes aegypti and Aedes albopictus (Stegomyia) remain. It is necessary to improve the techniques of vector control in the presence of large outbreaks in The American Region. We derive measures of disease control, using a mathematical model of mosquito-human interaction, by means of three scenarios: a) a single vector b) two vectors, c) two vectors and human and non-human reservoirs. The basic reproductive number and critical control measures were deduced by using computer algebra with Maple (Maplesoft Inc, Ontario Canada). Control measures were simulated with parameter values obtained from published data. According to the number of households in high risk areas, the goals of effective vector control to reduce the likelihood of mosquito-human transmission would be established. Besides the two vectors, if presence of other non-human reservoirs were reported, the monthly target of effective elimination of the vector would be approximately double compared to the presence of a single vector. The model shows the need to periodically evaluate the effectiveness of vector control measures.

  20. Parametric uncertainty modeling for robust control

    DEFF Research Database (Denmark)

    Rasmussen, K.H.; Jørgensen, Sten Bay

    1999-01-01

    The dynamic behaviour of a non-linear process can often be approximated with a time-varying linear model. In the presented methodology the dynamics is modeled non-conservatively as parametric uncertainty in linear lime invariant models. The obtained uncertainty description makes it possible...... method can be utilized in identification of a nominal model with uncertainty description. The method is demonstrated on a binary distillation column operating in the LV configuration. The dynamics of the column is approximated by a second order linear model, wherein the parameters vary as the operating...... to perform robustness analysis on a control system using the structured singular value. The idea behind the proposed method is to fit a rational function to the parameter variation. The parameter variation can then be expressed as a linear fractional transformation (LFT), It is discussed how the proposed...

  1. Catalyst Deactivation: Control Relevance of Model Assumptions

    Directory of Open Access Journals (Sweden)

    Bernt Lie

    2000-10-01

    Full Text Available Two principles for describing catalyst deactivation are discussed, one based on the deactivation mechanism, the other based on the activity and catalyst age distribution. When the model is based upon activity decay, it is common to use a mean activity developed from the steady-state residence time distribution. We compare control-relevant properties of such an approach with those of a model based upon the deactivation mechanism. Using a continuous stirred tank reactor as an example, we show that the mechanistic approach and the population balance approach lead to identical models. However, common additional assumptions used for activity-based models lead to model properties that may deviate considerably from the correct one.

  2. 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...

  3. Optimal feedback scheduling of model predictive controllers

    Institute of Scientific and Technical Information of China (English)

    Pingfang ZHOU; Jianying XIE; Xiaolong DENG

    2006-01-01

    Model predictive control (MPC) could not be reliably applied to real-time control systems because its computation time is not well defined. Implemented as anytime algorithm, MPC task allows computation time to be traded for control performance, thus obtaining the predictability in time. Optimal feedback scheduling (FS-CBS) of a set of MPC tasks is presented to maximize the global control performance subject to limited processor time. Each MPC task is assigned with a constant bandwidth server (CBS), whose reserved processor time is adjusted dynamically. The constraints in the FSCBS guarantee scheduler of the total task set and stability of each component. The FS-CBS is shown robust against the variation of execution time of MPC tasks at runtime. Simulation results illustrate its effectiveness.

  4. Modeling and Control of Underwater Robotic Systems

    Energy Technology Data Exchange (ETDEWEB)

    Schjoelberg, I:

    1996-12-31

    This doctoral thesis describes modeling and control of underwater vehicle-manipulator systems. The thesis also presents a model and a control scheme for a system consisting of a surface vessel connected to an underwater robotic system by means of a slender marine structure. The equations of motion of the underwater vehicle and manipulator are described and the system kinematics and properties presented. Feedback linearization technique is applied to the system and evaluated through a simulation study. Passivity-based controllers for vehicle and manipulator control are presented. Stability of the closed loop system is proved and simulation results are given. The equation of motion for lateral motion of a cable/riser system connected to a surface vessel at the top end and to a thruster at the bottom end is described and stability analysis and simulations are presented. The equations of motion in 3 degrees of freedom of the cable/riser, surface vessel and robotic system are given. Stability analysis of the total system with PD-controllers is presented. 47 refs., 32 figs., 7 tabs.

  5. Model-Driven Development of Automation and Control Applications: Modeling and Simulation of Control Sequences

    Directory of Open Access Journals (Sweden)

    Timo Vepsäläinen

    2014-01-01

    Full Text Available The scope and responsibilities of control applications are increasing due to, for example, the emergence of industrial internet. To meet the challenge, model-driven development techniques have been in active research in the application domain. Simulations that have been traditionally used in the domain, however, have not yet been sufficiently integrated to model-driven control application development. In this paper, a model-driven development process that includes support for design-time simulations is complemented with support for simulating sequential control functions. The approach is implemented with open source tools and demonstrated by creating and simulating a control system model in closed-loop with a large and complex model of a paper industry process.

  6. Models, controls, and levels of semiotic autonomy

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, C.

    1998-12-01

    In this paper the authors consider forms of autonomy, forms of semiotic systems, and any necessary relations among them. Levels of autonomy are identified as levels of system identity, from adiabatic closure to disintegration. Forms of autonomy or closure in systems are also recognized, including physical, dynamical, functional, and semiotic. Models and controls are canonical linear and circular (closed) semiotic relations respectively. They conclude that only at higher levels of autonomy do semiotic properties become necessary. In particular, all control systems display at least a minimal degree of semiotic autonomy; and all systems with sufficiently interesting functional autonomy are semiotically related to their environments.

  7. A Modified Model Predictive Control Scheme

    Institute of Scientific and Technical Information of China (English)

    Xiao-Bing Hu; Wen-Hua Chen

    2005-01-01

    In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offline LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offline so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.

  8. Nonconvex Model Predictive Control for Commercial Refrigeration

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Larsen, Lars F.S.; Jørgensen, John Bagterp

    2013-01-01

    is to minimize the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost...... the iterations, which is more than fast enough to run in real-time. We demonstrate our method on a realistic model, with a full year simulation and 15 minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost...

  9. Modeling and Control for Magnetostrictive Hysteresis

    Institute of Scientific and Technical Information of China (English)

    MAO Jian-qin; MA Yan-hua

    2006-01-01

    To deal with the rate-dependent hysteresis presented in a magnetostrictive actuator, a new method of modeling and control is proposed. The relationship between inputs and outputs of the actuator is approximately described by a dynamic differential equation with two rate-dependent coefficients, each expressed as a polynomial of frequency. For a given frequency, the coefficients will be able to be estimated by approximating the experimental data of the outputs of the magnetostrictive actuator. Based on this model, a quasi-PID controller is designed. In the space of the coefficients and frequency, the stable domain of closed loop system with hysteresis is analyzed. The numerical simulation and experiments have born witness to the feasibility of the proposed new method.

  10. Snake Robots Modelling, Mechatronics, and Control

    CERN Document Server

    Liljebäck, Pål; Stavdahl, Øyvind; Gravdahl, Jan Tommy

    2013-01-01

    Snake Robots is a novel treatment of theoretical and practical topics related to snake robots: robotic mechanisms designed to move like biological snakes and able to operate in challenging environments in which human presence is either undesirable or impossible. Future applications of such robots include search and rescue, inspection and maintenance, and subsea operations. Locomotion in unstructured environments is a focus for this book. The text targets the disparate muddle of approaches to modelling, development and control of snake robots in current literature, giving a unified presentation of recent research results on snake robot locomotion to increase the reader’s basic understanding of these mechanisms and their motion dynamics and clarify the state of the art in the field. The book is a complete treatment of snake robotics, with topics ranging from mathematical modelling techniques, through mechatronic design and implementation, to control design strategies. The development of two snake robots is de...

  11. CFD Modeling for Mercury Control Technology

    Energy Technology Data Exchange (ETDEWEB)

    Madsen, J.I.

    2006-12-01

    Compliance with the Clean Air Mercury Rule will require implementation of dedicated mercury control solutions at a significant portion of the U.S. coal-fired utility fleet. Activated Carbon Injection (ACI) upstream of a particulate control device (ESP or baghouse) remains one of the most promising near-term mercury control technologies. The DOE/NETL field testing program has advanced the understanding of mercury control by ACI, but a persistent need remains to develop predictive models that may improve the understanding and practical implementation of this technology. This presentation describes the development of an advanced model of in-flight mercury capture based on Computational Fluid Dynamics (CFD). The model makes detailed predictions of the induct spatial distribution and residence time of sorbent, as well as predictions of mercury capture efficiency for particular sorbent flow rates and injection grid configurations. Hence, CFD enables cost efficient optimization of sorbent injection systems for mercury control to a degree that would otherwise be impractical both for new and existing plants. In this way, modeling tools may directly address the main cost component of operating an ACI system – the sorbent expense. A typical 300 MW system is expected to require between $1 and $2 million of sorbent per year, and so even modest reductions (say 10-20%) in necessary sorbent feed injection rates will quickly make any optimization effort very worthwhile. There are few existing models of mercury capture, and these typically make gross assumptions of plug gas flow, zero velocity slip between particle and gas phase, and uniform sorbent dispersion. All of these assumptions are overcome with the current model, which is based on first principles and includes mass transfer processes occurring at multiple scales, ranging from the large-scale transport in the duct to transport within the porous structure of a sorbent particle. In principle any single one of these processes

  12. Internal Model Based Active Disturbance Rejection Control

    OpenAIRE

    Pan, Jinwen; Wang, Yong

    2016-01-01

    The basic active disturbance rejection control (BADRC) algorithm with only one order higher extended state observer (ESO) proves to be robust to both internal and external disturbances. An advantage of BADRC is that in many applications it can achieve high disturbance attenuation level without requiring a detailed model of the plant or disturbance. However, this can be regarded as a disadvantage when the disturbance characteristic is known since the BADRC algorithm cannot exploit such informa...

  13. Validation of Air Traffic Controller Workload Models

    Science.gov (United States)

    1979-09-01

    SAR) tapes dtirinq the data reduc- tion phase of the project. Kentron International Limited provided the software support for the oroject. This included... ETABS ) or to revised traffic control procedures. The models also can be used to verify productivity benefits after new configurations have been...col- lected and processed manually. A preliminary compari- son has been made between standard NAS Stage A and ETABS operations at Miami. 1.2

  14. Model Based Control of Refrigeration Systems

    DEFF Research Database (Denmark)

    Larsen, Lars Finn Sloth

    of the supermarket refrigeration systems therefore greatly relies on a human operator to detect and accommodate failures, and to optimize system performance under varying operational condition. Today these functions are maintained by monitoring centres located all over the world. Initiated by the growing need...... for automation of these procedures, that is to incorporate some "intelligence" in the control system, this project was started up. The main emphasis of this work has been on model based methods for system optimizing control in supermarket refrigeration systems. The idea of implementing a system optimizing.......e. by degrading the performance. The method has been successfully applied on a test frigeration system for minimization of the power consumption; the hereby gained experimental results will be presented. The present control structure in a supermarket refrigeration system is distributed, which means...

  15. Nitrogen Controls on Climate Model Evapotranspiration.

    Science.gov (United States)

    Dickinson, Robert E.; Berry, Joseph A.; Bonan, Gordon B.; Collatz, G. James; Field, Christopher B.; Fung, Inez Y.; Goulden, Michael; Hoffmann, William A.; Jackson, Robert B.; Myneni, Ranga; Sellers, Piers J.; Shaikh, Muhammad

    2002-02-01

    Most evapotranspiration over land occurs through vegetation. The fraction of net radiation balanced by evapotranspiration depends on stomatal controls. Stomates transpire water for the leaf to assimilate carbon, depending on the canopy carbon demand, and on root uptake, if it is limiting. Canopy carbon demand in turn depends on the balancing between visible photon-driven and enzyme-driven steps in the leaf carbon physiology. The enzyme-driven component is here represented by a Rubisco-related nitrogen reservoir that interacts with plant-soil nitrogen cycling and other components of a climate model. Previous canopy carbon models included in GCMs have assumed either fixed leaf nitrogen, that is, prescribed photosynthetic capacities, or an optimization between leaf nitrogen and light levels so that in either case stomatal conductance varied only with light levels and temperature.A nitrogen model is coupled to a previously derived but here modified carbon model and includes, besides the enzyme reservoir, additional plant stores for leaf structure and roots. It also includes organic and mineral reservoirs in the soil; the latter are generated, exchanged, and lost by biological fixation, deposition and fertilization, mineralization, nitrification, root uptake, denitrification, and leaching. The root nutrient uptake model is a novel and simple, but rigorous, treatment of soil transport and root physiological uptake. The other soil components are largely derived from previously published parameterizations and global budget constraints.The feasibility of applying the derived biogeochemical cycling model to climate model calculations of evapotranspiration is demonstrated through its incorporation in the Biosphere-Atmosphere Transfer Scheme land model and a 17-yr Atmospheric Model Inter comparison Project II integration with the NCAR CCM3 GCM. The derived global budgets show land net primary production (NPP), fine root carbon, and various aspects of the nitrogen cycling are

  16. Performance and robustness of hybrid model predictive control for controllable dampers in building models

    Science.gov (United States)

    Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

    2016-04-01

    A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

  17. PI controller based model reference adaptive control for nonlinear ...

    African Journals Online (AJOL)

    user

    which can deal effectively for real-time online computer control. The NN of the ..... applications such as machine tools, industrial robot control, position control, and other engineering practices. .... Transactions on Mechatronics, vol.1, no.2, pp.

  18. Modelling the control of interceptive actions.

    Science.gov (United States)

    Beek, P J; Dessing, J C; Peper, C E; Bullock, D

    2003-09-29

    In recent years, several phenomenological dynamical models have been formulated that describe how perceptual variables are incorporated in the control of motor variables. We call these short-route models as they do not address how perception-action patterns might be constrained by the dynamical properties of the sensory, neural and musculoskeletal subsystems of the human action system. As an alternative, we advocate a long-route modelling approach in which the dynamics of these subsystems are explicitly addressed and integrated to reproduce interceptive actions. The approach is exemplified through a discussion of a recently developed model for interceptive actions consisting of a neural network architecture for the online generation of motor outflow commands, based on time-to-contact information and information about the relative positions and velocities of hand and ball. This network is shown to be consistent with both behavioural and neurophysiological data. Finally, some problems are discussed with regard to the question of how the motor outflow commands (i.e. the intended movement) might be modulated in view of the musculoskeletal dynamics.

  19. Control mechanisms for a nonlinear model of international relations

    Energy Technology Data Exchange (ETDEWEB)

    Pentek, A.; Kadtke, J. [Univ. of California, San Diego, La Jolla, CA (United States). Inst. for Pure and Applied Physical Sciences; Lenhart, S. [Univ. of Tennessee, Knoxville, TN (United States). Mathematics Dept.; Protopopescu, V. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.

    1997-07-15

    Some issues of control in complex dynamical systems are considered. The authors discuss two control mechanisms, namely: a short range, reactive control based on the chaos control idea and a long-term strategic control based on an optimal control algorithm. They apply these control ideas to simple examples in a discrete nonlinear model of a multi-nation arms race.

  20. Modeling and control of dialysis systems

    CERN Document Server

    2013-01-01

    This book is the first text of its kind that presents both the traditional and the modern aspects of dialysis modeling and control in a clear, insightful and highly comprehensive writing style. It provides an in-depth analysis of the mathematical models and algorithms, and demonstrates their applications in real world problems of significant complexity. It explains concepts in a clear, matter-of-fact style. The material of this book will be useful to advanced undergraduate and graduate biomedical engineering students. Also, researchers and practitioners in the field of dialysis, control systems, soft computing will benefit from it. In order to make the reader aware of the applied side of the subject, the book includes:       Chapter openers with a chapter outline, chapter objectives, key terms list, and abstract.       Solved numerical examples to illustrate the application of a particular concept, and also to encourage good problem-solving skills.       More than 1000 questions to give the rea...

  1. Unified power flow controller: Modeling, stability analysis, control strategy and control system design

    Science.gov (United States)

    Sreenivasachar, Kannan

    2001-07-01

    Unified power flow controller (UPFC) has been the most versatile Flexible AC Transmission System (FACTS) device due to its ability to control real and reactive power flow on transmission lines while controlling the voltage of the bus to which it is connected. UPFC being a multi-variable power system controller it is necessary to analyze its effect on power system operation. To study the performance of the UPFC in damping power oscillations using PSCAD-EMTDC software, a de-coupled control system has been designed for the shunt inverter to control the UPFC bus voltage and the DC link capacitor voltage. The series inverter of a UPFC controls the real power flow in the transmission line. One problem associated with using a high gain PI controller (used to achieve fast control of transmission line real power flow) for the series inverter of a UPFC to control the real power flow in a transmission line is the presence of low damping. This problem is solved in this research by using a fuzzy controller. A method to model a fuzzy controller in PSCAD-EMTDC software has also been described. Further, in order to facilitate proper operation between the series and the shunt inverter control system, a new real power coordination controller has been developed and its performance was evaluated. The other problem concerning the operation of a UPFC is with respect to transmission line reactive power flow control. Step changes to transmission line reactive power references have significant impact on the UPFC bus voltage. To reduce the adverse effect of step changes in transmission line reactive power references on the UPFC bus voltage, a new reactive power coordination controller has been designed. Transient response studies have been conducted using PSCAD-EMTDC software to show the improvement in power oscillation damping with UPFC. These simulations include the real and reactive power coordination controllers. Finally, a new control strategy has been proposed for UPFC. In this

  2. Modeling resistance to genetic control of insects.

    Science.gov (United States)

    Alphey, Nina; Bonsall, Michael B; Alphey, Luke

    2011-02-07

    The sterile insect technique is an area-wide pest control method that reduces pest populations by releasing mass-reared sterile insects which compete for mates with wild insects. Modern molecular tools have created possibilities for improving and extending the sterile insect technique. As with any new insect control method, questions arise about potential resistance. Genetic RIDL(®)(1) (Release of Insects carrying a Dominant Lethal) technology is a proposed modification of the technique, releasing insects that are homozygous for a repressible dominant lethal genetic construct rather than being sterilized by irradiation. Hypothetical resistance to the lethal mechanism is a potential threat to RIDL strategies' effectiveness. Using population genetic and population dynamic models, we assess the circumstances under which monogenic biochemically based resistance could have a significant impact on the effectiveness of releases for population control. We assume that released insects would be homozygous susceptible to the lethal genetic construct and therefore releases would have a built-in element of resistance dilution. We find that this effect could prevent or limit the spread of resistance to RIDL constructs; the outcomes are subject to competing selective forces deriving from the fitness properties of resistance and the release ratio. Resistance that is spreading and capable of having a significant detrimental impact on population reduction is identifiable, signaling in advance a need for mitigating action.

  3. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  4. Modeling hormonal control of cambium proliferation.

    Science.gov (United States)

    Oles, Vladyslav; Panchenko, Alexander; Smertenko, Andrei

    2017-01-01

    Rise of atmospheric CO2 is one of the main causes of global warming. Catastrophic climate change can be avoided by reducing emissions and increasing sequestration of CO2. Trees are known to sequester CO2 during photosynthesis, and then store it as wood biomass. Thus, breeding of trees with higher wood yield would mitigate global warming as well as augment production of renewable construction materials, energy, and industrial feedstock. Wood is made of cellulose-rich xylem cells produced through proliferation of a specialized stem cell niche called cambium. Importance of cambium in xylem cells production makes it an ideal target for the tree breeding programs; however our knowledge about control of cambium proliferation remains limited. The morphology and regulation of cambium are different from those of stem cell niches that control axial growth. For this reason, translating the knowledge about axial growth to radial growth has limited use. Furthermore, genetic approaches cannot be easily applied because overlaying tissues conceal cambium from direct observation and complicate identification of mutants. To overcome the paucity of experimental tools in cambium biology, we constructed a Boolean network CARENET (CAmbium REgulation gene NETwork) for modelling cambium activity, which includes the key transcription factors WOX4 and HD-ZIP III as well as their potential regulators. Our simulations predict that: (1) auxin, cytokinin, gibberellin, and brassinosteroids act cooperatively in promoting transcription of WOX4 and HD-ZIP III; (2) auxin and cytokinin pathways negatively regulate each other; (3) hormonal pathways act redundantly in sustaining cambium activity; (4) individual cambium cells can have diverse molecular identities. CARENET can be extended to include components of other signalling pathways and be integrated with models of xylem and phloem differentiation. Such extended models would facilitate breeding trees with higher wood yield.

  5. Modeling hormonal control of cambium proliferation

    Science.gov (United States)

    Oles, Vladyslav; Panchenko, Alexander

    2017-01-01

    Rise of atmospheric CO2 is one of the main causes of global warming. Catastrophic climate change can be avoided by reducing emissions and increasing sequestration of CO2. Trees are known to sequester CO2 during photosynthesis, and then store it as wood biomass. Thus, breeding of trees with higher wood yield would mitigate global warming as well as augment production of renewable construction materials, energy, and industrial feedstock. Wood is made of cellulose-rich xylem cells produced through proliferation of a specialized stem cell niche called cambium. Importance of cambium in xylem cells production makes it an ideal target for the tree breeding programs; however our knowledge about control of cambium proliferation remains limited. The morphology and regulation of cambium are different from those of stem cell niches that control axial growth. For this reason, translating the knowledge about axial growth to radial growth has limited use. Furthermore, genetic approaches cannot be easily applied because overlaying tissues conceal cambium from direct observation and complicate identification of mutants. To overcome the paucity of experimental tools in cambium biology, we constructed a Boolean network CARENET (CAmbium REgulation gene NETwork) for modelling cambium activity, which includes the key transcription factors WOX4 and HD-ZIP III as well as their potential regulators. Our simulations predict that: (1) auxin, cytokinin, gibberellin, and brassinosteroids act cooperatively in promoting transcription of WOX4 and HD-ZIP III; (2) auxin and cytokinin pathways negatively regulate each other; (3) hormonal pathways act redundantly in sustaining cambium activity; (4) individual cambium cells can have diverse molecular identities. CARENET can be extended to include components of other signalling pathways and be integrated with models of xylem and phloem differentiation. Such extended models would facilitate breeding trees with higher wood yield. PMID:28187161

  6. Adaptive Control and Synchronization of the Shallow Water Model

    Directory of Open Access Journals (Sweden)

    P. Sangapate

    2012-01-01

    Full Text Available The shallow water model is one of the important models in dynamical systems. This paper investigates the adaptive chaos control and synchronization of the shallow water model. First, adaptive control laws are designed to stabilize the shallow water model. Then adaptive control laws are derived to chaos synchronization of the shallow water model. The sufficient conditions for the adaptive control and synchronization have been analyzed theoretically, and the results are proved using a Barbalat's Lemma.

  7. Modelling strategies for controlling SARS outbreaks.

    Science.gov (United States)

    Gumel, Abba B.; Ruan, Shigui; Day, Troy; Watmough, James; Brauer, Fred; van den Driessche, P.; Gabrielson, Dave; Bowman, Chris; Alexander, Murray E.; Ardal, Sten; Wu, Jianhong; Sahai, Beni M.

    2004-01-01

    Severe acute respiratory syndrome (SARS), a new, highly contagious, viral disease, emerged in China late in 2002 and quickly spread to 32 countries and regions causing in excess of 774 deaths and 8098 infections worldwide. In the absence of a rapid diagnostic test, therapy or vaccine, isolation of individuals diagnosed with SARS and quarantine of individuals feared exposed to SARS virus were used to control the spread of infection. We examine mathematically the impact of isolation and quarantine on the control of SARS during the outbreaks in Toronto, Hong Kong, Singapore and Beijing using a deterministic model that closely mimics the data for cumulative infected cases and SARS-related deaths in the first three regions but not in Beijing until mid-April, when China started to report data more accurately. The results reveal that achieving a reduction in the contact rate between susceptible and diseased individuals by isolating the latter is a critically important strategy that can control SARS outbreaks with or without quarantine. An optimal isolation programme entails timely implementation under stringent hygienic precautions defined by a critical threshold value. Values below this threshold lead to control, but those above are associated with the incidence of new community outbreaks or nosocomial infections, a known cause for the spread of SARS in each region. Allocation of resources to implement optimal isolation is more effective than to implement sub-optimal isolation and quarantine together. A community-wide eradication of SARS is feasible if optimal isolation is combined with a highly effective screening programme at the points of entry. PMID:15539347

  8. On modeling and controlling intelligent systems

    Energy Technology Data Exchange (ETDEWEB)

    Dress, W.B.

    1993-11-01

    The aim of this paper is to show how certain diverse and advanced techniques of information processing and system theory might be integrated into a model of an intelligent, complex entity capable of materially enhancing an advanced information management system. To this end, we first examine the notion of intelligence and ask whether a semblance thereof can arise in a system consisting of ensembles of finite-state automata. Our goal is to find a functional model of intelligence in an information-management setting that can be used as a tool. The purpose of this tool is to allow us to create systems of increasing complexity and utility, eventually reaching the goal of an intelligent information management system that provides and anticipates needed data and information. We base our attempt on the ideas of general system theory where the four topics of system identification, modeling, optimization, and control provide the theoretical framework for constructing a complex system that will be capable of interacting with complex systems in the real world. These four key topics are discussed within the purview of cellular automata, neural networks, and evolutionary programming. This is a report of ongoing work, and not yet a success story of a synthetic intelligent system.

  9. On modeling and controlling intelligent systems

    Energy Technology Data Exchange (ETDEWEB)

    Dress, W.B.

    1993-11-01

    The aim of this paper is to show how certain diverse and advanced techniques of information processing and system theory might be integrated into a model of an intelligent, complex entity capable of materially enhancing an advanced information management system. To this end, we first examine the notion of intelligence and ask whether a semblance thereof can arise in a system consisting of ensembles of finite-state automata. Our goal is to find a functional model of intelligence in an information-management setting that can be used as a tool. The purpose of this tool is to allow us to create systems of increasing complexity and utility, eventually reaching the goal of an intelligent information management system that provides and anticipates needed data and information. We base our attempt on the ideas of general system theory where the four topics of system identification, modeling, optimization, and control provide the theoretical framework for constructing a complex system that will be capable of interacting with complex systems in the real world. These four key topics are discussed within the purview of cellular automata, neural networks, and evolutionary programming. This is a report of ongoing work, and not yet a success story of a synthetic intelligent system.

  10. Modelling and control for position-controlled modular robot manipulators

    OpenAIRE

    Shao, Zilong; Zheng, Gang; Efimov, Denis; Perruquetti, Wilfrid

    2015-01-01

    International audience; Modular Robot Manipulators are user-configurable manipulators which provide rapid design and inexpensive implementation. To be easy-use, smart actuators embedded with position input and position feedback controller are adopted, these local controllers render the manipulators position controlled, but also result in limited performance and precision. This paper targets the case that the built-in controller does not provide desirable precision for set-point regulation. Fi...

  11. Application of dimensional analysis in systems modeling and control design

    CERN Document Server

    Balaguer, Pedro

    2013-01-01

    Dimensional analysis is an engineering tool that is widely applied to numerous engineering problems, but has only recently been applied to control theory and problems such as identification and model reduction, robust control, adaptive control, and PID control. Application of Dimensional Analysis in Systems Modeling and Control Design provides an introduction to the fundamentals of dimensional analysis for control engineers, and shows how they can exploit the benefits of the technique to theoretical and practical control problems.

  12. An Industrial Model Based Disturbance Feedback Control Scheme

    DEFF Research Database (Denmark)

    Kawai, Fukiko; Nakazawa, Chikashi; Vinther, Kasper

    2014-01-01

    This paper presents a model based disturbance feedback control scheme. Industrial process systems have been traditionally controlled by using relay and PID controller. However these controllers are affected by disturbances and model errors and these effects degrade control performance. The authors...... propose a new control method that can decrease the negative impact of disturbance and model errors. The control method is motivated by industrial practice by Fuji Electric. Simulation tests are examined with a conventional PID controller and the disturbance feedback control. The simulation results...

  13. Perti Net-Based Workflow Access Control Model

    Institute of Scientific and Technical Information of China (English)

    陈卓; 骆婷; 石磊; 洪帆

    2004-01-01

    Access control is an important protection mechanism for information systems. This paper shows how to make access control in workflow system. We give a workflow access control model (WACM) based on several current access control models. The model supports roles assignment and dynamic authorization. The paper defines the workflow using Petri net. It firstly gives the definition and description of the workflow, and then analyzes the architecture of the workflow access control model (WACM). Finally, an example of an e-commerce workflow access control model is discussed in detail.

  14. Modeling and control in the biomedical sciences

    CERN Document Server

    Banks, H T

    1975-01-01

    These notes are based on (i) a series of lectures that I gave at the 14th Biennial Seminar of the Canadian Mathematical Congress held at the University of Western Ontario August 12-24, 1973 and (li) some of my lectures in a modeling course that I have cotaught in the Division of Bio-Medical Sciences at Brown during the past several years. An earlier version of these notes appeared in the Center for Dynamical Systems Lectures Notes series (CDS LN 73-1, November 1973). I have in this revised and extended version of those earlier notes incorporated a number of changes based both on classroom experience and on my research efforts with several colleagues during the intervening period. The narrow viewpoint of the present notes (use of optimization and control theory in biomedical problems) reflects more the scope of the CMC lectures given in August, 1973 than the scope of my own interests. Indeed, my real interests have included the modeling process itself as well as the contributions made by investiga­ tors who e...

  15. 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.

  16. Distributional Analysis for Model Predictive Deferrable Load Control

    OpenAIRE

    Chen, Niangjun; Gan, Lingwen; Low, Steven H.; Wierman, Adam

    2014-01-01

    Deferrable load control is essential for handling the uncertainties associated with the increasing penetration of renewable generation. Model predictive control has emerged as an effective approach for deferrable load control, and has received considerable attention. In particular, previous work has analyzed the average-case performance of model predictive deferrable load control. However, to this point, distributional analysis of model predictive deferrable load control has been elusive. In ...

  17. Autonomous underwater vehicles modeling, control design and simulation

    CERN Document Server

    Wadoo, Sabiha

    2010-01-01

    Underwater vehicles present some difficult and very particular control system design problems. These are often the result of nonlinear dynamics and uncertain models, as well as the presence of sometimes unforeseeable environmental disturbances that are difficult to measure or estimate. Autonomous Underwater Vehicles: Modeling, Control Design, and Simulation outlines a novel approach to help readers develop models to simulate feedback controllers for motion planning and design. The book combines useful information on both kinematic and dynamic nonlinear feedback control models, providing simula

  18. An optimal promotion cost control model for a markovian manpower ...

    African Journals Online (AJOL)

    An optimal promotion cost control model for a markovian manpower system. ... Log in or Register to get access to full text downloads. ... A theory concerning the existence of an optimal promotion control strategy for controlling a Markovian ...

  19. 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 cont

  20. 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

  1. Towards automatic model based controller design for reconfigurable plants

    DEFF Research Database (Denmark)

    Michelsen, Axel Gottlieb; Stoustrup, Jakob; Izadi-Zamanabadi, Roozbeh

    2008-01-01

    This paper introduces model-based Plug and Play Process Control, a novel concept for process control, which allows a model-based control system to be reconfigured when a sensor or an actuator is plugged into a controlled process. The work reported in this paper focuses on composing a monolithic m...

  2. The Dynamic Model of Allocation Control in Venture Capital

    Institute of Scientific and Technical Information of China (English)

    TIAN Zeng-rui

    2008-01-01

    The allocation of control and stock in venture capital is the key point of the venture capital project. This paper develops a dynamic model of control and stock and profoundly analyses how to allocate the control between the entrepreneur and the venture capitalist. The model reveals the relationship of control and stock's structure, the time and the degree of imparting the control to the entrepreneur or the venture capitalist, the condition of retracting the control and compensation accordingly.

  3. Modeling and Control of Active Suspensions for MDOF Vehicle

    Institute of Scientific and Technical Information of China (English)

    李克强; 郑四发; 杨殿阁; 连小珉; 永井正夫

    2003-01-01

    The conventional method for analyzing active suspension control for a vehicle is only to analyze aquarter or half car with a lower order degree-of freedom (DOF) model, but such models do not actually modelpractical applications. Accurate models of a suspension control system require a multi-degree-of-freedom(MDOF) vehicle model with a detailed model of the controller. An MDOF model was developed including theinfluence of factors such as the engine, the seats, and the passengers to describe vehicle motion using areduced order model of the controller designed by using the H∞ control method. The control systemperformance has been investigated by comparing the H∞ controller with a linear quadratic (LQ) controller.

  4. Modelling and Control Design of Unified Power Flow Controller for Various Control Strategies

    Directory of Open Access Journals (Sweden)

    T. Nireekshana

    2010-11-01

    Full Text Available Unified Power Flow Controller (UPFC is used to control the power flow in the transmission systems by controlling the impedance, voltage magnitude and phase angle. This controller offers advantages in terms of static and dynamic operation of the power system. It also brings in new challenges in power electronics and power system design. The basic structure of the UPFC consists of two voltage source inverter (VSI; where one converter is connected in parallel to the transmission line while the other is in series with the transmission line. The aim of the paper is to develop a control strategy for UPFC, modeling UPFC using MATLAB/SIMULINK and to analyze the control strategy to use the series voltage injection and shunt current injection for UPFC control. To simplify the design procedure we carry out the design for the series and shunt branches separately.In each case, a simple equivalent circuit represents the external system. The design has to be validated when the various subsystems are integrated.

  5. Catalytic cracking models developed for predictive control purposes

    Directory of Open Access Journals (Sweden)

    Dag Ljungqvist

    1993-04-01

    Full Text Available The paper deals with state-space modeling issues in the context of model-predictive control, with application to catalytic cracking. Emphasis is placed on model establishment, verification and online adjustment. Both the Fluid Catalytic Cracking (FCC and the Residual Catalytic Cracking (RCC units are discussed. Catalytic cracking units involve complex interactive processes which are difficult to operate and control in an economically optimal way. The strong nonlinearities of the FCC process mean that the control calculation should be based on a nonlinear model with the relevant constraints included. However, the model can be simple compared to the complexity of the catalytic cracking plant. Model validity is ensured by a robust online model adjustment strategy. Model-predictive control schemes based on linear convolution models have been successfully applied to the supervisory dynamic control of catalytic cracking units, and the control can be further improved by the SSPC scheme.

  6. Finite element models applied in active structural acoustic control

    NARCIS (Netherlands)

    Oude Nijhuis, Marco H.H.; Boer, de André; Rao, Vittal S.

    2002-01-01

    This paper discusses the modeling of systems for active structural acoustic control. The finite element method is applied to model structures including the dynamics of piezoelectric sensors and actuators. A model reduction technique is presented to make the finite element model suitable for controll

  7. 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 microsc

  8. 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 microsc

  9. Model-based dynamic control and optimization of gas networks

    Energy Technology Data Exchange (ETDEWEB)

    Hofsten, Kai

    2001-07-01

    This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum

  10. Automatic control of finite element models for temperature-controlled radiofrequency ablation

    Directory of Open Access Journals (Sweden)

    Haemmerich Dieter

    2005-07-01

    Full Text Available Abstract Background The finite element method (FEM has been used to simulate cardiac and hepatic radiofrequency (RF ablation. The FEM allows modeling of complex geometries that cannot be solved by analytical methods or finite difference models. In both hepatic and cardiac RF ablation a common control mode is temperature-controlled mode. Commercial FEM packages don't support automating temperature control. Most researchers manually control the applied power by trial and error to keep the tip temperature of the electrodes constant. Methods We implemented a PI controller in a control program written in C++. The program checks the tip temperature after each step and controls the applied voltage to keep temperature constant. We created a closed loop system consisting of a FEM model and the software controlling the applied voltage. The control parameters for the controller were optimized using a closed loop system simulation. Results We present results of a temperature controlled 3-D FEM model of a RITA model 30 electrode. The control software effectively controlled applied voltage in the FEM model to obtain, and keep electrodes at target temperature of 100°C. The closed loop system simulation output closely correlated with the FEM model, and allowed us to optimize control parameters. Discussion The closed loop control of the FEM model allowed us to implement temperature controlled RF ablation with minimal user input.

  11. Vehicle active steering control research based on two-DOF robust internal model control

    Science.gov (United States)

    Wu, Jian; Liu, Yahui; Wang, Fengbo; Bao, Chunjiang; Sun, Qun; Zhao, Youqun

    2016-07-01

    Because of vehicle's external disturbances and model uncertainties, robust control algorithms have obtained popularity in vehicle stability control. The robust control usually gives up performance in order to guarantee the robustness of the control algorithm, therefore an improved robust internal model control(IMC) algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness. The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties. In order to separate the design process of model tracking from the robustness design process, the improved 2 degree of freedom(DOF) robust internal model controller structure is given from the standard Youla parameterization. Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm, on the basis of a nonlinear vehicle simulation model with a magic tyre model. Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance, which can enhance the vehicle stability and handling, regardless of variations of the vehicle model parameters and the external crosswind interferences. Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

  12. Model based control of dynamic atomic force microscope

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Chibum [Department of Mechanical System Design Engineering, Seoul National University of Science and Technology, Seoul 139-743 (Korea, Republic of); Salapaka, Srinivasa M., E-mail: salapaka@illinois.edu [Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 (United States)

    2015-04-15

    A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H{sub ∞} control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.

  13. Model based control of dynamic atomic force microscope.

    Science.gov (United States)

    Lee, Chibum; Salapaka, Srinivasa M

    2015-04-01

    A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.

  14. Modelling of command and control agility

    CSIR Research Space (South Africa)

    Oosthuizen, R

    2014-06-01

    Full Text Available Different systems engineering techniques and approaches are applied to design and develop Command and Control solutions for complex problems. Command and Control is a complex sociotechnical system where human commanders make sense of a situation...

  15. Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

    Institute of Scientific and Technical Information of China (English)

    Hongli L(U); Lei JIA; Shulan KONG; Zhaosheng ZHANG

    2007-01-01

    In heating,ventilating and air-conditioning(HVAC)systems,there exist severe nonlinearity,time-varying nature,disturbances and uncertainties.A new predictive functional control based on Takagi-Sugeno(T-S)fuzzy model was proposed to control HVAC systems.The T-S fuzzy model of stabilized controlled process was obtained using the least squares method,then on the basis of global linear predictive model from T-S fuzzy model,the process was controlled by the predictive functional controller.Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model.Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness.Compared with the conventional PID controller,this control strategy has the advantages of less overshoot and shorter setting time,etc.

  16. Fuzzy Control Strategies in Human Operator and Sport Modeling

    CERN Document Server

    Ivancevic, Tijana T; Markovic, Sasa

    2009-01-01

    The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal control. As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.

  17. Model-based analysis of control performance in sewer systems

    DEFF Research Database (Denmark)

    Mollerup, Ane Høyer; Mauricio Iglesias, Miguel; Johansen, N.B.;

    2012-01-01

    Design and assessment of control in wastewater systems has to be tackled at all levels, including supervisory and regulatory level. We present here an integrated approach to assessment of control in sewer systems based on modelling and the use of process control tools to assess the controllability...... of the process. A case study of a subcatchment area in Copenhagen (Denmark) is used to illustrate the combined approach in modelling of the system and control assessment....

  18. Humanoid Walking Robot: Modeling, Inverse Dynamics, and Gain Scheduling Control

    OpenAIRE

    Elvedin Kljuno; Williams, Robert L.

    2010-01-01

    This article presents reference-model-based control design for a 10 degree-of-freedom bipedal walking robot, using nonlinear gain scheduling. The main goal is to show concentrated mass models can be used for prediction of the required joint torques for a bipedal walking robot. Relatively complicated architecture, high DOF, and balancing requirements make the control task of these robots difficult. Although linear control techniques can be used to control bipedal robots, nonlinear control is n...

  19. Model based control charts in stage 1 quality control

    NARCIS (Netherlands)

    A.J. Koning (Alex)

    1999-01-01

    textabstractIn this paper a general method of constructing control charts for preliminary analysis of individual observations is presented, which is based on recursive score residuals. A simulation study shows that certain implementations of these charts are highly effective in detecting assignable

  20. Modelling and Internal Fuzzy Model Power Control of a Francis Water Turbine

    OpenAIRE

    Klemen Nagode; Igor Škrjanc

    2014-01-01

    This paper presents dynamic modelling of a Francis turbine with a surge tank and the control of a hydro power plant (HPP). Non-linear and linear models include technical parameters and show high similarity to measurement data. Turbine power control with an internal model control (IMC) is proposed, based on a turbine fuzzy model. Considering appropriate control responses in the entire area of turbine power, the model parameters of the process are determined from a fuzzy model, which are furthe...

  1. 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.

  2. Modeling And Position Control Of Scara Type 3D Printer

    Directory of Open Access Journals (Sweden)

    Ahmet Saygamp305n Ogulmuamp351

    2015-08-01

    Full Text Available In this work a scara robot type 3D printer system is dynamically modeled and position control of the system is realized. For this aim computer aided design model of three degrees of freedom robotic system is created using SolidWorks program then obtained model is exported to MATLABSimMechanics software for position control. Also mathematical model of servo motors used in robotic 3D printer system is included in control methodology to design proportional controllers. Uncontrolled and controlled position results are simulated and given in the form of the graphics.

  3. Model-based Control of a Bottom Fired Marine Boiler

    DEFF Research Database (Denmark)

    Solberg, Brian; Karstensen, Claus M. S.; Andersen, Palle;

    This paper focuses on applying model based MIMO control to minimize variations in water level for a specific boiler type. A first principles model is put up. The model is linearized and an LQG controller is designed. Furthermore the benefit of using a steam °ow measurement is compared to a strategy...... relying on estimates of the disturbance. Preliminary tests at the boiler system show that the designed controller is able to control the boiler process. Furthermore it can be concluded that relying on estimates of the steam flow in the control strategy does not decrease the controller performance...

  4. Model-based Control of a Bottom Fired Marine Boiler

    DEFF Research Database (Denmark)

    Solberg, Brian; Karstensen, Claus M. S.; Andersen, Palle;

    2005-01-01

    This paper focuses on applying model based MIMO control to minimize variations in water level for a specific boiler type. A first principles model is put up. The model is linearized and an LQG controller is designed. Furthermore the benefit of using a steam °ow measurement is compared to a strategy...... relying on estimates of the disturbance. Preliminary tests at the boiler system show that the designed controller is able to control the boiler process. Furthermore it can be concluded that relying on estimates of the steam flow in the control strategy does not decrease the controller performance...

  5. Creation and Control of an Internet Controlled Mars Rover Model

    Science.gov (United States)

    Angeli, Gabor; Walker, C.

    2007-12-01

    The latest project in a longstanding correspondence between NOAO Tucson and the CADIAS center in La Serena, Chile focuses on Mars and Mars exploration. The objective was to provide a user-friendly yet moderately versatile imitation of the Spirit and Opportunity MARS rovers to be used by grade school students. In addition to basic motion, the rover that was built is able to take color photographs from a rotating camera, and avoid harmful collisions or structural stress via 'bumper' sensors on each of the wheels. The rover is intended to be used remotely via the Internet, and controlled locally via wireless radio. The focus of the project was to create a system that is stable, versatile, and user friendly. The majority of the system was coded in Java, including the micro controller, providing stability and a reliable internet protocol. A partial implementation of Scheme was used as a scripting language, providing an abstraction in the means of communication and control of the robot and allowing for a level of versatility in the range of commands available to the rover and the ease of tweaking those commands. A graphical user interface was implemented to provide a safe means of controlling the rover, creating an 'action queue' of safe commands to be sent as a block to the rover. We hope the project will provide a useful education tool for students in Chile, and potentially in the future students in Tucson as well. Angeli's research was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation through Scientific Program Order No. 3 (AST-0243875) of the Cooperative Agreement No. AST-0132798 between the Association of Universities for Research in Astronomy (AURA) and the NSF.

  6. Dynamic Model Identification for Ultrasonic Motor Frequency-Speed Control

    Institute of Scientific and Technical Information of China (English)

    Shi Jingzhuo; Song Le

    2015-01-01

    The mathematical model of ultrasonic motor (USM ) is the foundation of the motor high performance control .Considering the motor speed control requirements ,the USM control model identification is established with frequency as the independent variable .The frequency-speed control model of USM system is developed ,thus laying foundation for the motor high performance control .The least square method and the extended least square method are used to identify the model .By comparing the results of the identification and measurement ,and fitting the time-varying parameters of the model ,one can show that the model obtained by using the extended least square method is reasonable and possesses high accuracy .Finally ,the frequency-speed control model of USM contains the nonlinear information .

  7. Approximately bisimilar symbolic models for nonlinear control systems

    CERN Document Server

    Pola, Giordano; Tabuada, Paulo

    2007-01-01

    Control systems are usually modeled by differential equations describing how physical phenomena can be influenced by certain control parameters or inputs. Although these models are very powerful when dealing with physical phenomena, they are less suitable to describe software and hardware interfacing the physical world. For this reason there is a growing interest in describing control systems through symbolic models that are abstract descriptions of the continuous dynamics, where each ``symbol'' corresponds to an ``aggregate'' of states in the continuous model. Since these symbolic models are of the same nature of the models used in computer science to describe software and hardware, they provide a unified language to study problems of control in which software and hardware interact with the physical world. Furthermore the use of symbolic models enables one to leverage techniques from supervisory control and algorithms from game theory for controller synthesis purposes. In this paper we show that every increm...

  8. Experience-based model predictive control using reinforcement learning

    NARCIS (Netherlands)

    Negenborn, R.R.; De Schutter, B.; Wiering, M.A.; Hellendoorn, J.

    2004-01-01

    Model predictive control (MPC) is becoming an increasingly popular method to select actions for controlling dynamic systems. TraditionallyMPC uses a model of the system to be controlled and a performance function to characterize the desired behavior of the system. The MPC agent finds actions over a

  9. Model Based Monitoring and Control of Chemical and Biochemical Processes

    DEFF Research Database (Denmark)

    Huusom, Jakob Kjøbsted

    This presentation will give an overview of the work performed at the department of Chemical and Biochemical Engineering related to process control. A research vision is formulated and related to a number of active projects at the department. In more detail a project describing model estimation...... and controller tuning in Model Predictive Control application is discussed....

  10. Attributes Enhanced Role-Based Access Control Model

    DEFF Research Database (Denmark)

    Mahmood Rajpoot, Qasim; Jensen, Christian D.; Krishnan, Ram

    2015-01-01

    as an important area of research. In this paper, we propose an access control model that combines the two models in a novel way in order to unify their benefits. Our approach provides a fine-grained access control mechanism that not only takes contextual information into account while making the access control...

  11. 76 FR 9265 - Special Conditions: Gulfstream Model GVI Airplane; Electronic Flight Control System: Control...

    Science.gov (United States)

    2011-02-17

    ... Model GVI Airplane; Electronic Flight Control System: Control Surface Position Awareness AGENCY: Federal... transport category airplanes. These design features include an electronic flight control system. The... The GVI has an electronic flight control system and no direct coupling from the cockpit controller to...

  12. Humanoid Robot Balance Control using the Spherical Inverted Pendulum Model

    Directory of Open Access Journals (Sweden)

    Ahmed eElhasairi

    2015-10-01

    Full Text Available Human beings are highly efficient in maintaining standing balance under the influence of different perturbations. However, biped humanoid robots are far from exhibiting similar skills. This is mainly due to the limitations in the current control and modelling techniques used in humanoid robots. Even though approaches using the Linear Inverted Pendulum Model and the Preview Control schemes have shown improved results, they still suffer from shortcomings in the overall generated motion. We propose here a model and control approach that aims to overcome the limiting assumptions in the LIPM models, through using the ankle joint variables in modelling and control of the standing balance of the humanoid robot.

  13. Characteristic modeling and the control of flexible structure

    Institute of Scientific and Technical Information of China (English)

    吴宏鑫; 刘一武; 刘忠汉; 解永春

    2001-01-01

    Appropriate modeling for a controlled plant has been a remarkable problem in the control field. A new modeling theory, i.e. characteristic modeling, is roundly demonstrated. It is deduced in detail that a general linear constant high_order system can be equivalently described with a two_order time_varying difference equation. The application of the characteristic modeling method to the control of flexible structure is also introduced. Especially, as an example, the Hubble Space Telescope is used to illustrate the application of the characteristic modeling and adaptive control method proposed in this paper.

  14. On the control of the Heider balance model

    Science.gov (United States)

    Wongkaew, S.; Caponigro, M.; Kułakowski, K.; Borzì, A.

    2015-12-01

    The Heider social balance model describes the evolution of the relationships in a social network of humans or animals. This model is built upon the concept of balance of triads consisting of friendly or hostile edges representing the state of the network. In this differential model, a leader is introduced in order to control the system and to drive the social network to a desired relationship state. Further, the stability, the local controllability, and the optimal control through leadership of the Heider model are investigated. Results of numerical experiments demonstrate the ability of the proposed control strategy to drive the Heider balance model to friendship.

  15. Design, modeling and control of nanopositioning systems

    CERN Document Server

    Fleming, Andrew J

    2014-01-01

    Covering the complete design cycle of nanopositioning systems, this is the first comprehensive text on the topic. The book first introduces concepts associated with nanopositioning stages and outlines their application in such tasks as scanning probe microscopy, nanofabrication, data storage, cell surgery and precision optics. Piezoelectric transducers, employed ubiquitously in nanopositioning applications are then discussed in detail including practical considerations and constraints on transducer response. The reader is then given an overview of the types of nanopositioner before the text turns to the in-depth coverage of mechanical design including flexures, materials, manufacturing techniques, and electronics. This process is illustrated by the example of a high-speed serial-kinematic nanopositioner. Position sensors are then catalogued and described and the text then focuses on control. Several forms of control are treated: shunt control, feedback control, force feedback control and feedforward control (...

  16. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    load shifting capabilities of the units that adapts to the given price predictions. We furthermore evaluated control performance in terms of economic savings for different control strategies and forecasts. Chapter 5 describes and compares the proposed large-scale Aggregator control strategies....... Aggregators are assumed to play an important role in the future Smart Grid and coordinate a large portfolio of units. The developed economic MPC controllers interfaces each unit directly to an Aggregator. We developed several MPC-based aggregation strategies that coordinates the global behavior of a portfolio...

  17. Nonlinear Modeling and Neuro-Fuzzy Control of PEMFC

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The proton exchange membrane generation technology is highly efficient, and clean and is considered as the most hopeful "green" power technology. The operating principles of proton exchange membrane fuel cell (PEMFC) system involve thermodynamics, electrochemistry, hydrodynamics and mass transfer theory, which comprise a complex nonlinear system, for which it is difficult to establish a mathematical model and control online.This paper analyzed the characters of the PEMFC; and used the approach and self-study ability of artificial neural networks to build the model of nonlinear system, and adopted the adaptive neural-networks fuzzy infer system to build the temperature model of PEMFC which is used as the reference model of the control system, and adjusted the model parameters to control online. The model and control were implemented in SIMULINK environment.The results of simulation show the test data and model have a good agreement. The model is useful for the optimal and real time control of PEMFC system.

  18. Model-Based Traffic Control for Sustainable Mobility

    NARCIS (Netherlands)

    Zegeye, S.K.

    2011-01-01

    Computationally efficient dynamic fuel consumption, emissions, and dispersion of emissions models are developed. Fast and practically feasible model-based controller is proposed. Using the developed models, the controller steers the traffic flow in such a way that a balanced trade-off between the t

  19. Stabilization of model-based networked control systems

    Science.gov (United States)

    Miranda, Francisco; Abreu, Carlos; Mendes, Paulo M.

    2016-06-01

    A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.

  20. Modeling and Control of Flexible Structures.

    Science.gov (United States)

    1986-12-16

    amount of viscous damping then stabilizing control can be computed. Since viscous effects will not be present in space applications one is faced with a...which involve the correctors and the data of the problem. f, - 4.3 Homogenization and Stabilizing Control of Lat- - tice Structures In this subsection we

  1. Nonlinear model predictive control of a packed distillation column

    Energy Technology Data Exchange (ETDEWEB)

    Patwardhan, A.A.; Edgar, T.F. (Univ. of Texas, Austin, TX (United States). Dept. of Chemical Engineering)

    1993-10-01

    A rigorous dynamic model based on fundamental chemical engineering principles was formulated for a packed distillation column separating a mixture of cyclohexane and n-heptane. This model was simplified to a form suitable for use in on-line model predictive control calculations. A packed distillation column was operated at several operating conditions to estimate two unknown model parameters in the rigorous and simplified models. The actual column response to step changes in the feed rate, distillate rate, and reboiler duty agreed well with dynamic model predictions. One unusual characteristic observed was that the packed column exhibited gain-sign changes, which are very difficult to treat using conventional linear feedback control. Nonlinear model predictive control was used to control the distillation column at an operating condition where the process gain changed sign. An on-line, nonlinear model-based scheme was used to estimate unknown/time-varying model parameters.

  2. The semiotics of control and modeling relations in complex systems.

    Science.gov (United States)

    Joslyn, C

    2001-01-01

    We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.

  3. Model predictive control of P-time event graphs

    Science.gov (United States)

    Hamri, H.; Kara, R.; Amari, S.

    2016-12-01

    This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.

  4. Modelling and control PEMFC using fuzzy neural networks

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Proton exchange membrane generation technology is highly efficient, clean and considered as the most hopeful "green" power technology. The operating principles of proton exchange membrane fuel cell (PEMFC) system involve thermodynamics, electrochemistry, hydrodynamics and mass transfer theory, which comprise a complex nonlinear system, for which it is difficult to establish a mathematical model and control online. This paper first simply analyzes the characters of the PEMFC; and then uses the approach and self-study ability of artificial neural networks to build the model of the nonlinear system, and uses the adaptive neural-networks fuzzy infer system (ANFIS) to build the temperature model of PEMFC which is used as the reference model of the control system, and adjusts the model parameters to control it online. The model and control are implemented in SIMULINK environment. Simulation results showed that the test data and model agreed well, so it will be very useful for optimal and real-time control of PEMFC system.

  5. Building A Flight Control System For A Modelled Aircraft

    OpenAIRE

    Garratt, Paul William; Rushton, Andrew; Yilmaz, Esat

    2004-01-01

    Abstract. We modelled an aircraft based on the Airbus A320 and constructed a synthesisable flight control system. The novel feature was the use of C and VHDL, Very High Speed Inte-grated Circuit Design Language, to allow the flight control system to reside in a Field Pro-grammable Gate Array in a model aircraft or an Uninhabited Aerial Vehicle. The simulator models axial, normal, transverse, pitch, roll and yaw movements. The flight control system has automatic manoeuvre envelope protection a...

  6. On-line control models for the Stanford Linear Collider

    Energy Technology Data Exchange (ETDEWEB)

    Sheppard, J.C.; Helm, R.H.; Lee, M.J.; Woodley, M.D.

    1983-03-01

    Models for computer control of the SLAC three-kilometer linear accelerator and damping rings have been developed as part of the control system for the Stanford Linear Collider. Some of these models have been tested experimentally and implemented in the control program for routine linac operations. This paper will describe the development and implementation of these models, as well as some of the operational results.

  7. General model and control of an n rotor helicopter

    OpenAIRE

    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 experimentally on a quadcopter. Using the combined model andcontrollers, simple system simulation and control is possible, by replacing the physical valuesfor the individual systems.

  8. 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 ...

  9. 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...

  10. 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.

  11. Fuzzy modeling and control theory and applications

    CERN Document Server

    Matía, Fernando; Jiménez, Emilio

    2014-01-01

    Much work on fuzzy control, covering research, development and applications, has been developed in Europe since the 90's. Nevertheless, the existing books in the field are compilations of articles without interconnection or logical structure or they express the personal point of view of the author. This book compiles the developments of researchers with demonstrated experience in the field of fuzzy control following a logic structure and a unified the style. The first chapters of the book are dedicated to the introduction of the main fuzzy logic techniques, where the following chapters focus on concrete applications. This book is supported by the EUSFLAT and CEA-IFAC societies, which include a large number of researchers in the field of fuzzy logic and control. The central topic of the book, Fuzzy Control, is one of the main research and development lines covered by these associations.

  12. Towards a South African crowd control model

    CSIR Research Space (South Africa)

    Modise, M

    2013-03-01

    Full Text Available With the escalating number of incidents of service delivery, labour related protests and the increasingly violent nature of protests; crowd control is one of the major challenges facing South Africa today. Often these protests are characterized...

  13. Model predictive control for wind power gradients

    DEFF Research Database (Denmark)

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

    2015-01-01

    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......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...... transform the problem to one with linear dynamics and convex constraints. Thus, the problem can be globally solved, using robust, fast solvers tailored for embedded control applications. We implement the optimal control problem in a receding horizon manner and provide extensive closed-loop tests with real...

  14. 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

    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......, 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......) or other advanced optimal control applications of a wind farm....

  15. 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...... 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...

  16. A service-oriented data access control model

    Science.gov (United States)

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

    2017-01-01

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

  17. Modeling, Simulation and Position Control of 3DOF Articulated Manipulator

    Directory of Open Access Journals (Sweden)

    Hossein Sadegh Lafmejani

    2014-08-01

    Full Text Available In this paper, the modeling, simulation and control of 3 degrees of freedom articulated robotic manipulator have been studied. First, we extracted kinematics and dynamics equations of the mentioned manipulator by using the Lagrange method. In order to validate the analytical model of the manipulator we compared the model simulated in the simulation environment of Matlab with the model was simulated with the SimMechanics toolbox. A sample path has been designed for analyzing the tracking subject. The system has been linearized with feedback linearization and then a PID controller was applied to track a reference trajectory. Finally, the control results have been compared with a nonlinear PID controller.

  18. Stability Constraints for Robust Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Amanda G. S. Ottoni

    2015-01-01

    Full Text Available This paper proposes an approach for the robust stabilization of systems controlled by MPC strategies. Uncertain SISO linear systems with box-bounded parametric uncertainties are considered. The proposed approach delivers some constraints on the control inputs which impose sufficient conditions for the convergence of the system output. These stability constraints can be included in the set of constraints dealt with by existing MPC design strategies, in this way leading to the “robustification” of the MPC.

  19. Model-based dynamic control and optimization of gas networks

    Energy Technology Data Exchange (ETDEWEB)

    Hofsten, Kai

    2001-07-01

    This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum

  20. Low Order Empirical Galerkin Models for Feedback Flow Control

    Science.gov (United States)

    Tadmor, Gilead; Noack, Bernd

    2005-11-01

    Model-based feedback control restrictions on model order and complexity stem from several generic considerations: real time computation, the ability to either measure or reliably estimate the state in real time and avoiding sensitivity to noise, uncertainty and numerical ill-conditioning are high on that list. Empirical POD Galerkin models are attractive in the sense that they are simple and (optimally) efficient, but are notoriously fragile, and commonly fail to capture transients and control effects. In this talk we review recent efforts to enhance empirical Galerkin models and make them suitable for feedback design. Enablers include `subgrid' estimation of turbulence and pressure representations, tunable models using modes from multiple operating points, and actuation models. An invariant manifold defines the model's dynamic envelope. It must be respected and can be exploited in observer and control design. These ideas are benchmarked in the cylinder wake system and validated by a systematic DNS investigation of a 3-dimensional Galerkin model of the controlled wake.

  1. Modelling and Control of Magnetorheological Damper

    DEFF Research Database (Denmark)

    Bhowmik, Subrata

    damper is identified by both the standard parametric Bouc-Wen model and the non-parametric neural network model from an experimental data set generated by dynamic tests of the MR damper mounted in a hydraulic testing machine. The forward model represents the direct dynamics of the MR damper where...... contribution to the modelling of an MR damper is the use of experimental measurement data of a rotary MR damper that requires appropriate filtering. The semi-systematic optimisation procedure proposed in the thesis derives an effective neural network structure, where only velocity and damper force...... fuses the displacement and the acceleration data to get an accurate and robust estimate of the velocity. The simplicity of the network and the application of velocity in terms of KKF is a novel contribution of the thesis to the generation of a training set for neural network modelling of MR dampers...

  2. Optimal control design that accounts for model mismatch errors

    Energy Technology Data Exchange (ETDEWEB)

    Kim, T.J. [Sandia National Labs., Albuquerque, NM (United States); Hull, D.G. [Texas Univ., Austin, TX (United States). Dept. of Aerospace Engineering and Engineering Mechanics

    1995-02-01

    A new technique is presented in this paper that reduces the complexity of state differential equations while accounting for modeling assumptions. The mismatch controls are defined as the differences between the model equations and the true state equations. The performance index of the optimal control problem is formulated with a set of tuning parameters that are user-selected to tune the control solution in order to achieve the best results. Computer simulations demonstrate that the tuned control law outperforms the untuned controller and produces results that are comparable to a numerically-determined, piecewise-linear optimal controller.

  3. SPICE modeling of flux-controlled unipolar memristive devices

    Institute of Scientific and Technical Information of China (English)

    Fang Xu-Dong; Tang Yu-Hua; Wu Jun-Jie; Zhu Xuan; Zhou Jing; Huang Da

    2013-01-01

    Unipolar memristive devices are an important kind of resistive switching devices.However,few circuit models of them have been proposed.In this paper,we propose the SPICE modeling of flux-controlled unipolar memristive devices based on the memristance versus state map.Using our model,the flux thresholds,ON and OFF resistance,and compliance current can easily be set as model parameters.We simulate the model in HSPICE using model parameters abstracted from real devices,and the simulation results show that the proposed model caters to the real device data very well,thus demonstrating that the model is correct.Using the same modeling methodology,the SPICE model of charge-controlled unipolar memristive devices could also be developed.The proposed model could be used to model resistive memory cells,logical gates as well as synapses in artificial neural networks.

  4. Logistic Regression Model on Antenna Control Unit Autotracking Mode

    Science.gov (United States)

    2015-10-20

    412TW-PA-15240 Logistic Regression Model on Antenna Control Unit Autotracking Mode DANIEL T. LAIRD AIR FORCE TEST CENTER EDWARDS AFB, CA...OCT 15 4. TITLE AND SUBTITLE Logistic Regression Model on Antenna Control Unit Autotracking Mode 5a. CONTRACT NUMBER 5b. GRANT...alternative-hypothesis. This paper will present an Antenna Auto- tracking model using Logistic Regression modeling. This paper presents an example of

  5. Model reference, sliding mode adaptive control for flexible structures

    Science.gov (United States)

    Yurkovich, S.; Ozguner, U.; Al-Abbass, F.

    1988-01-01

    A decentralized model reference adaptive approach using a variable-structure sliding model control has been developed for the vibration suppression of large flexible structures. Local models are derived based upon the desired damping and response time in a model-following scheme, and variable structure controllers are then designed which employ colocated angular rate and position feedback. Numerical simulations have been performed using NASA's flexible grid experimental apparatus.

  6. Developing an Integrated Set of Production Planning and Control Models

    OpenAIRE

    Wang, Hui

    2012-01-01

    This paper proposes an integrated set of production planning and control models that can be applied in the Push system (Make-to-stock). The integrated model include forecasting, aggregate planning, materials requirements planning, inventory control, capacity planning and scheduling. This integrated model solves the planning issues via three levels, which include strategic level, tactical level and operational level. The model obtains the optimal production plan for each product type in each p...

  7. Molten carbonate fuel cells. Modeling, analysis, simulation, and control

    Energy Technology Data Exchange (ETDEWEB)

    Sundmacher, K.; Kienle, A. [Max-Planck-Institut fuer Dynamik Komplexer Technischer Systeme, Magdeburg (Germany); Pesch, H.J. [Bayreuth Univ. (Germany). Lehrstuhl fuer Ingenieurmathematik; Berndt, J.F. [IPF Beteiligungsgesellschaft Berndt KG, Reilingen (Germany); Huppmann, G. (eds.) [MTU CFC Solutions GmbH, Muenchen (Germany)

    2007-07-01

    This book presents model-based concepts for process analysis and control on a generalized basis. It is structured as follows: Part I - DESIGN AND OPERATION: MTU's Carbonate Fuel Cell HotModule; Operational Experiences. Part II - MODEL-BASED PROCESS ANALYSIS: MCFC Reference Model; Index Analysis of Models; Parameter Identification; Steady State Process Analysis; Hot spot formation and steady state multiplicities; Conceptual design an Reforming concepts. Part III - OPTIMIZATION AND ADVANCED CONTROL: Model reduction and State estimation; Optimal Control Strategies; Optimization of Reforming Catalyst Distribution.

  8. Model-Based Development of Control Systems for Forestry Cranes

    Directory of Open Access Journals (Sweden)

    Pedro La Hera

    2015-01-01

    Full Text Available Model-based methods are used in industry for prototyping concepts based on mathematical models. With our forest industry partners, we have established a model-based workflow for rapid development of motion control systems for forestry cranes. Applying this working method, we can verify control algorithms, both theoretically and practically. This paper is an example of this workflow and presents four topics related to the application of nonlinear control theory. The first topic presents the system of differential equations describing the motion dynamics. The second topic presents nonlinear control laws formulated according to sliding mode control theory. The third topic presents a procedure for model calibration and control tuning that are a prerequisite to realize experimental tests. The fourth topic presents the results of tests performed on an experimental crane specifically equipped for these tasks. Results of these studies show the advantages and disadvantages of these control algorithms, and they highlight their performance in terms of robustness and smoothness.

  9. Modeling and control of the magnetic suspension system.

    Science.gov (United States)

    Golob, Marjan; Tovornik, Boris

    2003-01-01

    A fuzzy logic based controller applied to a simple magnetic suspension is presented in this paper. The simple electromagnet-ball system and the contactless optical position measurement system are developed as a physical model of the magnetic suspension. A nonlinear mathematical model is presented and linearized. This model has been used to design a discrete linear PID controller with optimal parameters. The physical real-time model was constructed in order to compare the performance of the linear discrete PID controller and the proposed fuzzy logic based PID controller. The decomposed fuzzy PID controller has proportional, integral, and derivative separate parts which are tuned independently. When testing it becomes clear that the decomposed fuzzy PID controller gives better performance over a typical operational range than a traditional linear PID controller.

  10. Modelling and control of a suspension system for vehicle applications

    OpenAIRE

    Dowds, Padraig; O'Dwyer, Aidan

    2005-01-01

    This paper discusses the modelling of passive and active suspension systems in a car, and the subsequent design of appropriate feedback controllers for the active suspension system. The models will be investigated using a quarter car model and a full car model approach.

  11. The Modeling Strategies for Open Software Architecture of Robot Controller

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Although the modeling technologies for open robot controllers have been discussed widely, not much literature is devoted to the actual general modeling principles and strategies. The reason is that many researches focus on specific application fields. This paper accommodates for this lacuna and provides some general modeling principles and strategies. At last, the actual new modeling method -Hierarchical Object-Oriented Petri net (HOONet) which has been proved to be an effective modeling methodology, is used to illustrate the modeling strategies.

  12. Intelligent control based on intelligent characteristic model and its application

    Institute of Scientific and Technical Information of China (English)

    吴宏鑫; 王迎春; 邢琰

    2003-01-01

    This paper presents a new intelligent control method based on intelligent characteristic model for a kind of complicated plant with nonlinearities and uncertainties, whose controlled output variables cannot be measured on line continuously. The basic idea of this method is to utilize intelligent techniques to form the characteristic model of the controlled plant according to the principle of combining the char-acteristics of the plant with the control requirements, and then to present a new design method of intelli-gent controller based on this characteristic model. First, the modeling principles and expression of the intelligent characteristic model are presented. Then based on description of the intelligent characteristic model, the design principles and methods of the intelligent controller composed of several open-loops and closed-loops sub controllers with qualitative and quantitative information are given. Finally, the ap-plication of this method in alumina concentration control in the real aluminum electrolytic process is in-troduced. It is proved in practice that the above methods not only are easy to implement in engineering design but also avoid the trial-and-error of general intelligent controllers. It has taken better effect in the following application: achieving long-term stable control of low alumina concentration and increasing the controlled ratio of anode effect greatly from 60% to 80%.

  13. 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....

  14. Joint Control for Dummies*: An Elaboration of Lowenkron's Model of Joint (Stimulus) Control.

    Science.gov (United States)

    Sidener, David W

    2006-01-01

    The following paper describes Lowenkron's model of joint (stimulus) control. Joint control is described as a means of accounting for performances, especially generalized performances, for which a history of contingency control does not provide an adequate account. Examples are provided to illustrate instances in which joint control may facilitate performance of a task.

  15. Joint Control for Dummies: An Elaboration of Lowenkron's Model of Joint (Stimulus) Control

    Science.gov (United States)

    Sidener, David W.

    2006-01-01

    The following paper describes Lowenkron's model of joint (stimulus) control. Joint control is described as a means of accounting for performances, especially generalized performances, for which a history of contingency control does not provide an adequate account. Examples are provided to illustrate instances in which joint control may facilitate…

  16. Modelling the control of interceptive actions

    National Research Council Canada - National Science Library

    P. J. Beek; J. C. Dessing; C. E. Peper; D. Bullock

    2003-01-01

    .... We call these short–route models as they do not address how perception–action patterns might be constrained by the dynamical properties of the sensory, neural and musculoskeletal subsystems of the human action system...

  17. Control of Stirling engine. Simplified, compressible model

    Science.gov (United States)

    Plotnikov, P. I.; Sokołowski, J.; Żochowski, A.

    2016-06-01

    A one-dimensional free boundary problem on a motion of a heavy piston in a tube filled with viscous gas is considered. The system of governing equations and boundary conditions is derived. The obtained system of differential equations can be regarded as a mathematical model of an exterior combustion engine. The existence of a weak solution to this model is proved. The problem of maximization of the total work of the engine is considered.

  18. Comparative analysis for NN inverse model controller and backstepping controller on mobile robots

    Directory of Open Access Journals (Sweden)

    Margarita Gjonaj

    2016-11-01

    Full Text Available This work addresses the design and implementation of a neural network based controller for the trajectory tracking of a differential drive mobile robot. A neural network based tracking control algorithm is proposed and simulation and experimental results are presented. The algorithm is a control structure that makes possible the integration of a back-stepping controller and a neural network (NN computed-torque controller for a nonholonomic mobile robot. Integration of a neural network controller and the kinematic based controller gives the advantage of dealing with unmodeled and unstructured uncertainties and disturbances to the system. Comprehensive system modeling including robot kinematics, dynamics and actuator modeling has been done. The dynamic modeling is done Lagrangian methodologies for nonholonomic systems. Simulation of the robot model and different controllers has been done using Matlab and Matlab Simulink.

  19. Efficient Control of Nonlinear Noise-Corrupted Systems Using a Novel Model Predictive Control Framework

    OpenAIRE

    Weissel, Florian; Huber, Marco F.; Hanebeck, Uwe D.

    2007-01-01

    Model identification and measurement acquisition is always to some degree uncertain. Therefore, a framework for Nonlinear Model Predictive Control (NMPC) is proposed that explicitly considers the noise influence on nonlinear dynamic systems with continuous state spaces and a finite set of control inputs in order to significantly increase the control quality. Integral parts of NMPC are the prediction of system states over a finite horizon as well as the problem specific modeling of reward func...

  20. Model-based control of hopper dredgers

    NARCIS (Netherlands)

    Braaksma, J.

    2008-01-01

    The modern trailing suction hopper dredgers are advanced ships that are equipped with many automation systems that can be controlled with integrated computer systems from the bridge. From the operators it is expected that they generate the right set-points for all these systems. The latest ships are

  1. Hydraulic Control Design and Modeling Techniques.

    Science.gov (United States)

    1989-02-01

    methodologies. This report may be difficult to read for the casual reader . It is written assuming the reader has some fundamental background in control...INTERVAL DTSMP=.O0012207 STEP=. 0012207 INDEX=INDEX+i DOUT( INDEX2)=L1 A- 4 END $*OF DISCRETE SAMP 2" DERIVATIVE tarot (INDEX2 .GE. 4098) END $*OF

  2. A new modeling and control scheme for thyristor-controlled series capacitor

    Institute of Scientific and Technical Information of China (English)

    Zhizhong MAO

    2009-01-01

    In order to design an optimal controller for the thyristor controlled series capacitor(TCSC),a novel TCSC control model is developed.In the model,the delay angle of thyristor valves is the input,and the inductor current is chosen as the output.Theoretical analysis and simulation studies show that TCSC is a non-linear system and its parameters vary with the operating point.In consideration of the special characteristics of the TCSC,an improved model algorithmic control (IMAC) scheme is proposed to control TCSC effectively.The good performance can be observed from simulation results when IMAC is applied to a series compensated radial system.

  3. Numerical model of compressible gas flow in soil pollution control

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Based on the theory of fluid dynamics in porous media, a numerical model of gas flow in unsaturated zone is developed with the consideration of gas density change due to variation of air pressure. This model is characterized of its wider range of availability. The accuracy of this numerical model is analyzed through comparison with modeling results by previous model with presumption of little pressure variation and the validity of this numerical model is shown. Thus it provides basis for the designing and management of landfill gas control system or soil vapor ex.action system in soil pollution control.

  4. Modeling and Control of a teletruck using electronic load sensing

    DEFF Research Database (Denmark)

    Hansen, Rico Hjerm; Iversen, Asger Malte; Jensen, Mads Schmidt;

    2010-01-01

    system is most commonly controlled using a hydro-mechanical control scheme called Hydraulic Load Sensing (HLS). However, with the demands for increased efficiency and controllability the HLS solutions are reaching their limits. Motivated by availability of electronic controllable fluid power...... the controller design for the ELS system, a complete model of the teletruck’s articulated arm and fluid power system is developed. To show the feasibility, a preliminary control structure for the ELS system is developed. The controller is tested on the machine, validating that features such as pump pressure...

  5. Model-free Adaptive Control for Spacecraft Attitude

    Institute of Scientific and Technical Information of China (English)

    Ran Xie; Ting Song; Peng Shi; Yushan Zhao

    2016-01-01

    A model⁃free adaptive control method is proposed for the spacecrafts whose dynamical parameters change over time and cannot be acquired accurately. The algorithm is based on full form dynamic linearization. A dimension reduction matrix is introduced to construct an augmented system with the same dimension input and output. The design of the controller depends on the system input and output data rather than the knowledge of the controlled plant. The numerical simulation results show that the improved controller can deal with different models with the same set of controller parameters, and the controller performance is better than that of PD controller for the time⁃varying system with disturbance.

  6. Information Model for Resource of ASON Control Plane

    Institute of Scientific and Technical Information of China (English)

    XU Yun-bin; SONG Hong-sheng; GUI Xuan; ZHANG Jie; GU Wan-yi

    2004-01-01

    Automatic Switched Optical network (ASON) is the key technology for the next generation optical networks, and the recommendations for ASON were also developed by ITU-T. However, the recommendations for the management plane have not been made yet. In this paper, the management information model for the resources of control plane is proposed based on the management requirements of ASON for the first time. The managed objects for control plane could be used for the management of control Network Elements(NEs) and control channels, they can also be used for route areas division in control plane, parameter configuration and performance inspection for the control modules in a control NEs.

  7. Digital Control System For Wind-Tunnel Model

    Science.gov (United States)

    Hoadley, Sherwood T.; Mcgraw, Sandra

    1995-01-01

    Multiple functions performed by multiple coordinated processors for real-time control. Multiple input, multiple-output, multiple-function digital control system developed for wind-tunnel model of advanced fighter airplane with actively controlled flexible wings. Digital control system provides flexibility in selection of control laws, sensors, and actuators, plus some redundancy to accommodate failures in some of its subsystems. Implements feedback control scheme providing simultaneously for suppression of flutter, control of roll angle, roll-rate tracking during maximized roll maneuvers, and alleviation of loads during roll maneuvers.

  8. System Modeling, Validation, and Design of Shape Controllers for NSTX

    Science.gov (United States)

    Walker, M. L.; Humphreys, D. A.; Eidietis, N. W.; Leuer, J. A.; Welander, A. S.; Kolemen, E.

    2011-10-01

    Modeling of the linearized control response of plasma shape and position has become fairly routine in the last several years. However, such response models rely on the input of accurate values of model parameters such as conductor and diagnostic sensor geometry and conductor resistivity or resistance. Confidence in use of such a model therefore requires that some effort be spent in validating that the model has been correctly constructed. We describe the process of constructing and validating a response model for NSTX plasma shape and position control, and subsequent use of that model for the development of shape and position controllers. The model development, validation, and control design processes are all integrated within a Matlab-based toolset known as TokSys. The control design method described emphasizes use of so-called decoupling control, in which combinations of coil current modifications are designed to modify only one control parameter at a time, without perturbing any other control parameter values. Work supported by US DOE under DE-FG02-99ER54522 and DE-AC02-09CH11466.

  9. A control model for district heating networks with storage

    NARCIS (Netherlands)

    Scholten, Tjeert; De Persis, Claudio; Tesi, Pietro

    2014-01-01

    In [1] pressure control of hydraulic networks is investigated. We extend this work to district heating systems with storage capabilities and derive a model taking the topology of the network into account. The goal for the derived model is that it should allow for control of the storage level and tem

  10. Estimated Frequency Domain Model Uncertainties used in Robust Controller Design

    DEFF Research Database (Denmark)

    Tøffner-Clausen, S.; Andersen, Palle; Stoustrup, Jakob;

    1994-01-01

    This paper deals with the combination of system identification and robust controller design. Recent results on estimation of frequency domain model uncertainty are......This paper deals with the combination of system identification and robust controller design. Recent results on estimation of frequency domain model uncertainty are...

  11. Green Granary Temperature Control System Modeling and Simulation

    Science.gov (United States)

    Shi, Qingsheng

    As an important link of food production and distribution process, Granary's temperature control performance seriously affects the food quality and storage costs. Based on the analysis of granary components, granary temperature control model is established. The simulation results show the validity of established model.

  12. 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 exper...

  13. A control model for district heating networks with storage

    NARCIS (Netherlands)

    Scholten, Tjeert; De Persis, Claudio; Tesi, Pietro

    2014-01-01

    In [1] pressure control of hydraulic networks is investigated. We extend this work to district heating systems with storage capabilities and derive a model taking the topology of the network into account. The goal for the derived model is that it should allow for control of the storage level and tem

  14. Quality control of geological voxel models using experts' gaze

    NARCIS (Netherlands)

    Maanen, van Peter-Paul; Busschers, Freek S.; Brouwer, Anne-Marie; Meulendijk, van der Michiel J.; Erp, van Jan B.F.

    2015-01-01

    Due to an expected increase in geological voxel model data-flow and user demands, the development of improved quality control for such models is crucial. This study explores the potential of a new type of quality control that improves the detection of errors by just using gaze behavior of 12 geologi

  15. Modeling, analysis and control of a variable geometry actuator

    NARCIS (Netherlands)

    Evers, W.J.; Knaap, A. van der; Besselink, I.J.M.; Nijmeijer, H.

    2008-01-01

    A new design of variable geometry force actuator is presented in this paper. Based upon this design, a model is derived which is used for steady-state analysis, as well as controller design in the presence of friction. The controlled actuator model is finally used to evaluate the power consumption u

  16. Online Model Learning Algorithms for Actor-Critic Control

    NARCIS (Netherlands)

    Grondman, I.

    2015-01-01

    Classical control theory requires a model to be derived for a system, before any control design can take place. This can be a hard, time-consuming process if the system is complex. Moreover, there is no way of escaping modelling errors. As an alternative approach, there is the possibility of having

  17. Delayed Random Walks: Modeling Human Posture Control

    Science.gov (United States)

    Ohira, Toru

    1998-03-01

    We consider a phenomenological description of a noisy trajectory which appears on a stabiliogram platform during human postural sway. We hypothesize that this trajectory arises due to a mixture of uncontrollable noise and a corrective delayed feedback to an upright position. Based on this hypothesis, we model the process with a biased random walk whose transition probability depends on its position at a fixed time delay in the past, which we call a delayed random walk. We first introduce a very simple model (T. Ohira and J. G. Milton, Phys.Rev.E. 52), 3277, (1995), which can nevertheless capture the rough qualitative features of the two--point mean square displacement of experimental data with reasonable estimation of delay time. Then, we discuss two approaches toward better capturing and understanding of the experimental data. The first approach is an extension of the model to include a spatial displacement threshold from the upright position below which no or only weak corrective feedback motion takes place. This can be incorporated into an extended delayed random walk model. Numerical simulations show that this extended model can better capture the three scaling region which appears in the two--point mean square displacement. The other approach studied the autocorrelation function of the experimental data, which shows oscillatory behavior. We recently investigated a delayed random walk model whose autocorrelation function has analytically tractable oscillatory behavior (T. Ohira, Phys.Rev.E. 55), R1255, (1997). We discuss how this analytical understanding and its application to delay estimation (T. Ohira and R. Sawatari, Phys.Rev.E. 55), R2077, (1997) could possibly be used to further understand the postural sway data.

  18. Hidden Markov models estimation and control

    CERN Document Server

    Elliott, Robert J; Moore, John B

    1995-01-01

    As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filte

  19. Controlled Ecological Life Support System (CELSS) modeling

    Science.gov (United States)

    Drysdale, Alan; Thomas, Mark; Fresa, Mark; Wheeler, Ray

    1992-01-01

    Attention is given to CELSS, a critical technology for the Space Exploration Initiative. OCAM (object-oriented CELSS analysis and modeling) models carbon, hydrogen, and oxygen recycling. Multiple crops and plant types can be simulated. Resource recovery options from inedible biomass include leaching, enzyme treatment, aerobic digestion, and mushroom and fish growth. The benefit of using many small crops overlapping in time, instead of a single large crop, is demonstrated. Unanticipated results include startup transients which reduce the benefit of multiple small crops. The relative contributions of mass, energy, and manpower to system cost are analyzed in order to determine appropriate research directions.

  20. Multilevel Flow Modelling of Process Plant for Diagnosis and Control

    DEFF Research Database (Denmark)

    Lind, Morten

    1982-01-01

    of complex systems. A model of a nuclear power plant (PWR) is presented in the paper for illustration. Due to the consistency of the method, multilevel flow models provide specifications of plant goals and functions and may be used as a basis for design of computer-based support systems for the plant...... operator. Plant control requirements can be derived from the models and due to independence of the actual controller implementation the method may be used as a basis for design of control strategies and for the allocation of control tasks to the computer and the plant operator....

  1. MODELLING AND CONTROLLING OF INDUCTION MOTOR BY USING LINEAR ADRC

    Directory of Open Access Journals (Sweden)

    CH. NAGA KOTI KUMAR,

    2011-04-01

    Full Text Available In this paper we present a new novel approach for the speed control of an IM using Linear Active Disturbance Rejection Controller [LADRC]. The field oriented control of IM needs the accuratemathematical model of IM, but it is very difficult to develop an accurate mathematical model. The LADRC does depend on the mathematical model so it is very robust to changes in plant parameters. This controller can also estimate and compensate the general disturbances which include the unknown internal dynamics and external disturbances by using the Extended State Observer, which can reduce the system to a linear one.

  2. Cascaded process model based control: packed absorption column application.

    Science.gov (United States)

    Govindarajan, Anand; Jayaraman, Suresh Kumar; Sethuraman, Vijayalakshmi; Raul, Pramod R; Rhinehart, R Russell

    2014-03-01

    Nonlinear, adaptive, process-model based control is demonstrated in a cascaded single-input-single-output mode for pressure drop control in a pilot-scale packed absorption column. The process is shown to be nonlinear. Control is demonstrated in both servo and regulatory modes, for no wind-up in a constrained situation, and for bumpless transfer. Model adaptation is demonstrated and shown to provide process insight. The application procedure is revealed as a design guide to aid others in implementing process-model based control.

  3. Modeling for Optimal Control : A Validated Diesel-Electric Powertrain Model

    OpenAIRE

    Sivertsson, Martin; Eriksson, Lars

    2014-01-01

    An optimal control ready model of a diesel-electric powertrain is developed,validated and provided to the research community. The aim ofthe model is to facilitate studies of the transient control of diesel-electricpowertrains and also to provide a model for developers of optimizationtools. The resulting model is a four state three control mean valueengine model that captures the significant nonlinearity of the diesel engine, while still being continuously differentiable.

  4. AN EOQ MODEL WITH CONTROLLABLE SELLING RATE

    OpenAIRE

    HORNG-JINH CHANG; PO-YU CHEN

    2008-01-01

    According to the marketing principle, a decision maker may control demand rate through selling price and the unit facility cost of promoting transaction. In fact, the upper bound of willing-to-pay price and the transaction cost probably depend upon the subjective judgment of individual consumer in purchasing merchandise. This study therefore attempts to construct a bivariate distribution function to simultaneously incorporate the willing-to-pay price and the transaction cost into the classica...

  5. Mechanics and model-based control of advanced engineering systems

    CERN Document Server

    Irschik, Hans; Krommer, Michael

    2014-01-01

    Mechanics and Model-Based Control of Advanced Engineering Systems collects 32 contributions presented at the International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines, which took place in St. Petersburg, Russia in July 2012. The workshop continued a series of international workshops, which started with a Japan-Austria Joint Workshop on Mechanics and Model Based Control of Smart Materials and Structures and a Russia-Austria Joint Workshop on Advanced Dynamics and Model Based Control of Structures and Machines. In the present volume, 10 full-length papers based on presentations from Russia, 9 from Austria, 8 from Japan, 3 from Italy, one from Germany and one from Taiwan are included, which represent the state of the art in the field of mechanics and model based control, with particular emphasis on the application of advanced structures and machines.

  6. Grey forecasting model for active vibration control systems

    Science.gov (United States)

    Lihua, Zou; Suliang, Dai; Butterworth, John; Ma, Xing; Dong, Bo; Liu, Aiping

    2009-05-01

    Based on the grey theory, a GM(1,1) forecasting model and an optimal GM(1,1) forecasting model are developed and assessed for use in active vibration control systems for earthquake response mitigation. After deriving equations for forecasting the control state vector, design procedures for an optimal active control method are proposed. Features of the resulting vibration control and the influence on it of time-delay based on different sampling intervals of seismic ground motion are analysed. The numerical results show that the forecasting models based on the grey theory are reliable and practical in structural vibration control fields. Compared with the grey forecasting model, the optimal forecasting model is more efficient in reducing the influences of time-delay and disturbance errors.

  7. Hybrid internal model control and proportional control of chaotic dynamical systems

    Institute of Scientific and Technical Information of China (English)

    齐冬莲; 姚良宾

    2004-01-01

    A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.

  8. Hybrid internal model control and proportional control of chaotic dynamical systems.

    Science.gov (United States)

    Qi, Dong-lian; Yao, Liang-bin

    2004-01-01

    A new chaos control method is proposed to take advantage of chaos or avoid it. The hybrid Internal Model Control and Proportional Control learning scheme are introduced. In order to gain the desired robust performance and ensure the system's stability, Adaptive Momentum Algorithms are also developed. Through properly designing the neural network plant model and neural network controller, the chaotic dynamical systems are controlled while the parameters of the BP neural network are modified. Taking the Lorenz chaotic system as example, the results show that chaotic dynamical systems can be stabilized at the desired orbits by this control strategy.

  9. Modeling Smart Energy Systems for Model Predictive Control

    DEFF Research Database (Denmark)

    2012-01-01

    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...... on a time scale ranging from seconds to several days by moving power consumption, exploiting thermal inertia or battery storage capacity, respectively. Using advanced control algorithms these systems are able to reduce their own electricity costs by planning ahead and moving consumption to periods...... the total power consumption of the smart energy systems connected to the power grid. Compared to a direct control strategy the complexity of the problem is reduced and decreases both the computation eorts and the need for communication. However, not only the current price, but a forecast of the expected...

  10. Modeling of Reaction Processes Controlled by Diffusion

    CERN Document Server

    Revelli, J

    2003-01-01

    Stochastic modeling is quite powerful in science and technology.The technics derived from this process have been used with great success in laser theory, biological systems and chemical reactions.Besides, they provide a theoretical framework for the analysis of experimental results on the field of particle's diffusion in ordered and disordered materials.In this work we analyze transport processes in one-dimensional fluctuating media, which are media that change their state in time.This fact induces changes in the movements of the particles giving rise to different phenomena and dynamics that will be described and analyzed in this work.We present some random walk models to describe these fluctuating media.These models include state transitions governed by different dynamical processes.We also analyze the trapping problem in a lattice by means of a simple model which predicts a resonance-like phenomenon.Also we study effective diffusion processes over surfaces due to random walks in the bulk.We consider differe...

  11. 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...

  12. Multi-model unfalsified switching control of uncertain multivariable systems

    NARCIS (Netherlands)

    Baldi, S.; Battistelli, G.; Mari, D.; Mosca, E.; Tesi, P.

    2012-01-01

    This paper addresses the problem of controlling an uncertain multi-input multi-output system by means of adaptive switching control schemes. In particular, the paper aims at extending the multi-model unfalsified control approach, so far restricted to single-input single-output systems, to a general

  13. Multiple-Model Adaptive Switching Control for Uncertain Multivariable Systems

    NARCIS (Netherlands)

    Baldi, Simone; Battistelli, Giorgio; Mari, Daniele; Mosca, Edoardo; Tesi, Pietro

    2011-01-01

    This paper addresses the problem of controlling an uncertain multi-input multi-output (MIMO) system by means of adaptive switching control schemes. In particular, the paper aims at extending the approach of multiple-model unfalsified adaptive switched control, so far restricted to single-input singl

  14. Distributed Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus Fogtmann; Vandenberghe, Lieven; Poulsen, Niels Kjølstad

    2016-01-01

    Integration of a large number of flexible consumers in a smart grid requires a scalable power balancing strategy. We formulate the control problem as an optimization problem to be solved repeatedly by the aggregator in a model predictive control framework. To solve the large-scale control problem...

  15. 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.

  16. Hybrid model predictive control for speed control of permanent magnet synchronous motor with saturation

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    A discrete-time hybrid model of a permanent magnet synchronous motor (PMSM) with saturation in voltage and current is formulated.The controller design with incorporated constraints is achieved in a systematic way from modeling to control synthesis and implementation.The Hybrid System Description Language is used to obtain a mixed-logical dynamical (MLD) model.Based on the MLD model,a model predictive controller is designed for an optimal speed regulation of the motor.For reducing computation complexity and ...

  17. Unified Modeling of Complex Real-Time Control Systems

    CERN Document Server

    Hai, He; Chi-Lan, Cai

    2011-01-01

    Complex real-time control system is a software dense and algorithms dense system, which needs modern software engineering techniques to design. UML is an object-oriented industrial standard modeling language, used more and more in real-time domain. This paper first analyses the advantages and problems of using UML for real-time control systems design. Then, it proposes an extension of UML-RT to support time-continuous subsystems modeling. So we can unify modeling of complex real-time control systems on UML-RT platform, from requirement analysis, model design, simulation, until generation code.

  18. Transfer Function Model of Multirate Feedback Control Systems

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Based on the suitably defined multivariable version of Krancoperators and the extended input and output vectors, the multirate sampling plant is transformed to a equivalent time invariant single rate one, then the transfer function model of the multivariable multirate sampling plant is obtained. By combining this plant model with the time invariant description of the multirate controller in terms of extended vectors, the closed-loop transfer function model of the multirate feedback control system can be determinated. This transfer function model has a very simple structure, and can be used as a basis for the analysis and synthesis of the multirate sampling feedback control systems in the frequency domain.

  19. Iterative learning control of SOFC based on ARX identification model

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper presents an application of iterative learning control (ILC) technique to the voltage control of solid oxide fuel cell (SOFC) stack. To meet the demands of the control system design, an autoregressive model with exogenous input (ARX) is established. Firstly, by regulating the variation of the hydrogen flow rate proportional to that of the current, the fuel utilization of the SOFC is kept within its admissible range. Then, based on the ARX model, three kinds of ILC controllers, i.e. P-, PI- and PD-type are designed to keep the voltage at a desired level. Simulation results demonstrate the potential of the ARX model applied to the control of the SOFC, and prove the excellence of the ILC controllers for the voltage control of the SOFC.

  20. Sensor Fault Tolerant Generic Model Control for Nonlinear Systems

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    A modified Strong Tracking Filter (STF) is used to develop a new approach to sensor fault tolerant control. Generic Model Control (GMC) is used to control the nonlinear process while the process runs normally because of its robust control performance. If a fault occurs in the sensor, a sensor bias vector is then introduced to the output equation of the process model. The sensor bias vector is estimated on-line during every control period using the STF. The estimated sensor bias vector is used to develop a fault detection mechanism to supervise the sensors. When a sensor fault occurs, the conventional GMC is switched to a fault tolerant control scheme, which is, in essence, a state estimation and output prediction based GMC. The laboratory experimental results on a three-tank system demonstrate the effectiveness of the proposed Sensor Fault Tolerant Generic Model Control (SFTGMC) approach.

  1. Controlling self-organized criticality in sandpile models

    CERN Document Server

    Cajueiro, Daniel O

    2013-01-01

    We introduce an external control to reduce the size of avalanches in some sandpile models exhibiting self organized criticality. This rather intuitive approach seems to be missing in the vast literature on such systems. The control action, which amounts to triggering avalanches in sites that are near to be come critical, reduces the probability of very large events, so that energy dissipation occurs most locally. The control is applied to a directed Abelian sandpile model driven by both uncorrelated and correlated deposition. The latter is essential to design an efficient and simple control heuristic, but has only small influence in the uncontrolled avalanche probability distribution. The proposed control seeks a tradeoff between control cost and large event risk. Preliminary results hint that the proposed control works also for an undirected sandpile model.

  2. Aminoglycoside nephrotoxicity: modeling, simulation, and control.

    Science.gov (United States)

    Rougier, Florent; Claude, Daniel; Maurin, Michel; Sedoglavic, Alexandre; Ducher, Michel; Corvaisier, Stéphane; Jelliffe, Roger; Maire, Pascal

    2003-03-01

    The main constraints on the administration of aminoglycosides are the risks of nephrotoxicity and ototoxicity, which can lead to acute, renal, vestibular, and auditory toxicities. In the present study we focused on nephrotoxicity. No reliable predictor of nephrotoxicity has been found to date. We have developed a deterministic model which describes the pharmacokinetic behavior of aminoglycosides (with a two-compartment model), the kinetics of aminoglycoside accumulation in the renal cortex, the effects of aminoglycosides on renal cells, the resulting effects on renal function by tubuloglomerular feedback, and the resulting effects on serum creatinine concentrations. The pharmacokinetic parameter values were estimated by use of the NPEM program. The estimated pharmacodynamic parameter values were obtained after minimization of the least-squares objective function between the measured and the calculated serum creatinine concentrations. A simulation program assessed the influences of the dosage regimens on the occurrence of nephrotoxicity. We have also demonstrated the relevancy of modeling of the circadian rhythm of the renal function. We have shown the ability of the model to fit with 49 observed serum creatinine concentrations for a group of eight patients treated for endocarditis by comparison with 49 calculated serum creatinine concentrations (r(2) = 0.988; P < 0.001). We have found that for the same daily dose, the nephrotoxicity observed with a thrice-daily administration schedule appears more rapidly, induces a greater decrease in renal function, and is more prolonged than those that occur with less frequent administration schedules (for example, once-daily administration). Moreover, for once-daily administration, we have demonstrated that the time of day of administration can influence the incidence of aminoglycoside nephrotoxicity. The lowest level of nephrotoxicity was observed when aminoglycosides were administered at 1:30 p.m. Clinical application of this

  3. Modelling and Internal Fuzzy Model Power Control of a Francis Water Turbine

    Directory of Open Access Journals (Sweden)

    Klemen Nagode

    2014-02-01

    Full Text Available This paper presents dynamic modelling of a Francis turbine with a surge tank and the control of a hydro power plant (HPP. Non-linear and linear models include technical parameters and show high similarity to measurement data. Turbine power control with an internal model control (IMC is proposed, based on a turbine fuzzy model. Considering appropriate control responses in the entire area of turbine power, the model parameters of the process are determined from a fuzzy model, which are further included in the internal model controller. The results are compared to a proportional-integral (PI controller tuned with an integral absolute error (IAE objective function, and show an improved response of internal model control.

  4. Support vector regression-based internal model control

    Institute of Scientific and Technical Information of China (English)

    HUANG Yan-wei; PENG Tie-gen

    2007-01-01

    This paper proposes a design of internal model control systems for process with delay by using support vector regression (SVR). The proposed system fully uses the excellent nonlinear estimation performance of SVR with the structural risk minimization principle. Closed-system stability and steady error are analyzed for the existence of modeling errors. The simulations show that the proposed control systems have the better control performance than that by neural networks in the cases of the training samples with small size and noises.

  5. Fuzzy Adaptive Model Following Speed Control for Vector Controlled Permanent Magnet Synchronous Motor

    Directory of Open Access Journals (Sweden)

    Baghdad BELABES

    2008-12-01

    Full Text Available In this paper a hybrid controller combining a linear model following controller (LMFC and fuzzy logic control (FLC for speed vector controlled permanent magnet synchronous motor (PMSM is described on this study. The FLC is introduced at the adaptive mechanism level. First, an LMFC system is designed to allow the plant states to be controlled to follow the states produced by a reference model. In the nominal conditions, the model following is perfect and the adaptive mechanism based on the fuzzy logic is idle. Secondly, when parameter variations or external disturbances occur, an augmented signal will be generated by FLC mechanism to preserve the desired model following control performance. The effectiveness and robustness of the proposed controller is demonstrated by some simulation results.

  6. Marginal linearization method in modeling on fuzzy control systems

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Marginal linearization method in modeling on fuzzy control systems is proposed, which is to deal with the nonlinear model with variable coefficients. The method can turn a nonlinear model with variable coefficients into a linear model with variable coefficients in the way that the membership functions of the fuzzy sets in fuzzy partitions of the universes are changed from triangle waves into rectangle waves. However, the linearization models are incomplete in their forms because of their lacking some items. For solving this problem, joint approximation by using linear models is introduced. The simulation results show that marginal linearization models are of higher approximation precision than their original nonlinear models.

  7. Support vector machine-based multi-model predictive control

    Institute of Scientific and Technical Information of China (English)

    Zhejing BA; Youxian SUN

    2008-01-01

    In this paper,a support vector machine-based multi-model predictive control is proposed,in which SVM classification combines well with SVM regression.At first,each working environment is modeled by SVM regression and the support vector machine network-based model predictive control(SVMN-MPC)algorithm corresponding to each environment is developed,and then a multi-class SVM model is established to recognize multiple operating conditions.As for control,the current environment is identified by the multi-class SVM model and then the corresponding SVMN.MPCcontroller is activated at each sampling instant.The proposed modeling,switching and controller design is demonstrated in simulation results.

  8. 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

    to production is crucial. We present a model for a house with a heat pump used for supplying thermal energy to a floor heating system. The model is a linear state space model and the resulting controller is an Economic MPC formulated as a linear program. The model includes forecasts of both weather...

  9. Model independent control of lightly damped noise/vibration systems.

    Science.gov (United States)

    Yuan, Jing

    2008-07-01

    Feedforward control is a popular strategy of active noise/vibration control. In well-damped noise/vibration systems, path transfer functions from actuators to sensors can be modeled by finite impulse response (FIR) filters with negligible errors. It is possible to implement noninvasive model independent feedforward control by a recently proposed method called orthogonal adaptation. In lightly damped noise/vibration systems, however, path transfer functions have infinite impulse responses (IIRs) that cause difficulties in design and implementation of broadband feedforward controllers. A major source of difficulties is model error if IIR path transfer functions are approximated by FIR filters. In general, active control performance deteriorates as model error increases. In this study, a new method is proposed to design and implement model independent feedforward controllers for broadband in lightly damped noise/vibration systems. It is shown analytically that the proposed method is able to drive the convergence of a noninvasive model independent feedforward controller to improve broadband control in lightly damped noise/vibration systems. The controller is optimized in the minimum H2 norm sense. Experiment results are presented to verify the analytical results.

  10. Iterative learning control algorithm for spiking behavior of neuron model

    Science.gov (United States)

    Li, Shunan; Li, Donghui; Wang, Jiang; Yu, Haitao

    2016-11-01

    Controlling neurons to generate a desired or normal spiking behavior is the fundamental building block of the treatment of many neurologic diseases. The objective of this work is to develop a novel control method-closed-loop proportional integral (PI)-type iterative learning control (ILC) algorithm to control the spiking behavior in model neurons. In order to verify the feasibility and effectiveness of the proposed method, two single-compartment standard models of different neuronal excitability are specifically considered: Hodgkin-Huxley (HH) model for class 1 neural excitability and Morris-Lecar (ML) model for class 2 neural excitability. ILC has remarkable advantages for the repetitive processes in nature. To further highlight the superiority of the proposed method, the performances of the iterative learning controller are compared to those of classical PI controller. Either in the classical PI control or in the PI control combined with ILC, appropriate background noises are added in neuron models to approach the problem under more realistic biophysical conditions. Simulation results show that the controller performances are more favorable when ILC is considered, no matter which neuronal excitability the neuron belongs to and no matter what kind of firing pattern the desired trajectory belongs to. The error between real and desired output is much smaller under ILC control signal, which suggests ILC of neuron’s spiking behavior is more accurate.

  11. Linear control theory for gene network modeling.

    Science.gov (United States)

    Shin, Yong-Jun; Bleris, Leonidas

    2010-09-16

    Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

  12. Modeling and control of precision actuators

    CERN Document Server

    Kiong, Tan Kok

    2013-01-01

    IntroductionGrowing Interest in Precise ActuatorsTypes of Precise ActuatorsApplications of Precise ActuatorsNonlinear Dynamics and ModelingHysteresisCreepFrictionForce RipplesIdentification and Compensation of Preisach Hysteresis in Piezoelectric ActuatorsSVD-Based Identification and Compensation of Preisach HysteresisHigh-Bandwidth Identification and Compensation of Hysteretic Dynamics in Piezoelectric ActuatorsConcluding RemarksIdentification and Compensation of Frict

  13. A dynamic epidemic control model on uncorrelated complex networks

    Institute of Scientific and Technical Information of China (English)

    Pei Wei-Dong; Chen Zeng-Qiang; Yuan Zhu-Zhi

    2008-01-01

    In this paper,a dynamic epidemic control model on the uncorrelated complex networks is proposed.By means of theoretical analysis,we found that the new model has a similar epidemic threshold as that of the susceptible-infectedrecovered (SIR) model on the above networks,but it can reduce the prevalence of the infected individuals remarkably.This result may help us understand epidemic spreading phenomena on real networks and design appropriate strategies to control infections.

  14. Uncertainty Quantification in Control Problems for Flocking Models

    Directory of Open Access Journals (Sweden)

    Giacomo Albi

    2015-01-01

    Full Text Available The optimal control of flocking models with random inputs is investigated from a numerical point of view. The effect of uncertainty in the interaction parameters is studied for a Cucker-Smale type model using a generalized polynomial chaos (gPC approach. Numerical evidence of threshold effects in the alignment dynamic due to the random parameters is given. The use of a selective model predictive control permits steering of the system towards the desired state even in unstable regimes.

  15. Flexible robot control: Modeling and experiments

    Science.gov (United States)

    Oppenheim, Irving J.; Shimoyama, Isao

    1989-01-01

    Described here is a model and its use in experimental studies of flexible manipulators. The analytical model uses the equivalent of Rayleigh's method to approximate the displaced shape of a flexible link as the static elastic displacement which would occur under end rotations as applied at the joints. The generalized coordinates are thereby expressly compatible with joint motions and rotations in serial link manipulators, because the amplitude variables are simply the end rotations between the flexible link and the chord connecting the end points. The equations for the system dynamics are quite simple and can readily be formulated for the multi-link, three-dimensional case. When the flexible links possess mass and (polar moment of) inertia which are small compared to the concentrated mass and inertia at the joints, the analytical model is exact and displays the additional advantage of reduction in system dimension for the governing equations. Four series of pilot tests have been completed. Studies on a planar single-link system were conducted at Carnegie-Mellon University, and tests conducted at Toshiba Corporation on a planar two-link system were then incorporated into the study. A single link system under three-dimensional motion, displaying biaxial flexure, was then tested at Carnegie-Mellon.

  16. Uniformed model of networked control systems with long time delay

    Institute of Scientific and Technical Information of China (English)

    Zhu Qixin; Liu Hongli; Hu Shousong

    2008-01-01

    Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems (NCS). The defining feature of an NCS is that information is exchanged using a network among control system components. Two new concepts including long time delay and short time delay are proposed.The sensor is almost always clock driven. The controller or the actuator is either clock driven or event driven. Four possible driving modes of networked control systems are presented. The open loop mathematic models of networked control systems with long time delay are developed when the system is driven by anyone of the four different modes.The uniformed modeling method of networked control systems with long time delay is proposed. The simulation results are given in the end.

  17. Principles of the Proposed Czech Postal Sector Price Control Model

    Directory of Open Access Journals (Sweden)

    Libor Švadlenka

    2009-01-01

    Full Text Available The paper deals with the postal sector control. It resultsfrom the control theory and proves the justifiability of control inthe postal sector. Within the price control it results from E U Directive97!67/EC requirements on this control and states individualtypes of price control focusing on ineffective price controlcurrently used in the Czech postal sector (especially withindomestic services and proposes a more effective method ofprice control. The paper also discusses the principles of the proposedmethod of price control of the Czech postal sector. It describesconcrete fulfilment of the price control model resultingfrom the price-cap and tariff formula RP I-X and concentrateson its quantitative expression. The application of the proposedmodel is carried out for a hypothetical period in the past (in orderto compare it with the current control system for letteritems tariff basket.

  18. Modelling of a PMSG Wind Turbine with Autonomous Control

    OpenAIRE

    Chia-Nan Wang; Wen-Chang Lin; Xuan-Khoa Le

    2014-01-01

    The aim of this research is to model an autonomous control wind turbine driven permanent magnetic synchronous generator (PMSG) which feeds alternating current (AC) power to the utility grid. Furthermore, this research also demonstrates the effects and the efficiency of PMSG wind turbine which is integrated by autonomous controllers. In order for well autonomous control, two voltage source inverters are used to control wind turbine connecting with the grid. The generator-side inverter is used ...

  19. State Predictive Model Following Control System for Linear Time Delays

    Institute of Scientific and Technical Information of China (English)

    Da-Zhong Wang; Shu-Jing Wu; Shigenori Okubo

    2009-01-01

    In this paper, we propose a new state predictive model following control system (MFCS). The considered system has linear time delays. With the MFCS method, we obtain a simple input control law. The bounded property of the internal states for the control is given and the utility of this control design is guaranteed. Finally, an example is given to illustrate the effectiveness of the proposed method.

  20. Probabilistic Priority Message Checking Modeling Based on Controller Area Networks

    Science.gov (United States)

    Lin, Cheng-Min

    Although the probabilistic model checking tool called PRISM has been applied in many communication systems, such as wireless local area network, Bluetooth, and ZigBee, the technique is not used in a controller area network (CAN). In this paper, we use PRISM to model the mechanism of priority messages for CAN because the mechanism has allowed CAN to become the leader in serial communication for automobile and industry control. Through modeling CAN, it is easy to analyze the characteristic of CAN for further improving the security and efficiency of automobiles. The Markov chain model helps us to model the behaviour of priority messages.

  1. Modeling Pediatric Brain Trauma: Piglet Model of Controlled Cortical Impact.

    Science.gov (United States)

    Pareja, Jennifer C Munoz; Keeley, Kristen; Duhaime, Ann-Christine; Dodge, Carter P

    2016-01-01

    The brain has different responses to traumatic injury as a function of its developmental stage. As a model of injury to the immature brain, the piglet shares numerous similarities in regards to morphology and neurodevelopmental sequence compared to humans. This chapter describes a piglet scaled focal contusion model of traumatic brain injury that accounts for the changes in mass and morphology of the brain as it matures, facilitating the study of age-dependent differences in response to a comparable mechanical trauma.

  2. Modelling and controller design for a UV disinfection plant

    NARCIS (Netherlands)

    van Mourik, S.; Geurts, Bernardus J.; Zwart, Heiko J.; Keesman, Karel

    A mathematical model describing fluid flow and concentration dynamics of micro-organisms inside a UV photoreactor is developed. Using physical arguments and techniques from system theory, we approximate this model by a first order linear one. For this reduced model, we design a controller. The

  3. Modelling and controller design for a UV disinfection plant

    NARCIS (Netherlands)

    van Mourik, S.; Geurts, Bernardus J.; Zwart, Heiko J.

    2007-01-01

    A mathematical model describing fluid flow and concentration dynamics of microorganisms inside a UV photoreactor is developed. Using physical arguments and techniques from system theory, we approximate this model by a first order linear one. For this reduced model, we design a controller. The

  4. Integration of Design and Control through Model Analysis

    DEFF Research Database (Denmark)

    Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay;

    2002-01-01

    A systematic computer aided analysis of the process model is proposed as a pre-solution step for integration of design and control problems. The process model equations are classified in terms of balance equations, constitutive equations and conditional equations. Analysis of the phenomena models...... (structure selection) issues for the integrated problems are considered. (C) 2002 Elsevier Science Ltd. All rights reserved....

  5. Modeling and Control of Primary Parallel Isolated Boost Converter

    DEFF Research Database (Denmark)

    Mira Albert, Maria del Carmen; Hernandez Botella, Juan Carlos; Sen, Gökhan

    2012-01-01

    In this paper state space modeling and closed loop controlled operation have been presented for primary parallel isolated boost converter (PPIBC) topology as a battery charging unit. Parasitic resistances have been included to have an accurate dynamic model. The accuracy of the model has been tes...

  6. Modeling and control of water disinfection process in annular photoreactors

    NARCIS (Netherlands)

    Keesman, K.J.; Vries, D.; Mourik, van S.; Zwart, H.J.; Tzafestas, S.

    2007-01-01

    As an alternative or addition to complex physical modeling, in this paper transfer function models of the disinfection process in annular photoreactors under different flow conditions are derived. These transfer function models allow an analytical evaluation of the system dynamics and the control st

  7. Modelling and controller design for a UV disinfection plant

    NARCIS (Netherlands)

    Mourik, van S.; Geurts, B.J.; Zwart, H.J.; Keesman, K.J.

    2010-01-01

    A mathematical model describing fluid flow and concentration dynamics of micro-organisms inside a UV photoreactor is developed. Using physical arguments and techniques from system theory, we approximate this model by a first order linear one. For this reduced model, we design a controller. The contr

  8. Modeling and nonlinear heading control for sailing yachts

    DEFF Research Database (Denmark)

    Xiao, Lin; Jouffroy, Jerome

    2011-01-01

    This paper presents a study on the development and testing of a model-based heading controller for a sailing yacht. Using Fossen's compact notation for marine vehicles, we first describe a nonlinear 4-DOF dynamic model for a sailing yacht, including roll. Starting from this model, we then design ...

  9. Modeling and nonlinear heading control for sailing yachts

    DEFF Research Database (Denmark)

    Xiao, Lin; Jouffroy, Jerome

    2014-01-01

    This paper presents a study on the development and testing of a model-based heading controller for a sailing yacht. Using Fossen’s compact notation for marine vehicles, we first describe a nonlinear four-degree-of-freedom (DOF) dynamic model for a sailing yacht, including roll. Our model also inc...

  10. Robust Control for the Segway with Unknown Control Coefficient and Model Uncertainties

    Directory of Open Access Journals (Sweden)

    Byung Woo Kim

    2016-06-01

    Full Text Available The Segway, which is a popular vehicle nowadays, is an uncertain nonlinear system and has an unknown time-varying control coefficient. Thus, we should consider the unknown time-varying control coefficient and model uncertainties to design the controller. Motivated by this observation, we propose a robust control for the Segway with unknown control coefficient and model uncertainties. To deal with the time-varying unknown control coefficient, we employ the Nussbaum gain technique. We introduce an auxiliary variable to solve the underactuated problem. Due to the prescribed performance control technique, the proposed controller does not require the adaptive technique, neural network, and fuzzy logic to compensate the uncertainties. Therefore, it can be simple. From the Lyapunov stability theory, we prove that all signals in the closed-loop system are bounded. Finally, we provide the simulation results to demonstrate the effectiveness of the proposed control scheme.

  11. Neighboring extremal optimal control design including model mismatch errors

    Energy Technology Data Exchange (ETDEWEB)

    Kim, T.J. [Sandia National Labs., Albuquerque, NM (United States); Hull, D.G. [Texas Univ., Austin, TX (United States). Dept. of Aerospace Engineering and Engineering Mechanics

    1994-11-01

    The mismatch control technique that is used to simplify model equations of motion in order to determine analytic optimal control laws is extended using neighboring extremal theory. The first variation optimal control equations are linearized about the extremal path to account for perturbations in the initial state and the final constraint manifold. A numerical example demonstrates that the tuning procedure inherent in the mismatch control method increases the performance of the controls to the level of a numerically-determined piecewise-linear controller.

  12. Distributed Software Development Modelling and Control Framework

    Directory of Open Access Journals (Sweden)

    Yi Feng

    2012-10-01

    Full Text Available With the rapid progress of internet technology, more and more software projects adopt e-development tofacilitate the software development process in a world-wide context. However, distributed softwaredevelopment activity itself is a complex orchestration. It involves many people working together without thebarrier of time and space difference. Therefore, how to efficiently monitor and control software edevelopmentin a global perspective becomes an important issue for any internet-based softwaredevelopment project. In this paper, we present a novel approach to tackle this crucial issue by means ofcontrolling e-development process, collaborative task progress and communication quality. Meanwhile, wealso present our e-development supporting environment prototype: Caribou, to demonstrate the viability ofour approach.

  13. Cognitive control in majority search: A computational modeling approach

    Directory of Open Access Journals (Sweden)

    Hongbin eWang

    2011-02-01

    Full Text Available Despite the importance of cognitive control in many cognitive tasks involving uncertainty, the computational mechanisms of cognitive control in response to uncertainty remain unclear. In this study, we develop biologically realistic neural network models to investigate the instantiation of cognitive control in a majority function task, where one determines the category to which the majority of items in a group belong. Two models are constructed, both of which include the same set of modules representing task-relevant brain functions and share the same model structure. However, with a critical change of a model parameter setting, the two models implement two different underlying algorithms: one for grouping search (where a subgroup of items are sampled and re-sampled until a congruent sample is found and the other for self-terminating search (where the items are scanned and counted one-by-one until the majority is decided. The two algorithms hold distinct implications for the involvement of cognitive control. The modeling results show that while both models are able to perform the task, the grouping search model fit the human data better than the self-terminating search model. An examination of the dynamics underlying model performance reveals how cognitive control might be instantiated in the brain via the V4-ACC-LPFC-IPS loop for computing the majority function.

  14. Cognitive control in majority search: a computational modeling approach.

    Science.gov (United States)

    Wang, Hongbin; Liu, Xun; Fan, Jin

    2011-01-01

    Despite the importance of cognitive control in many cognitive tasks involving uncertainty, the computational mechanisms of cognitive control in response to uncertainty remain unclear. In this study, we develop biologically realistic neural network models to investigate the instantiation of cognitive control in a majority function task, where one determines the category to which the majority of items in a group belong. Two models are constructed, both of which include the same set of modules representing task-relevant brain functions and share the same model structure. However, with a critical change of a model parameter setting, the two models implement two different underlying algorithms: one for grouping search (where a subgroup of items are sampled and re-sampled until a congruent sample is found) and the other for self-terminating search (where the items are scanned and counted one-by-one until the majority is decided). The two algorithms hold distinct implications for the involvement of cognitive control. The modeling results show that while both models are able to perform the task, the grouping search model fit the human data better than the self-terminating search model. An examination of the dynamics underlying model performance reveals how cognitive control might be instantiated in the brain for computing the majority function.

  15. A Composite Model Predictive Control Strategy for Furnaces

    Institute of Scientific and Technical Information of China (English)

    Hao Zang; Hongguang Li; Jingwen Huang; Jia Wang

    2014-01-01

    Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimi-zation of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control (CMPC) strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The control ers connected with two kinds of communi-cation networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reason-able CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively.

  16. Variable structure control of nonlinear systems through simplified uncertain models

    Science.gov (United States)

    Sira-Ramirez, Hebertt

    1986-01-01

    A variable structure control approach is presented for the robust stabilization of feedback equivalent nonlinear systems whose proposed model lies in the same structural orbit of a linear system in Brunovsky's canonical form. An attempt to linearize exactly the nonlinear plant on the basis of the feedback control law derived for the available model results in a nonlinearly perturbed canonical system for the expanded class of possible equivalent control functions. Conservatism tends to grow as modeling errors become larger. In order to preserve the internal controllability structure of the plant, it is proposed that model simplification be carried out on the open-loop-transformed system. As an example, a controller is developed for a single link manipulator with an elastic joint.

  17. Provably Safe and Robust Learning-Based Model Predictive Control

    CERN Document Server

    Aswani, Anil; Sastry, S Shankar; Tomlin, Claire

    2011-01-01

    Controller design for systems typically faces a trade-off between robustness and performance, and the reliability of linear controllers has caused many control practitioners to focus on the former. However, there is a renewed interest in improving system performance to deal with growing energy and pollution constraints. This paper describes a learning-based model predictive control (MPC) scheme. The MPC provides deterministic guarantees on robustness and safety, and the learning is used to identify richer models of the system to improve controller performance. Our scheme uses a linear model with bounds on its uncertainty to construct invariant sets which help to provide the guarantees, and it can be generalized to other classes of models and to pseudo-spectral methods. This framework allows us to handle state and input constraints and optimize system performance with respect to a cost function. The learning occurs through the use of an oracle which returns the value and gradient of unmodeled dynamics at discr...

  18. Task Delegation Based Access Control Models for Workflow Systems

    Science.gov (United States)

    Gaaloul, Khaled; Charoy, François

    e-Government organisations are facilitated and conducted using workflow management systems. Role-based access control (RBAC) is recognised as an efficient access control model for large organisations. The application of RBAC in workflow systems cannot, however, grant permissions to users dynamically while business processes are being executed. We currently observe a move away from predefined strict workflow modelling towards approaches supporting flexibility on the organisational level. One specific approach is that of task delegation. Task delegation is a mechanism that supports organisational flexibility, and ensures delegation of authority in access control systems. In this paper, we propose a Task-oriented Access Control (TAC) model based on RBAC to address these requirements. We aim to reason about task from organisational perspectives and resources perspectives to analyse and specify authorisation constraints. Moreover, we present a fine grained access control protocol to support delegation based on the TAC model.

  19. Composite control for raymond mill based on model predictive control and disturbance observer

    Directory of Open Access Journals (Sweden)

    Dan Niu

    2016-03-01

    Full Text Available In the raymond mill grinding process, precise control of operating load is vital for the high product quality. However, strong external disturbances, such as variations of ore size and ore hardness, usually cause great performance degradation. It is not easy to control the current of raymond mill constant. Several control strategies have been proposed. However, most of them (such as proportional–integral–derivative and model predictive control reject disturbances just through feedback regulation, which may lead to poor control performance in the presence of strong disturbances. For improving disturbance rejection, a control method based on model predictive control and disturbance observer is put forward in this article. The scheme employs disturbance observer as feedforward compensation and model predictive control controller as feedback regulation. The test results illustrate that compared with model predictive control method, the proposed disturbance observer–model predictive control method can obtain significant superiority in disturbance rejection, such as shorter settling time and smaller peak overshoot under strong disturbances.

  20. Control Oriented Modeling of a De-oiling Hydrocyclone

    DEFF Research Database (Denmark)

    Løhndorf, Petar Durdevic; Pedersen, Simon; Bram, Mads Valentin;

    2015-01-01

    Deoiling hydrocyclones are an important part of the downstream water treatment in offshore oil & gas production, they ensure a low discharge of oil and thus a higher yield of produced oil. This work investigates the possibility of developing a simple control-oriented model of a de....... There is a lack of a systematic and deep-insight analysis of the capability, stability and limitations of these control solutions, as there are few control-oriented models available for de-oiling hydrocyclone systems. This paper proposes a method of retrieving a set of simple 1st-order transfer function models......-oiling hydrocyclone based on experimental data that can support systematic analysis and control design of hydrocyclone systems. The most widely used control solution of a hydrocyclone is a Pressure Drop Ratio (PDR) control strategy, which is often empirically designed and experimentally tuned in a case-by-case manner...

  1. Power electronic converters modeling and control with case studies

    CERN Document Server

    Bacha, Seddik; Bratcu, Antoneta Iuliana

    2014-01-01

    Modern power electronic converters are involved in a very broad spectrum of applications: switched-mode power supplies, electrical-machine-motion-control, active power filters, distributed power generation, flexible AC transmission systems, renewable energy conversion systems and vehicular technology, among them. Power Electronics Converters Modeling and Control teaches the reader how to analyze and model the behavior of converters and so to improve their design and control. Dealing with a set of confirmed algorithms specifically developed for use with power converters, this text is in two parts: models and control methods. The first is a detailed exposition of the most usual power converter models: ·        switched and averaged models; ·        small/large-signal models; and ·        time/frequency models. The second focuses on three groups of control methods: ·        linear control approaches normally associated with power converters; ·        resonant controllers b...

  2. Modeling and simulation for train control system using cellular automata

    Institute of Scientific and Technical Information of China (English)

    LI; KePing; GAO; ZiYou; YANG; LiXing

    2007-01-01

    Train control system plays a key role in railway traffic. Its function is to manage and control the train movement on railway networks. In our previous works, based on the cellular automata (CA) model, we proposed several models and algorithms for simulating the train movement under different control system conditions. However, these models are only suitable for some simple traffic conditions. Some basic factors, which are important for train movement, are not considered. In this paper, we extend these models and algorithms and give a unified formula. Using the proposed method, we analyze and discuss the space-time diagram of railway traffic flow and the trajectories of the train movement. The numerical simulation and analytical results demonstrate that the unified CA model is an effective tool for simulating the train control system.

  3. Modeling, Prediction, and Control of Heating Temperature for Tube Billet

    Directory of Open Access Journals (Sweden)

    Yachun Mao

    2015-01-01

    Full Text Available Annular furnaces have multivariate, nonlinear, large time lag, and cross coupling characteristics. The prediction and control of the exit temperature of a tube billet are important but difficult. We establish a prediction model for the final temperature of a tube billet through OS-ELM-DRPLS method. We address the complex production characteristics, integrate the advantages of PLS and ELM algorithms in establishing linear and nonlinear models, and consider model update and data lag. Based on the proposed model, we design a prediction control algorithm for tube billet temperature. The algorithm is validated using the practical production data of Baosteel Co., Ltd. Results show that the model achieves the precision required in industrial applications. The temperature of the tube billet can be controlled within the required temperature range through compensation control method.

  4. A control theory model for human decision making

    Science.gov (United States)

    Levison, W. H.

    1972-01-01

    The optimal control model for pilot-vehicle systems has been extended to handle certain types of human decision tasks. The model for decision making incorporates the observation noise, optimal estimation, and prediction concepts that form the basis of the model for control behavior. Experiments are described for the following task situations: (1) single decision tasks; (2) two decision tasks; and (3) simultaneous manual control and decision tasks. Using fixed values for model parameters, single-task and two-task decision performance scores to within an accuracy of 10 percent can be predicted. The experiment on simultaneous control and decision indicates the presence of task interference in this situation, but the results are not adequate to allow a conclusive test of the predictive capability of the model.

  5. A control-theory model for human decision-making

    Science.gov (United States)

    Levison, W. H.; Tanner, R. B.

    1971-01-01

    A model for human decision making is an adaptation of an optimal control model for pilot/vehicle systems. The models for decision and control both contain concepts of time delay, observation noise, optimal prediction, and optimal estimation. The decision making model was intended for situations in which the human bases his decision on his estimate of the state of a linear plant. Experiments are described for the following task situations: (a) single decision tasks, (b) two-decision tasks, and (c) simultaneous manual control and decision making. Using fixed values for model parameters, single-task and two-task decision performance can be predicted to within an accuracy of 10 percent. Agreement is less good for the simultaneous decision and control situation.

  6. Modeling, Robust Control, and Experimental Validation of a Supercavitating Vehicle

    Science.gov (United States)

    Escobar Sanabria, David

    This dissertation considers the mathematical modeling, control under uncertainty, and experimental validation of an underwater supercavitating vehicle. By traveling inside a gas cavity, a supercavitating vehicle reduces hydrodynamic drag, increases speed, and minimizes power consumption. The attainable speed and power efficiency make these vehicles attractive for undersea exploration, high-speed transportation, and defense. However, the benefits of traveling inside a cavity come with difficulties in controlling the vehicle dynamics. The main challenge is the nonlinear force that arises when the back-end of the vehicle pierces the cavity. This force, referred to as planing, leads to oscillatory motion and instability. Control technologies that are robust to planing and suited for practical implementation need to be developed. To enable these technologies, a low-order vehicle model that accounts for inaccuracy in the characterization of planing is required. Additionally, an experimental method to evaluate possible pitfalls in the models and controllers is necessary before undersea testing. The major contribution of this dissertation is a unified framework for mathematical modeling, robust control synthesis, and experimental validation of a supercavitating vehicle. First, we introduce affordable experimental methods for mathematical modeling and controller testing under planing and realistic flow conditions. Then, using experimental observations and physical principles, we create a low-order nonlinear model of the longitudinal vehicle motion. This model quantifies the planing uncertainty and is suitable for robust controller synthesis. Next, based on the vehicle model, we develop automated tools for synthesizing controllers that deliver a certificate of performance in the face of nonlinear and uncertain planing forces. We demonstrate theoretically and experimentally that the proposed controllers ensure higher performance when the uncertain planing dynamics are

  7. The Robust Control Mixer Method for Reconfigurable Control Design By Using Model Matching Strategy

    DEFF Research Database (Denmark)

    Yang, Z.; Blanke, Mogens; Verhagen, M.

    2001-01-01

    This paper proposes a robust reconfigurable control synthesis method based on the combination of the control mixer method and robust H1 con- trol techniques through the model-matching strategy. The control mixer modules are extended from the conventional matrix-form into the LTI sys- tem form. By...

  8. A Reduced-Order Model for Structural Wave Control and the Concept of Degree of Controllability

    Institute of Scientific and Technical Information of China (English)

    王泉; 王大钧; 苏先樾

    1994-01-01

    This paper introduces the concept and criteria of controllability and degree of controllability for structural wave control, and advances a new approach to structural reduced-order model, which is similar to the constrained substructural method in dynamics, and is also the extension of the method of aggregation raised by Aoki. It has physical meaning and is easy to realize.

  9. The Robust Control Mixer Method for Reconfigurable Control Design By Using Model Matching Strategy

    DEFF Research Database (Denmark)

    Yang, Z.; Blanke, Mogens; Verhagen, M.

    2001-01-01

    This paper proposes a robust reconfigurable control synthesis method based on the combination of the control mixer method and robust H1 con- trol techniques through the model-matching strategy. The control mixer modules are extended from the conventional matrix-form into the LTI sys- tem form. By...... of one space robot arm system subjected to failures....

  10. Synthetical Control of AGC/LPC System Based on Neural Networks Internal Model Control

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    One synthetical control method of AGC/LPC system based on intelligence control theory-neural networks internal model control method is presented. Genetic algorithm (GA) is applied to optimize the parameters of the neural networks. Simulation results prove that this method is effective.

  11. A New Mathematical Modeling Technique for Pull Production Control Systems

    Directory of Open Access Journals (Sweden)

    O. Srikanth

    2013-12-01

    Full Text Available The Kanban Control System widely used to control the release of parts of multistage manufacturing system operating under a pull production control system. Most of the work on Kanban Control System deals with multi-product manufacturing system. In this paper, we are proposing a regression modeling technique in a multistage manufacturing system is to be coordinates the release of parts into each stage of the system with the arrival of customer demands for final products. And also comparing two variants stages of the Kanban Control System model and combines with mathematical and Simulink model for the production coordination of parts in an assembly manufacturing systems. In both variants, the production of a new subassembly is authorized only when an assembly Kanban is available. Assembly kanbans become available when finished product is consumed. A simulation environment for the product line system has to generate with the proposed model and the mathematical model have to give implementation against the simulation model in the working platform of MATLAB. Both the simulation and model outputs have provided an in depth analysis of each of the resulting control system for offering model of a product line system.

  12. Tensor Product Model Transformation Based Adaptive Integral-Sliding Mode Controller: Equivalent Control Method

    Directory of Open Access Journals (Sweden)

    Guoliang Zhao

    2013-01-01

    Full Text Available This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

  13. Tensor product model transformation based adaptive integral-sliding mode controller: equivalent control method.

    Science.gov (United States)

    Zhao, Guoliang; Sun, Kaibiao; Li, Hongxing

    2013-01-01

    This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model.

  14. Model based control for run-of-river system. Part 2: Comparison of control structures

    Directory of Open Access Journals (Sweden)

    Liubomyr Vytvytskyi

    2015-10-01

    Full Text Available Optimal operation and control of a run-of-river hydro power plant depend on good knowledge of the elements of the plant in the form of models. Both the control architecture of the system, i.e. the choice of inputs and outputs, and to what degree a model is used, will affect the achievable control performance. Here, a model of a river reach based on the Saint Venant equations for open channel flow illustrates the dynamics of the run-of-river system. The hyperbolic partial differential equations are discretized using the Kurganov-Petrova central upwind scheme - see Part I for details. A comparison is given of achievable control performance using two alternative control signals: the inlet or the outlet volumetric flow rates to the system, in combination with a number of different control structures such as PI control, PI control with Smith predictor, and predictive control. The control objective is to keep the level just in front of the dam as high as possible, and with little variation in the level to avoid overflow over the dam. With a step change in the volumetric inflow to the river reach (disturbance and using the volumetric outflow as the control signal, PI control gives quite good performance. Model predictive control (MPC gives superior control in the sense of constraining the variation in the water level, at a cost of longer computational time and thus constraints on possible sample time. Details on controller tuning are given. With volumetric inflow to the river reach as control signal and outflow (production as disturbance, this introduces a considerable time delay in the control signal. Because of nonlinearity in the system (varying time delay, etc., it is difficult to achieve stable closed loop performance using a simple PI controller. However, by combining a PI controller with a Smith predictor based on a simple integrator + fixed time delay model, stable closed loop operation is possible with decent control performance. Still, an MPC

  15. ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.

  16. Developments in model-based optimization and control distributed control and industrial applications

    CERN Document Server

    Grancharova, Alexandra; Pereira, Fernando

    2015-01-01

    This book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization. The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on: · complexity and structure in model predictive control (MPC); · collaborative MPC; · distributed MPC; · optimization-based analysis and desi...

  17. Modeling Open Software Architectures of Robot Controllers: A Brief Survey of Modeling Methods and Developing Methods

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Openness is one of the features of modern robot controllers. Although many modeling technologies have been discussed to model and develop open robot controllers, the focus is always on modeling methodologies. Meanwhile, the relations between the former and the latter are usually ignored. According to the general software architecture of open robot controllers, this paper discusses modeling and developing methods. And the relationships between the typical ones are also analyzed.

  18. Fuzzy Universal Model Approximator for Distributed Solar Collector Field Control

    KAUST Repository

    Elmetennani, Shahrazed

    2014-07-01

    This paper deals with the control of concentrating parabolic solar collectors by forcing the outlet oil temperature to track a set reference. A fuzzy universal approximate model is introduced in order to accurately reproduce the behavior of the system dynamics. The proposed model is a low order state space representation derived from the partial differential equation describing the oil temperature evolution using fuzzy transform theory. The resulting set of ordinary differential equations simplifies the system analysis and the control law design and is suitable for real time control implementation. Simulation results show good performance of the proposed model.

  19. Direct Model Reference Adaptive Control for a Magnetic Bearing

    Energy Technology Data Exchange (ETDEWEB)

    Durling, Mike [Rensselaer Polytechnic Inst., Troy, NY (United States)

    1999-11-01

    A Direct Model Reference Adaptive Controller (DMRAC) is applied to a magnetic bearing test stand. The bearing of interest is the MBC 500 Magnetic Bearing System manufactured by Magnetic Moments, LLC. The bearing model is presented in state space form and the system transfer function is measured directly using a closed-loop swept sine technique. Next, the bearing models are used to design a phase-lead controller, notch filter and then a DMRAC. The controllers are tuned in simulations and finally are implemented using a combination of MATLAB, SIMULINK and dSPACE. The results show a successful implementation of a DMRAC on the magnetic bearing hardware.

  20. Stochastic wind turbine modeling for individual pitch control

    DEFF Research Database (Denmark)

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

    2009-01-01

    By pitching the blades of a wind turbine individually it is possible to attenuate the asymmetric loads caused by a non-uniform wind field - this is denoted individual pitch control. In this work we investigate how to set up a simplified stochastic and deterministic description of the wind...... and a simplified description of the aerodynamics with sufficient detail to design model-based individual pitch controllers. Combined with a simplified model of the wind turbine, we exemplify how to use the model elements to systematically design an individual pitch controller. The design is investigated...

  1. Predictive control applied to an evaporator mathematical model

    Directory of Open Access Journals (Sweden)

    Daniel Alonso Giraldo Giraldo

    2010-07-01

    Full Text Available This paper outlines designing a predictive control model (PCM applied to a mathematical model of a falling film evaporator with mechanical steam compression like those used in the dairy industry. The controller was designed using the Connoisseur software package and data gathered from the simulation of a non-linear mathematical model. A control law was obtained from minimising a cost function sublect to dynamic system constraints, using a quadratic programme (QP algorithm. A linear programming (LP algorithm was used for finding a sub-optimal operation point for the process in stationary state.

  2. Modeling and Control of a Bending Backwards Industrial Robot

    OpenAIRE

    Wernholt, Erik; Östring, Måns

    2003-01-01

    In this work we have looked at various parts of modeling of robots. First the rigid body motion is studied, spanning from kinematics to dynamics and path and trajectory generation. We have also looked into how to extend the rigid body model with flexible gear-boxes and how this could be incorporated with Robotics Toolbox. A very simple feedforward control based on the rigid model is applied in addition to PID control and in the simulations the overshoot is halved compared to only PID control....

  3. Dynamic modeling, simulation and control of energy generation

    CERN Document Server

    Vepa, Ranjan

    2013-01-01

    This book addresses the core issues involved in the dynamic modeling, simulation and control of a selection of energy systems such as gas turbines, wind turbines, fuel cells and batteries. The principles of modeling and control could be applied to other non-convention methods of energy generation such as solar energy and wave energy.A central feature of Dynamic Modeling, Simulation and Control of Energy Generation is that it brings together diverse topics in thermodynamics, fluid mechanics, heat transfer, electro-chemistry, electrical networks and electrical machines and focuses on their appli

  4. Economic Model Predictive Control for Spray Drying Plants

    DEFF Research Database (Denmark)

    Petersen, Lars Norbert

    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...

  5. 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.

  6. Semiotic aspects of control and modeling relations in complex systems

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, C.

    1996-08-01

    A conceptual analysis of the semiotic nature of control is provided with the goal of elucidating its nature in complex systems. Control is identified as a canonical form of semiotic relation of a system to its environment. As a form of constraint between a system and its environment, its necessary and sufficient conditions are established, and the stabilities resulting from control are distinguished from other forms of stability. These result from the presence of semantic coding relations, and thus the class of control systems is hypothesized to be equivalent to that of semiotic systems. Control systems are contrasted with models, which, while they have the same measurement functions as control systems, do not necessarily require semantic relations because of the lack of the requirement of an interpreter. A hybrid construction of models in control systems is detailed. Towards the goal of considering the nature of control in complex systems, the possible relations among collections of control systems are considered. Powers arguments on conflict among control systems and the possible nature of control in social systems are reviewed, and reconsidered based on our observations about hierarchical control. Finally, we discuss the necessary semantic functions which must be present in complex systems for control in this sense to be present at all.

  7. Wind power electric systems modeling, simulation and control

    CERN Document Server

    Rekioua, Djamila

    2014-01-01

    The book helps readers understand key concepts in standalone and grid connected wind energy systems and features analysis into the modeling and optimization of commonly used configurations through the implementation of different control strategies.Utilizing several electrical machinery control approaches, such as vector control and direct torque control 'Wind Power Electric Systems' equips readers with the means to understand, assess and develop their own wind energy systems and to evaluate the performance of such systems.Mathematical models are provided for each system and a corresponding MAT

  8. 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...... 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....

  9. Control architecture of power systems: Modeling of purpose and function

    DEFF Research Database (Denmark)

    Heussen, Kai; Saleem, Arshad; Lind, Morten

    2009-01-01

    for semantically consistent modeling of control architecture is presented. The method, called Multilevel Flow Modeling (MFM), is applied to the case of system balancing. It was found that MFM is capable of capturing implicit control knowledge, which is otherwise difficult to formalize. The method has possible...... of power systems and it is necessary to identify requirements and functions. How does new control architecture fit with the old architecture? How can power system functions be specified independent of technology? What is the purpose of control in power systems? In this paper, a method suitable...

  10. Model algorithm control using neural networks for input delayed nonlinear control system

    Institute of Scientific and Technical Information of China (English)

    Yuanliang Zhang; Kil To Chong

    2015-01-01

    The performance of the model algorithm control method is partial y based on the accuracy of the system’s model. It is diffi-cult to obtain a good model of a nonlinear system, especial y when the nonlinearity is high. Neural networks have the ability to“learn”the characteristics of a system through nonlinear mapping to rep-resent nonlinear functions as wel as their inverse functions. This paper presents a model algorithm control method using neural net-works for nonlinear time delay systems. Two neural networks are used in the control scheme. One neural network is trained as the model of the nonlinear time delay system, and the other one pro-duces the control inputs. The neural networks are combined with the model algorithm control method to control the nonlinear time delay systems. Three examples are used to il ustrate the proposed control method. The simulation results show that the proposed control method has a good control performance for nonlinear time delay systems.

  11. Neural Modeling and Control of Diesel Engine with Pollution Constraints

    CERN Document Server

    Ouladsine, Mustapha; Dovifaaz, Xavier; 10.1007/s10846-005-3806-y

    2009-01-01

    The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identi?cation and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are ?exible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The present...

  12. Development of a trajectory following vehicle control model

    Directory of Open Access Journals (Sweden)

    Erdem Uzunsoy

    2016-05-01

    Full Text Available Determination of the handling properties of a vehicle may be restrictive in some situations. A vehicle model coupled with a driver model may be necessary and even unavoidable to analyse the real road behaviour in the most basic form. Therefore, a fuzzy logic–based controller has been investigated for potential application in modelling driver. Using some particular and limited number of information from characteristics of human driving operation, the model aims to provide any flexible vehicle path reliably. It generates the vehicle’s trajectory through a number of specified points through which the vehicle must pass. The controller was modified to account for peripheral vision characteristic of human eye, as an input. The simulation is carried out in the MATLAB© programming environment using a Simulink© vehicle model. Both longitudinal and lateral controls were applied in the study. This article adds novel approaches to the limited existing published work on driver steering model using fuzzy logic.

  13. Train Control System Formalization Modeling oriented Movement Authority

    Directory of Open Access Journals (Sweden)

    Xiaoming Wang

    2012-09-01

    Full Text Available Chinese Train Control System-3(CTCS-3 was integrated via various control system devices, assurance of CTCS-3 system transmission probability relied on empirical judgment, it is necessary to form its formalization to support integration for system stability of the whole CTCS-3. Movement Authority(MA acts on the whole information process of CTCS-3 to control train, its process properties can be as the reflection of CTCS probability. Aiming at that,  paper selected MA as the objective, proposed MA-oriented CTCS-3 formalization modeling. Paper designed generation and transmission algorithms of MA, formed MA computation models for application functions. Based on computation models, paper constructed MA hierarchical Colored Petri Nets(CPN models, and completed MA timed CPN model, the report and experimental result demonstrate that the model proposed is effective and can reflect CTCS-3 system properties accurately. 

  14. Robust Model Predictive Control of a Wind Turbine

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...

  15. Modeling and control of fuel cell systems and fuel processors

    Science.gov (United States)

    Pukrushpan, Jay Tawee

    Fuel cell systems offer clean and efficient energy production and are currently under intensive development by several manufacturers for both stationary and mobile applications. The viability, efficiency, and robustness of this technology depend on understanding, predicting, and controlling the unique transient behavior of the fuel cell system. In this thesis, we employ phenomenological modeling and multivariable control techniques to provide fast and consistent system dynamic behavior. Moreover, a framework for analyzing and evaluating different control architectures and sensor sets is provided. Two fuel cell related control problems are investigated in this study, namely, the control of the cathode oxygen supply for a high-pressure direct hydrogen Fuel Cell System (FCS) and control of the anode hydrogen supply from a natural gas Fuel Processor System (FPS). System dynamic analysis and control design is carried out using model-based linear control approaches. A system level dynamic model suitable for each control problem is developed from physics-based component models. The transient behavior captured in the model includes flow characteristics, inertia dynamics, lumped-volume manifold filling dynamics, time evolving spatially-homogeneous reactant pressure or mole fraction, membrane humidity, and the Catalytic Partial Oxidation (CPOX) reactor temperature. The goal of the FCS control problem is to effectively regulate the oxygen concentration in the cathode by quickly and accurately replenishing oxygen depleted during power generation. The features and limitations of different control configurations and the effect of various measurement on the control performance are examined. For example, an observability analysis suggests using the stack voltage measurement as feedback to the observer-based controller to improve the closed loop performance. The objective of the FPS control system is to regulate both the CPOX temperature and anode hydrogen concentration. Linear

  16. Control-oriented dynamic fuzzy model and predictive control for proton exchange membrane fuel cell stack

    Institute of Scientific and Technical Information of China (English)

    LI Xi; DENG Zhong-hua; CAO Guang-yi; ZHU Xin-jian; WEI Dong

    2006-01-01

    Proton exchange membrane fuel cell (PEMFC) stack temperature and cathode stoichiometric oxygen are very important control parameters. The performance and lifespan of PEMFC stack are greatly dependent on the parameters. So, in order to improve the performance index, tight control of two parameters within a given range and reducing their fluctuation are indispensable.However, control-oriented models and control strategies are very weak junctures in the PEMFC development. A predictive control algorithm was presented based on their model established by input-output data and operating experiences. It adjusts the operating temperature to 80 ℃. At the same time, the optimized region of stoichiometric oxygen is kept between 1.8-2.2. Furthermore, the control algorithm adjusts the variants quickly to the destination value and makes the fluctuation of the variants the least. According to the test results, compared with traditional fuzzy and PID controllers, the designed controller shows much better performance.

  17. Mean Value SI Engine Model for Control Studies

    DEFF Research Database (Denmark)

    Hendricks, Elbert; Sorenson, Spencer C

    1990-01-01

    This paper presents a mathematically simple nonlinear three state (three differential equation) dynamic model of an SI engine which has the same steady state accuracy as a typical dynamometer measurement of the engine over its entire speed/load operating range (± 2.0%). The model's accuracy for l....... The model can easily be run on a Personal Computer (PC) using a ordinary differential equation (ODE) integrating routine or package. This makes the model is useful for control system design and evaluation....

  18. Electrical Power Distribution and Control Modeling and Analysis

    Science.gov (United States)

    Fu, Johnny S.; Liffring, Mark; Mehdi, Ishaque S.

    2001-01-01

    This slide presentation reviews the use of Electrical Power Distribution and Control (EPD&C) Modeling and how modeling can support analysis. The presentation discusses using the EASY5 model to simulate and analyze the Space Shuttle Electric Auxiliary Power Unit. Diagrams of the model schematics are included, as well as graphs of the battery cell impedance, hydraulic load dynamics, and EPD&C response to hydraulic load variations.

  19. Modeling and control for closed environment plant production systems

    Science.gov (United States)

    Fleisher, David H.; Ting, K. C.; Janes, H. W. (Principal Investigator)

    2002-01-01

    A computer program was developed to study multiple crop production and control in controlled environment plant production systems. The program simulates crop growth and development under nominal and off-nominal environments. Time-series crop models for wheat (Triticum aestivum), soybean (Glycine max), and white potato (Solanum tuberosum) are integrated with a model-based predictive controller. The controller evaluates and compensates for effects of environmental disturbances on crop production scheduling. The crop models consist of a set of nonlinear polynomial equations, six for each crop, developed using multivariate polynomial regression (MPR). Simulated data from DSSAT crop models, previously modified for crop production in controlled environments with hydroponics under elevated atmospheric carbon dioxide concentration, were used for the MPR fitting. The model-based predictive controller adjusts light intensity, air temperature, and carbon dioxide concentration set points in response to environmental perturbations. Control signals are determined from minimization of a cost function, which is based on the weighted control effort and squared-error between the system response and desired reference signal.

  20. Integrated Modeling and Intelligent Control Methods of Grinding Process

    Directory of Open Access Journals (Sweden)

    Jie-sheng Wang

    2013-01-01

    Full Text Available The grinding process is a typical complex nonlinear multivariable process with strongly coupling and large time delays. Based on the data-driven modeling theory, the integrated modeling and intelligent control method of grinding process is carried out in the paper, which includes the soft-sensor model of economic and technique indexes, the optimized set-point model utilizing case-based reasoning, and the self-tuning PID decoupling controller. For forecasting the key technology indicators (grinding granularity and mill discharge rate of grinding process, an adaptive soft-sensor modeling method based on wavelet neural network optimized by the improved shuffled frog leaping algorithm (ISFLA is proposed. Then, a set point optimization control strategy of grinding process based on case-based reasoning (CBR method is adopted to obtain the optimized velocity set-point of ore feed and pump water feed in the grinding process controlled loops. Finally, a self-tuning PID decoupling controller optimized is used to control the grinding process. Simulation results and industrial application experiments clearly show the feasibility and effectiveness of control methods and satisfy the real-time control requirements of the grinding process.

  1. The Quadrotor Dynamic Modeling and Indoor Target Tracking Control Method

    Directory of Open Access Journals (Sweden)

    Dewei Zhang

    2014-01-01

    Full Text Available A reliable nonlinear dynamic model of the quadrotor is presented. The nonlinear dynamic model includes actuator dynamic and aerodynamic effect. Since the rotors run near a constant hovering speed, the dynamic model is simplified at hovering operating point. Based on the simplified nonlinear dynamic model, the PID controllers with feedback linearization and feedforward control are proposed using the backstepping method. These controllers are used to control both the attitude and position of the quadrotor. A fully custom quadrotor is developed to verify the correctness of the dynamic model and control algorithms. The attitude of the quadrotor is measured by inertia measurement unit (IMU. The position of the quadrotor in a GPS-denied environment, especially indoor environment, is estimated from the downward camera and ultrasonic sensor measurements. The validity and effectiveness of the proposed dynamic model and control algorithms are demonstrated by experimental results. It is shown that the vehicle achieves robust vision-based hovering and moving target tracking control.

  2. Active vibration control using state space LQG and internal model control methods

    DEFF Research Database (Denmark)

    Mørkholt, Jakob; Elliott, S.J.

    1998-01-01

    Two ways of designing discrete time robust H2-controllers for feedback broadband active vibration control are compared through computer simulations. The methods are based on different models of disturbance and plant transfer functions, but yield controllers with identical properties. Two simple...... ways of introducing robustness into the H2-design are compared, and finally an efficient way of designing a practical IIR-controller is proposed....

  3. Active vibration control using state space LQG and internal model control methods

    DEFF Research Database (Denmark)

    Mørkholt, Jakob; Elliott, S.J.

    1998-01-01

    Two ways of designing discrete time robust H2-controllers for feedback broadband active vibration control are compared through computer simulations. The methods are based on different models of disturbance and plant transfer functions, but yield controllers with identical properties. Two simple...... ways of introducing robustness into the H2-design are compared, and finally an efficient way of designing a practical IIR-controller is proposed....

  4. Boundary conditions control for a Shallow-Water model

    CERN Document Server

    Kazantsev, Eugene

    2012-01-01

    A variational data assimilation technique was used to estimate optimal discretization of interpolation operators and derivatives in the nodes adjacent to the rigid boundary. Assimilation of artificially generated observational data in the shallow-water model in a square box and assimilation of real observations in the model of the Black sea are discussed. It is shown in both experiments that controlling the discretization of operators near a rigid boundary can bring the model solution closer to observations as in the assimilation window and beyond the window. This type of control allows also to improve climatic variability of the model.

  5. Basic Model of a Control Assembly Drop in Nuclear Reactors

    Directory of Open Access Journals (Sweden)

    Radek BULÍN

    2013-06-01

    Full Text Available This paper is focused on the modelling and dynamic analysis of a nonlinear system representing a control assembly of the VVER 440/V213 nuclear reactor. A simple rigid body model intended for basic dynamic analyses is introduced. It contains the influences of the pressurized water and mainly the eects of possible control assembly contacts with guiding tubes inside the reactor. Another approach based on a complex multibody model is further described and the suitability of both modelling approaches is discussed.

  6. Study on modeling of vehicle dynamic stability and control technique

    Institute of Scientific and Technical Information of China (English)

    GAO Yun-ting; LI Pan-feng

    2012-01-01

    In order to solve the problem of enhancing the vehicle driving stability and safety,which has been the hot question researched by scientific and engineering in the vehicle industry,the new control method was investigated.After the analysis of tire moving characteristics and the vehicle stress analysis,the tire model based on the extension pacejka magic formula which combined longitudinal motion and lateral motion was developed and a nonlinear vehicle dynamical stability model with seven freedoms was made.A new model reference adaptive control project which made the slip angle and yaw rate of vehicle body as the output and feedback variable in adjusting the torque of vehicle body to control the vehicle stability was designed.A simulation model was also built in Matlab/Simulink to evaluate this control project.It was made up of many mathematical subsystem models mainly including the tire model module,the yaw moment calculation module,the center of mass parameter calculation module,tire parameter calculation module of multiple and so forth.The severe lane change simulation result shows that this vehicle model and the model reference adaptive control method have an excellent performance.

  7. COMPUTATIONALLY INTELLIGENT MODELLING AND CONTROL OF FLUIDIZED BED COMBUSTION PROCESS

    Directory of Open Access Journals (Sweden)

    Ivan T Ćirić

    2011-01-01

    Full Text Available In this paper modelling and control approaches for fluidized bed combustion process have been considered, that are based on the use of computational intelligence. Proposed adaptive neuro-fuzzy-genetic modelling and intelligent control strategies provide for efficient combining of available expert knowledge with experimental data. Firstly, based on the qualitative information on the desulphurization process, models of the SO2 emission in fluidized bed combustion have been developed, which provides for economical and efficient reduction of SO2 in FBC by estimation of optimal process parameters and by design of intelligent control systems based on defined emission models. Also, efficient fuzzy nonlinear FBC process modelling strategy by combining several linearized combustion models has been presented. Finally, fuzzy and conventional process control systems for fuel flow and primary air flow regulation based on developed models and optimized by genetic algorithms have also been developed. Obtained results indicate that computationally intelligent approach can be successfully applied for modelling and control of complex fluidized bed combustion process.

  8. Application of infinite model predictive control methodology to other advanced controllers.

    Science.gov (United States)

    Abu-Ayyad, M; Dubay, R; Hernandez, J M

    2009-01-01

    This paper presents an application of most recent developed predictive control algorithm an infinite model predictive control (IMPC) to other advanced control schemes. The IMPC strategy was derived for systems with different degrees of nonlinearity on the process gain and time constant. Also, it was shown that IMPC structure uses nonlinear open-loop modeling which is conducted while closed-loop control is executed every sampling instant. The main objective of this work is to demonstrate that the methodology of IMPC can be applied to other advanced control strategies making the methodology generic. The IMPC strategy was implemented on several advanced controllers such as PI controller using Smith-Predictor, Dahlin controller, simplified predictive control (SPC), dynamic matrix control (DMC), and shifted dynamic matrix (m-DMC). Experimental work using these approaches combined with IMPC was conducted on both single-input-single-output (SISO) and multi-input-multi-output (MIMO) systems and compared with the original forms of these advanced controllers. Computer simulations were performed on nonlinear plants demonstrating that the IMPC strategy can be readily implemented on other advanced control schemes providing improved control performance. Practical work included real-time control applications on a DC motor, plastic injection molding machine and a MIMO three zone thermal system.

  9. Modeling and controlling of a flexible hydraulic manipulator

    Institute of Scientific and Technical Information of China (English)

    LI Guang; WU Min

    2005-01-01

    A mathematical model was developed combining the dynamics of an Euler-Bernoulli beam, described by the assumed-mode method and hydraulic circuit dynamics. Only one matrix, termed drive Jacobian, was needed in the modeling of interaction between hydraulic circuit and flexible manipulator mechanism. Furthermore, a new robust controller based on mentioned above dynamic model was also considered to regulate both flexural vibrations and rigid body motion. The proposed controller combined sliding mode and backstepping techniques to deal with the nonlinear system with uncertainties. The sliding mode control was used to achieve an asymptotic joint angle and vibration regulation by providing a virtual force while the backstepping technique was used to regulate the spool position of a hydraulic valve to provide the required control force. Simulation results are presented to show the stabilizing effect and robustness of this control strategy.

  10. A Model of Workflow-oriented Attributed Based Access Control

    Directory of Open Access Journals (Sweden)

    Guoping Zhang

    2011-02-01

    Full Text Available the emergence of “Internet of Things” breaks previous traditional thinking, which integrates physical infrastructure and network infrastructure into unified infrastructure. There will be a lot of resources or information in IoT, so computing and processing of information is the core supporting of IoT. In this paper, we introduce “Service-Oriented Computing” to solve the problem where each device can offer its functionality as standard services. Here we mainly discuss the access control issue of service-oriented computing in Internet of Things. This paper puts forward a model of Workflow-oriented Attributed Based Access Control (WABAC, and design an access control framework based on WABAC model. The model grants permissions to subjects according to subject atttribute, resource attribute, environment attribute and current task, meeting access control request of SOC. Using the approach presented can effectively enhance the access control security for SOC applications, and prevent the abuse of subject permissions.

  11. Phase Model with Feedback Control for Power Grids

    CERN Document Server

    Matsuo, Tatsuma

    2013-01-01

    A phase model with feedback control is studied as a dynamical model of power grids. As an example, we study a model network corresponding to the power grid in the Kyushu region. The standard frequency is maintained by the mutual synchronization and the feedback control. Electric failures are induced by an overload. We propose a local feedback method in which the strength of feedback control is proportional to the magnitude of generators. We find that the electric failures do not occur until the utilization ratio is close to 1 under this feedback control. We also find that the temporal response for the time-varying input power is suppressed under this feedback control. We explain the mechanisms using the corresponding global feedback method.

  12. Case Studies in Modelling, Control in Food Processes.

    Science.gov (United States)

    Glassey, J; Barone, A; Montague, G A; Sabou, V

    2017-01-01

    This chapter discusses the importance of modelling and control in increasing food process efficiency and ensuring product quality. Various approaches to both modelling and control in food processing are set in the context of the specific challenges in this industrial sector and latest developments in each area are discussed. Three industrial case studies are used to demonstrate the benefits of advanced measurement, modelling and control in food processes. The first case study illustrates the use of knowledge elicitation from expert operators in the process for the manufacture of potato chips (French fries) and the consequent improvements in process control to increase the consistency of the resulting product. The second case study highlights the economic benefits of tighter control of an important process parameter, moisture content, in potato crisp (chips) manufacture. The final case study describes the use of NIR spectroscopy in ensuring effective mixing of dry multicomponent mixtures and pastes. Practical implementation tips and infrastructure requirements are also discussed.

  13. Phase Model with Feedback Control for Power Grids

    Science.gov (United States)

    Matsuo, Tatsuma; Sakaguchi, Hidetsugu

    2013-09-01

    A phase model with feedback control is studied as a dynamical model of power grids. As an example, we study a model network corresponding to the power grid in the Kyushu region. The standard frequency is maintained by the mutual synchronization and the feedback control. Electric failures are induced by an overload. We propose a local feedback method in which the strength of feedback control is proportional to the magnitude of generators. We find that the electric failures do not occur until the utilization ratio is close to 1 under this feedback control. We also find that the temporal response for the time-varying input power is suppressed under this feedback control. We explain the mechanisms using the corresponding global feedback method.

  14. Model of Controlling the Hubs in P2P Networks

    Directory of Open Access Journals (Sweden)

    Yuhua Liu

    2009-06-01

    Full Text Available Research into the hubs in Peer-to-Peer (P2P networks, and present a new method to avoid generating the hubs in the networks by controlling the logical topology structure of P2P networks. We firstly introduce the controlling ideas about hierarchizing the hubs. Then, we disclose and interpret the controlling model, and give out the concrete method to carry it out. Finally, we validate our controlling model via simulations and the simulation results demonstrate that our work is effective to control the hubs in P2P networks. Thus, this model can improve the network competence to defend against coordinated attacks, promote the network robustness, and ensure the network would develop continually and healthily.

  15. 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.

  16. Rotor-Flying Manipulator: Modeling, Analysis, and Control

    Directory of Open Access Journals (Sweden)

    Bin Yang

    2014-01-01

    Full Text Available Equipping multijoint manipulators on a mobile robot is a typical redesign scheme to make the latter be able to actively influence the surroundings and has been extensively used for many ground robots, underwater robots, and space robotic systems. However, the rotor-flying robot (RFR is difficult to be made such redesign. This is mainly because the motion of the manipulator will bring heavy coupling between itself and the RFR system, which makes the system model highly complicated and the controller design difficult. Thus, in this paper, the modeling, analysis, and control of the combined system, called rotor-flying multijoint manipulator (RF-MJM, are conducted. Firstly, the detailed dynamics model is constructed and analyzed. Subsequently, a full-state feedback linear quadratic regulator (LQR controller is designed through obtaining linearized model near steady state. Finally, simulations are conducted and the results are analyzed to show the basic control performance.

  17. Economic MPC based on LPV model for thermostatically controlled loads

    DEFF Research Database (Denmark)

    Zemtsov, Nikita; Hlava, Jaroslav; Frantsuzova, Galina

    2017-01-01

    Rapid increase of the renewable energy share in electricity production requires optimization and flexibility of the power consumption side. Thermostatically controlled loads (TCLs) have a large potential for regulation service provision. Economic model predictive control (MPC) is an advanced...... control method which can be used to syncronize the power consumption with undispatchable renewable electricity production. Thermal behavior of TCLs can be described by linear models based on energy balance of the system. In some cases, parameters of the model may be time-varying. In this work, we present....... As a case study, we present control system that minimizes operational cost of swimming pool heating system, where parameters of the model depend on the weather forecast. Simulation results demonstrate that the proposed method is able to deal with this kind of systems....

  18. Model-free adaptive control of advanced power plants

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  19. Pressure Control in Distillation Columns: A Model-Based Analysis

    DEFF Research Database (Denmark)

    Mauricio Iglesias, Miguel; Bisgaard, Thomas; Kristensen, Henrik

    2014-01-01

    A comprehensive assessment of pressure control in distillation columns is presented, including the consequences for composition control and energy consumption. Two types of representative control structures are modeled, analyzed, and benchmarked. A detailed simulation test, based on a real...... industrial distillation column, is used to assess the differences between the two control structures and to demonstrate the benefits of pressure control in the operation. In the second part of the article, a thermodynamic analysis is carried out to establish the influence of pressure on relative volatility...

  20. Model-free adaptive control of advanced power plants

    Science.gov (United States)

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  1. Controller design for TS models using delayed nonquadratic Lyapunov functions.

    Science.gov (United States)

    Lendek, Zsofia; Guerra, Thierry-Marie; Lauber, Jimmy

    2015-03-01

    In the last few years, nonquadratic Lyapunov functions have been more and more frequently used in the analysis and controller design for Takagi-Sugeno fuzzy models. In this paper, we developed relaxed conditions for controller design using nonquadratic Lyapunov functions and delayed controllers and give a general framework for the use of such Lyapunov functions. The two controller design methods developed in this framework outperform and generalize current state-of-the-art methods. The proposed methods are extended to robust and H∞ control and α -sample variation.

  2. Adaptive model-based control systems and methods for controlling a gas turbine

    Science.gov (United States)

    Brunell, Brent Jerome (Inventor); Mathews, Jr., Harry Kirk (Inventor); Kumar, Aditya (Inventor)

    2004-01-01

    Adaptive model-based control systems and methods are described so that performance and/or operability of a gas turbine in an aircraft engine, power plant, marine propulsion, or industrial application can be optimized under normal, deteriorated, faulted, failed and/or damaged operation. First, a model of each relevant system or component is created, and the model is adapted to the engine. Then, if/when deterioration, a fault, a failure or some kind of damage to an engine component or system is detected, that information is input to the model-based control as changes to the model, constraints, objective function, or other control parameters. With all the information about the engine condition, and state and directives on the control goals in terms of an objective function and constraints, the control then solves an optimization so the optimal control action can be determined and taken. This model and control may be updated in real-time to account for engine-to-engine variation, deterioration, damage, faults and/or failures using optimal corrective control action command(s).

  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. Control system design for flexible structures using data models

    Science.gov (United States)

    Irwin, R. Dennis; Frazier, W. Garth; Mitchell, Jerrel R.; Medina, Enrique A.; Bukley, Angelia P.

    1993-01-01

    The dynamics and control of flexible aerospace structures exercises many of the engineering disciplines. In recent years there has been considerable research in the developing and tailoring of control system design techniques for these structures. This problem involves designing a control system for a multi-input, multi-output (MIMO) system that satisfies various performance criteria, such as vibration suppression, disturbance and noise rejection, attitude control and slewing control. Considerable progress has been made and demonstrated in control system design techniques for these structures. The key to designing control systems for these structures that meet stringent performance requirements is an accurate model. It has become apparent that theoretically and finite-element generated models do not provide the needed accuracy; almost all successful demonstrations of control system design techniques have involved using test results for fine-tuning a model or for extracting a model using system ID techniques. This paper describes past and ongoing efforts at Ohio University and NASA MSFC to design controllers using 'data models.' The basic philosophy of this approach is to start with a stabilizing controller and frequency response data that describes the plant; then, iteratively vary the free parameters of the controller so that performance measures become closer to satisfying design specifications. The frequency response data can be either experimentally derived or analytically derived. One 'design-with-data' algorithm presented in this paper is called the Compensator Improvement Program (CIP). The current CIP designs controllers for MIMO systems so that classical gain, phase, and attenuation margins are achieved. The center-piece of the CIP algorithm is the constraint improvement technique which is used to calculate a parameter change vector that guarantees an improvement in all unsatisfied, feasible performance metrics from iteration to iteration. The paper also

  5. Integrating attentional control theory and the strength model of self-control.

    Science.gov (United States)

    Englert, Chris; Bertrams, Alex

    2015-01-01

    In the present article, we argue that it may be fruitful to incorporate the ideas of the strength model of self-control into the core assumptions of the well-established attentional control theory (ACT). In ACT, it is assumed that anxiety automatically leads to attention disruption and increased distractibility, which may impair subsequent cognitive or perceptual-motor performance, but only if individuals do not have the ability to counteract this attention disruption. However, ACT does not clarify which process determines whether one can volitionally regulate attention despite experiencing high levels of anxiety. In terms of the strength model of self-control, attention regulation can be viewed as a self-control act depending on the momentary availability of self-control strength. We review literature that has revealed that self-control strength moderates the anxiety-performance relationship, discuss how to integrate these two theoretical models, and offer practical recommendations of how to counteract negative anxiety effects.

  6. Mathematical models for therapeutic approaches to control HIV disease transmission

    CERN Document Server

    Roy, Priti Kumar

    2015-01-01

    The book discusses different therapeutic approaches based on different mathematical models to control the HIV/AIDS disease transmission. It uses clinical data, collected from different cited sources, to formulate the deterministic as well as stochastic mathematical models of HIV/AIDS. It provides complementary approaches, from deterministic and stochastic points of view, to optimal control strategy with perfect drug adherence and also tries to seek viewpoints of the same issue from different angles with various mathematical models to computer simulations. The book presents essential methods and techniques for students who are interested in designing epidemiological models on HIV/AIDS. It also guides research scientists, working in the periphery of mathematical modeling, and helps them to explore a hypothetical method by examining its consequences in the form of a mathematical modelling and making some scientific predictions. The model equations, mathematical analysis and several numerical simulations that are...

  7. Modeling of Random Delays in Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Yuan Ge

    2013-01-01

    Full Text Available In networked control systems (NCSs, the presence of communication networks in control loops causes many imperfections such as random delays, packet losses, multipacket transmission, and packet disordering. In fact, random delays are usually the most important problems and challenges in NCSs because, to some extent, other problems are often caused by random delays. In order to compensate for random delays which may lead to performance degradation and instability of NCSs, it is necessary to establish the mathematical model of random delays before compensation. In this paper, four major delay models are surveyed including constant delay model, mutually independent stochastic delay model, Markov chain model, and hidden Markov model. In each delay model, some promising compensation methods of delays are also addressed.

  8. Sliding Mode Control Design via Reduced Order Model Approach

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper presents a design of continuous-time sliding mode control for the higher order systems via reduced order model. It is shown that a continuous-time sliding mode control designed for the reduced order model gives similar performance for the higher order system. The method is illustrated by numerical examples. The paper also introduces a technique for design of a sliding surface such that the system satisfies a cost-optimality condition when on the sliding surface.

  9. Model Predictive Control of Buoy Type Wave Energy Converter

    DEFF Research Database (Denmark)

    Soltani, Mohsen N.; Sichani, Mahdi T.; 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 additive device attached to the buoy which may include damping, stiffness or similar terms hence will affect the dynamic motion of the buoy. Therefore such a device can be seen as a closed-loop controller. The objective of the wave energy converter is to harvest as much energy from sea as possible....... 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....

  10. Position Sensorless Control of IPMSMs Based on a Novel Flux Model Suitable for Maximum Torque Control

    Science.gov (United States)

    Matsumoto, Atsushi; Hasegawa, Masaru; Matsui, Keiju

    In this paper, a novel position sensorless control method for interior permanent magnet synchronous motors (IPMSMs) that is based on a novel flux model suitable for maximum torque control has been proposed. Maximum torque per ampere (MTPA) control is often utilized for driving IPMSMs with the maximum efficiency. In order to implement this control, generally, the parameters are required to be accurate. However, the inductance varies dramatically because of magnetic saturation, which has been one of the most important problems in recent years. Therefore, the conventional MTPA control method fails to achieve maximum efficiency for IPMSMs because of parameter mismatches. In this paper, first, a novel flux model has been proposed for realizing the position sensorless control of IPMSMs, which is insensitive to Lq. In addition, in this paper, it has been shown that the proposed flux model can approximately estimate the maximum torque control (MTC) frame, which as a new coordinate aligned with the current vector for MTPA control. Next, in this paper, a precise estimation method for the MTC frame has been proposed. By this method, highly accurate maximum torque control can be achieved. A decoupling control algorithm based on the proposed model has also been addressed in this paper. Finally, some experimental results demonstrate the feasibility and effectiveness of the proposed method.

  11. Modeling and control of surge and rotating stall in compressors

    Energy Technology Data Exchange (ETDEWEB)

    Gravdahl, Jan Tommy

    1998-12-31

    Compressors are used in power generation and a variety of other applications. This thesis contains new results in the field of modeling and control of rotating stall and surge in compressors. A close coupled valve is included in the Moore-Greitzer compression system model and controllers for both surge and rotating stall is derived using backstepping. Disturbances, constant and time varying, are then taken into account, and non-linear controllers are derived. Stability results are given. Then, passivity is used to derive a simple surge control law for the closed coupled valve. This propositional control law is shown to stabilize the system even in the presence of time varying disturbances in mass flow and pressure. A novel model for an axial compression system with non-constant compressor speed is derived by extending the Moore-Greitzer model. Rotating stall and surge is studied in connection with acceleration of the compressor. Finally, a model for a centrifugal compression system with time varying compressor speed is derived. The variable speed compressor characteristic is derived based on energy losses in the compressor components. Active control of surge in connection with varying speed is studied. Semi-global exponential stability of the compression system with both surge and speed control is proven. 103 refs., 38 figs., 5 tabs.

  12. Type-2 fuzzy logic uncertain systems’ modeling and control

    CERN Document Server

    Antão, Rómulo

    2017-01-01

    This book focuses on a particular domain of Type-2 Fuzzy Logic, related to process modeling and control applications. It deepens readers’understanding of Type-2 Fuzzy Logic with regard to the following three topics: using simpler methods to train a Type-2 Takagi-Sugeno Fuzzy Model; using the principles of Type-2 Fuzzy Logic to reduce the influence of modeling uncertainties on a locally linear n-step ahead predictor; and developing model-based control algorithms according to the Generalized Predictive Control principles using Type-2 Fuzzy Sets. Throughout the book, theory is always complemented with practical applications and readers are invited to take their learning process one step farther and implement their own applications using the algorithms’ source codes (provided). As such, the book offers avaluable referenceguide for allengineers and researchers in the field ofcomputer science who are interested in intelligent systems, rule-based systems and modeling uncertainty.

  13. 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.

  14. Linearized models for a new magnetic control in MAST

    Energy Technology Data Exchange (ETDEWEB)

    Artaserse, G., E-mail: giovanni.artaserse@enea.it [Associazione Euratom-ENEA sulla Fusione, Via Enrico Fermi 45, I-00044 Frascati (RM) (Italy); Maviglia, F.; Albanese, R. [Associazione Euratom-ENEA-CREATE sulla Fusione, Via Claudio 21, I-80125 Napoli (Italy); McArdle, G.J.; Pangione, L. [EURATOM/CCFE Fusion Association, Culham Science Centre, Abingdon, Oxon, OX14 3DB (United Kingdom)

    2013-10-15

    Highlights: ► We applied linearized models for a new magnetic control on MAST tokamak. ► A suite of procedures, conceived to be machine independent, have been used. ► We carried out model-based simulations, taking into account eddy currents effects. ► Comparison with the EFIT flux maps and the experimental magnetic signals are shown. ► A current driven model for the dynamic simulations of the experimental data have been performed. -- Abstract: The aim of this work is to provide reliable linearized models for the design and assessment of a new magnetic control system for MAST (Mega Ampère Spherical Tokamak) using rtEFIT, which can easily be exported to MAST Upgrade. Linearized models for magnetic control have been obtained using the 2D axisymmetric finite element code CREATE L. MAST linearized models include equivalent 2D axisymmetric schematization of poloidal field (PF) coils, vacuum vessel, and other conducting structures. A plasmaless and a double null configuration have been chosen as benchmark cases for the comparison with experimental data and EFIT reconstructions. Good agreement has been found with the EFIT flux map and the experimental signals coming from magnetic probes with only few mismatches probably due to broken sensors. A suite of procedures (equipped with a user friendly interface to be run even remotely) to provide linearized models for magnetic control is now available on the MAST linux machines. A new current driven model has been used to obtain a state space model having the PF coil currents as inputs. Dynamic simulations of experimental data have been carried out using linearized models, including modelling of the effects of the passive structures, showing a fair agreement. The modelling activity has been useful also to reproduce accurately the interaction between plasma current and radial position control loops.

  15. Fuzzy control of power converters based on quasilinear modelling

    Science.gov (United States)

    Li, C. K.; Lee, W. L.; Chou, Y. W.

    1995-03-01

    Unlike feedback control by the fuzzy PID method, a new fuzzy control algorithm based on quasilinear modelling of the DC-DC converter is proposed. Investigation is carried out using a buck-boost converter. Simulation results demonstrated that the converter can be regulated with improved performance even when subjected to input disturbance and load variation.

  16. Model-Checking Real-Time Control Programs

    DEFF Research Database (Denmark)

    Iversen, T. K.; Kristoffersen, K. J.; Larsen, Kim Guldstrand

    2000-01-01

    In this paper, we present a method for automatic verification of real-time control programs running on LEGO(R) RCX(TM) bricks using the verification tool UPPALL. The control programs, consisting of a number of tasks running concurrently, are automatically translated into the mixed automata model...

  17. Optimal control of a dengue epidemic model with vaccination

    CERN Document Server

    Rodrigues, Helena Sofia; Torres, Delfim F M

    2011-01-01

    We present a SIR+ASI epidemic model to describe the interaction between human and dengue fever mosquito populations. A control strategy in the form of vaccination, to decrease the number of infected individuals, is used. An optimal control approach is applied in order to find the best way to fight the disease.

  18. 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...

  19. Deficit Prevention: Budget Control Model for Enrollment-Dependent Colleges.

    Science.gov (United States)

    Townsley, Michael K.

    1994-01-01

    An ongoing system of short-term budget controls that test actual performance against budget forecasts is essential for enrollment-dependent independent colleges. The budget control model presented here is a tool to inform the management continuously of changes in the all-important tuition revenue stream. (Author/MSE)

  20. UAV Formation Flight Based on Nonlinear Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Zhou Chao

    2012-01-01

    Full Text Available We designed a distributed collision-free formation flight control law in the framework of nonlinear model predictive control. Formation configuration is determined in the virtual reference point coordinate system. Obstacle avoidance is guaranteed by cost penalty, and intervehicle collision avoidance is guaranteed by cost penalty combined with a new priority strategy.

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

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Hovgaard, Tobias

    2015-01-01

    Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designi...

  2. Dynamic modelling and process control of ZnS precipitation

    NARCIS (Netherlands)

    König, J.; Keesman, K.J.; Veeken, A.H.M.; Lens, P.N.L.

    2006-01-01

    This paper presents the dynamic modelling and design of a control strategy for the ZnS precipitation process. During lab¿scale experiments, the sulfide concentration in a precipitator was controlled at a prespecified pS value by manipulating the flow from a buffer vessel. Batch tests showed that the

  3. Integration of Design and Control Through Model Analysis

    DEFF Research Database (Denmark)

    Russel, Boris Mariboe; Henriksen, Jens Peter; Jørgensen, Sten Bay;

    2000-01-01

    A systematic analysis of the process model is proposed as a pre-solution step for integration of design and control problems. It is shown that the same set of process (control) variables and design (manipulative) variables is employed with different objectives in design and control. Analysis of t...... processes with mass and/or energy recycle. (C) 2000 Elsevier Science Ltd. All rights reserved....

  4. 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.

  5. Cellular Automaton Models of Highway Traffic Flow Considering Lane-Control and Speed-Control

    Institute of Scientific and Technical Information of China (English)

    钱勇生; 李文俊; 曾俊伟; 王敏; 杜加伟; 广晓平

    2011-01-01

    As two kinds of management modes of highway tramc control, lane-control, and speed-control produce different effect under different conditions. In this paper, traffic flow cellular automaton models for four-lane highway system with two opposing directions under the above two modes are established considering car and truck mixed running. Through computer numerical simulating, the fundamental diagrams with different parameters are obtained, and after the analysis of density-flux diagrams, the variation discipline of flux with traffic density under different control models is gained. The results indicate that, compared with lane-control, utilization ratio of road can be further improved with speed-control when the truck number increases. The research result is of great significance for reasonable providing theoretical guidance for highway traffic control.

  6. Review of Access Control Models for Cloud Computing

    Directory of Open Access Journals (Sweden)

    Natarajan Meghanathan

    2013-05-01

    Full Text Available The relationship between users and resources is dyn amic in the cloud, and service providers and users are typically not in the same security do main. Identity-based security (e.g., discretionary or mandatory access control models c annot be used in an open cloud computing environment, where each resource node may not be fa miliar, or even do not know each other. Users are normally identified by their attributes o r characteristics and not by predefined identities. There is often a need for a dynamic acc ess control mechanism to achieve cross- domain authentication. In this paper, we will focus on the following three broad categories of access control models for cloud computing: (1 Role -based models; (2 Attribute-based encryption models and (3 Multi-tenancy models. We will review the existing literature on each of the above access control models and their varian ts (technical approaches, characteristics, applicability, pros and cons, and identify future research directions for developing access control models for cloud computing environments .

  7. Engine modeling and control modeling and electronic management of internal combustion engines

    CERN Document Server

    Isermann, Rolf

    2014-01-01

    The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through simulation to calibration. The book treats physically-based as well as models based experimentally on test benches for gasoline (spark ignition) and diesel (compression ignition) engines and uses them for the design of the different control functions. The main topics are: - Development steps for engine control - Stationary and dynamic experimental modeling - Physical models of intake, combustion, mechanical system, turbocharger, exhaust, cooling, lubrication, drive train - Engine control structures, hardware, software, actuators, sensors, fuel supply, injection system, camshaft - Engine control methods, static and dynamic feedforward and feedback control, calibration and optimization, HiL, RCP, control software developm...

  8. Improving active space telescope wavefront control using predictive thermal modeling

    Science.gov (United States)

    Gersh-Range, Jessica; Perrin, Marshall D.

    2015-01-01

    Active control algorithms for space telescopes are less mature than those for large ground telescopes due to differences in the wavefront control problems. Active wavefront control for space telescopes at L2, such as the James Webb Space Telescope (JWST), requires weighing control costs against the benefits of correcting wavefront perturbations that are a predictable byproduct of the observing schedule, which is known and determined in advance. To improve the control algorithms for these telescopes, we have developed a model that calculates the temperature and wavefront evolution during a hypothetical mission, assuming the dominant wavefront perturbations are due to changes in the spacecraft attitude with respect to the sun. Using this model, we show that the wavefront can be controlled passively by introducing scheduling constraints that limit the allowable attitudes for an observation based on the observation duration and the mean telescope temperature. We also describe the implementation of a predictive controller designed to prevent the wavefront error (WFE) from exceeding a desired threshold. This controller outperforms simpler algorithms even with substantial model error, achieving a lower WFE without requiring significantly more corrections. Consequently, predictive wavefront control based on known spacecraft attitude plans is a promising approach for JWST and other future active space observatories.

  9. Modeling and vibration control of an active membrane mirror

    Science.gov (United States)

    Ruggiero, Eric J.; Inman, Daniel J.

    2009-09-01

    The future of space satellite technology lies in ultra-large mirrors and radar apertures for significant improvements in imaging and communication bandwidths. The availability of optical-quality membranes drives a parallel effort for structural models that can capture the dominant dynamics of large, ultra-flexible satellite payloads. Unfortunately, the inherent flexibility of membrane mirrors wreaks havoc with the payload's on-orbit stability and maneuverability. One possible means of controlling these undesirable dynamics is by embedding active piezoelectric ceramics near the boundary of the membrane mirror. In doing so, active feedback control can be used to eliminate detrimental vibration, perform static shape control, and evaluate the health of the structure. The overall motivation of the present work is to design a control system using distributed bimorph actuators to eliminate any detrimental vibration of the membrane mirror. As a basis for this study, a piezoceramic wafer was attached in a bimorph configuration near the boundary of a tensioned rectangular membrane sample. A finite element model of the system was developed to capture the relevant system dynamics from 0 to 300 Hz. The finite element model was compared against experimental results, and fair agreement found. Using the validated finite element models, structural control using linear quadratic regulator control techniques was then used to numerically demonstrate effective vibration control. Typical results show that less than 12 V of actuation voltage is required to eliminate detrimental vibration of the membrane samples in less than 15 ms. The functional gains of the active system are also derived and presented. These spatially descriptive control terms dictate favorable regions within the membrane domain for placing sensors and can be used as a design guideline for structural control applications. The results of the present work demonstrate that thin plate theory is an appropriate modeling

  10. Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks

    Directory of Open Access Journals (Sweden)

    Cunwu Han

    2014-01-01

    Full Text Available A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI techniques. Simulation results are given to illustrate the effectiveness of the proposed method.

  11. Empirical Reduced-Order Modeling for Boundary Feedback Flow Control

    Directory of Open Access Journals (Sweden)

    Seddik M. Djouadi

    2008-01-01

    Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.

  12. Numerical modelling of structural controls on fluid flow and mineralization

    Directory of Open Access Journals (Sweden)

    Yanhua Zhang

    2011-07-01

    Full Text Available This paper presents the results of a set of numerical models focussing on structural controls on hydrothermal mineralization. We first give an overview of natural phenomena of structurally-controlled ore formation and the background theory and mechanisms for such controls. We then provide the results of a group of simple 2D numerical models validated through comparison with Cu-vein structure observed near the Shilu Copper deposit (Yangchun, Guangdong Province, China and finally a case study of 3D numerical modelling applied to the Hodgkinson Province in North Queensland (Australia. Two modelling approaches, discrete deformation modelling and continuum coupled deformation and fluid flow modelling, are involved. The 2D model-derived patterns are remarkably consistent with the Cu-vein structure from the Shilu Copper deposit, and show that both modelling approaches can realistically simulate the mechanical behaviours of shear and dilatant fractures. The continuum coupled deformation and fluid flow model indicates that pattern of the Cu-veins near the Shilu deposit is the result of shear strain localization, development of dilation and fluid focussing into the dilatant fracture segments. The 3D case-study models (with deformation and fluid flow coupling on the Hodgkinson Province generated a number of potential gold mineralization targets.

  13. Automated Model Fit Method for Diesel Engine Control Development

    NARCIS (Netherlands)

    Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.

    2014-01-01

    This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is consider

  14. Modeling Alaska boreal forests with a controlled trend surface approach

    Science.gov (United States)

    Mo Zhou; Jingjing Liang

    2012-01-01

    An approach of Controlled Trend Surface was proposed to simultaneously take into consideration large-scale spatial trends and nonspatial effects. A geospatial model of the Alaska boreal forest was developed from 446 permanent sample plots, which addressed large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of...

  15. Human Behavior Model Based Control Program for ACC Mobile Robot

    Directory of Open Access Journals (Sweden)

    Claudiu Pozna

    2006-07-01

    Full Text Available Present work is a part of the ACC autonomous car project. This paper will focuson the control program architecture. To design this architecture we will start from thehuman driver behavior model. Using this model we have constructed a three level controlprogram. Preliminary results are presented.

  16. Discriminative training of self-structuring hidden control neural models

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Hartmann, Uwe; Hunnerup, Preben

    1995-01-01

    This paper presents a new training algorithm for self-structuring hidden control neural (SHC) models. The SHC models were trained non-discriminatively for speech recognition applications. Better recognition performance can generally be achieved, if discriminative training is applied instead. Thus...

  17. Modeling for Control of a Wobble–Yoke Stirling Engine

    NARCIS (Netherlands)

    García–Canseco, Eloísa; Scherpen, Jacquelien M.A.; Kuindersma, Marnix

    2009-01-01

    In this paper we derive the dynamic model of a four–cylinder double–acting wobble–yoke Stirling engine. In contrast with the classical thermodynamics methods that dominate the literature of Stirling mechanisms, we present a control system perspective to obtain a useful model for the analysis and syn

  18. Inventory Control Systems Model for Strategic Capacity Acquisition

    Directory of Open Access Journals (Sweden)

    Anthony S. White

    2016-01-01

    Full Text Available Variation of installed industrial capacity has been found to follow a cyclic pattern. This paper discusses the application of control theory to the problem of the timely acquisition of extra production capacity. The control system based model presented here is compared with a System Dynamics model proposed by Sterman. Key differences are the method of implementing rational decisions about deployment of extra capacity and the use of a nonlinear APVIOBPCS inventory model. Benefits of this new model are a more measurable process and the ability to select parameter values to optimise capacity deployment. Simulation of the model indicates that the results found by Sterman underestimate the production backlog and time taken to reach equilibrium. The use of a Proportional, Integral, and Derivative (PID controller in the capacity control loop model illustrates that it is possible not only to alter the backlog levels but at the same time to reduce the sales force and improve the revenue. The model also shows clearly that the impact of not increasing capacity promptly results in catastrophic failure of sales as a structural, rather than a business, problem. This model is simple enough to be implemented as a spreadsheet for use as a guide by managers.

  19. Modeling for Control of a Wobble–Yoke Stirling Engine

    NARCIS (Netherlands)

    García–Canseco, Eloísa; Scherpen, Jacquelien M.A.; Kuindersma, Marnix

    2009-01-01

    In this paper we derive the dynamic model of a four–cylinder double–acting wobble–yoke Stirling engine. In contrast with the classical thermodynamics methods that dominate the literature of Stirling mechanisms, we present a control system perspective to obtain a useful model for the analysis and syn

  20. Using Model Checking for Analyzing Distributed Power Control Problems

    DEFF Research Database (Denmark)

    Brihaye, Thomas; Jungers, Marc; Lasaulce, Samson

    2010-01-01

    Model checking (MC) is a formal verification technique which has been known and still knows a resounding success in the computer science community. Realizing that the distributed power control ( PC) problem can be modeled by a timed game between a given transmitter and its environment, the authors...

  1. Automated Model Fit Method for Diesel Engine Control Development

    NARCIS (Netherlands)

    Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.

    2014-01-01

    This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is

  2. Optimal Model-Based Control in HVAC Systems

    DEFF Research Database (Denmark)

    Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik;

    2008-01-01

    This paper presents optimal model-based control of a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger (a rotary wheel heat recovery) and a water-to- air heat exchanger. First dynamic model of the HVAC system...

  3. 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...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...

  4. Modeling of Methods to Control Heat-Consumption Efficiency

    Science.gov (United States)

    Tsynaeva, E. A.; Tsynaeva, A. A.

    2016-11-01

    In this work, consideration has been given to thermophysical processes in automated heat consumption control systems (AHCCSs) of buildings, flow diagrams of these systems, and mathematical models describing the thermophysical processes during the systems' operation; an analysis of adequacy of the mathematical models has been presented. A comparison has been made of the operating efficiency of the systems and the methods to control the efficiency. It has been determined that the operating efficiency of an AHCCS depends on its diagram and the temperature chart of central quality control (CQC) and also on the temperature of a low-grade heat source for the system with a heat pump.

  5. Thermal Storage Power Balancing with Model Predictive Control

    DEFF Research Database (Denmark)

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

    2013-01-01

    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....... 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...

  6. Fuzzy Approximate Model for Distributed Thermal Solar Collectors Control

    KAUST Repository

    Elmetennani, Shahrazed

    2014-07-01

    This paper deals with the problem of controlling concentrated solar collectors where the objective consists of making the outlet temperature of the collector tracking a desired reference. The performance of the novel approximate model based on fuzzy theory, which has been introduced by the authors in [1], is evaluated comparing to other methods in the literature. The proposed approximation is a low order state representation derived from the physical distributed model. It reproduces the temperature transfer dynamics through the collectors accurately and allows the simplification of the control design. Simulation results show interesting performance of the proposed controller.

  7. Modeling and simulation for heavy-duty mecanum wheel platform using model predictive control

    Science.gov (United States)

    Fuad, A. F. M.; Mahmood, I. A.; Ahmad, S.; Norsahperi, N. M. H.; Toha, S. F.; Akmeliawati, R.; Darsivan, F. J.

    2017-03-01

    This paper presents a study on a control system for a heavy-duty four Mecanum wheel platform. A mathematical model for the system is synthesized for the purpose of examining system behavior, including Mecanum wheel kinematics, AC servo motor, gearbox, and heavy duty load. The system is tested for velocity control, using model predictive control (MPC), and compared with a traditional PID setup. The parameters for the controllers are determined by manual tuning. Model predictive control was found to be more effective with reference to a linear velocity.

  8. Specifying Usage Control ModelWith Object Constraint Language

    Directory of Open Access Journals (Sweden)

    Min Li

    2013-02-01

    Full Text Available The recent usage control model (UCON is a foundation for next-generation access control models with distinguishing properties of decision continuity and attribute mutability. Constraints in UCON are one of the most important components that have involved in the principle motivations of usage analysis and design. The importance of constraints associated with authorizations, obligations, and conditions in UCON has been recognized but modeling these constraints has not been received much attention. In this paper we use a de facto constraints specification language in software engineering to analyze the constraints in UCON model. We show how to represent constraints with object constraint language (OCL and give out a formalized specification of UCON model which is built from basic constraints, such as authorization predicates, obligation actions and condition requirements. Further, we show the flexibility and expressive capability of this specified UCON model with extensive examples.

  9. Exogenous control of biological and ecological systems through evolutionary modelling

    Directory of Open Access Journals (Sweden)

    Alessandro Ferrarini

    2013-09-01

    Full Text Available The controllability of network-like systems is a topical issue in ecology and biology. It relies on the ability to lead a system's behaviour towards the desired state through the appropriate handling of input variables. Up to now, controllability of networks is based on the permanent control of a set of driver nodes that can guide the system's dynamics. This assumption seems motivated by real-world networks observation, where a decentralized control is often applied only to part of the nodes. While in a previous paper I showed that ecological and biological networks can be efficaciously controlled from the inside, here I further introduce a new framework for network controllability based on the employment of exogenous controllers and evolutionary modelling, and provide an exemplification of its application.

  10. Optimisation of Marine Boilers using Model-based Multivariable Control

    DEFF Research Database (Denmark)

    Solberg, Brian

    Traditionally, marine boilers have been controlled using classical single loop controllers. To optimise marine boiler performance, reduce new installation time and minimise the physical dimensions of these large steel constructions, a more comprehensive and coherent control strategy is needed. Th......). In the thesis the pressure control is based on this new method when on/off burner switching is required while the water level control is handled by a model predictive controller........ This research deals with the application of advanced control to a specific class of marine boilers combining well-known design methods for multivariable systems. This thesis presents contributions for modelling and control of the one-pass smoke tube marine boilers as well as for hybrid systems control. Much...... of the focus has been directed towards water level control which is complicated by the nature of the disturbances acting on the system as well as by low frequency sensor noise. This focus was motivated by an estimated large potential to minimise the boiler geometry by reducing water level fluctuations...

  11. An Access Control Model of Virtual Machine Security

    Directory of Open Access Journals (Sweden)

    QIN Zhong-yuan

    2013-07-01

    Full Text Available Virtualization technology becomes a hot IT technolo gy with the popu-larity of Cloud Computing. However, new security issues arise with it. Specifically, the resources sharing and data communication in virtual machines are most con cerned. In this paper an access control model is proposed which combines the Chinese Wall a nd BLP model. BLP multi-level security model is introduced with corresponding improvement based on PCW (Prioritized Chinese Wall security model. This model can be used to safely co ntrol the resources and event behaviors in virtual machines. Experimental results show its eff ectiveness and safety.

  12. Autonomous Traffic Signal Control Model with Neural Network Analogy

    CERN Document Server

    Ohira, T

    1997-01-01

    We propose here an autonomous traffic signal control model based on analogy with neural networks. In this model, the length of cycle time period of traffic lights at each signal is autonomously adapted. We find a self-organizing collective behavior of such a model through simulation on a one-dimensional lattice model road: traffic congestion is greatly diffused when traffic signals have such autonomous adaptability with suitably tuned parameters. We also find that effectiveness of the system emerges through interactions between units and shows a threshold transition as a function of proportion of adaptive signals in the model.

  13. Control design approaches for nonlinear systems using multiple models

    Institute of Scientific and Technical Information of China (English)

    Junyong ZHAI; Shumin FEI; Feipeng DA

    2007-01-01

    It is difficult to realize control for some complex nonlinear systems operated in different operating regions.Based on developing local models for different operating regions of the process, a novel algorithm using multiple models is proposed. It utilizes dynamic model bank to establish multiple local models, and their membership functions are defined according to respective regions. Then the nonlinear system is approximated to a weighted combination of the local models.The stability of the nonlinear system is proven. Finally, simulations are given to demonstrate the validity of the proposed method.

  14. Humanoid Walking Robot: Modeling, Inverse Dynamics, and Gain Scheduling Control

    Directory of Open Access Journals (Sweden)

    Elvedin Kljuno

    2010-01-01

    Full Text Available This article presents reference-model-based control design for a 10 degree-of-freedom bipedal walking robot, using nonlinear gain scheduling. The main goal is to show concentrated mass models can be used for prediction of the required joint torques for a bipedal walking robot. Relatively complicated architecture, high DOF, and balancing requirements make the control task of these robots difficult. Although linear control techniques can be used to control bipedal robots, nonlinear control is necessary for better performance. The emphasis of this work is to show that the reference model can be a bipedal walking model with concentrated mass at the center of gravity, which removes the problems related to design of a pseudo-inverse system. Another significance of this approach is the reduced calculation requirements due to the simplified procedure of nominal joint torques calculation. Kinematic and dynamic analysis is discussed including results for joint torques and ground force necessary to implement a prescribed walking motion. This analysis is accompanied by a comparison with experimental data. An inverse plant and a tracking error linearization-based controller design approach is described. We propose a novel combination of a nonlinear gain scheduling with a concentrated mass model for the MIMO bipedal robot system.

  15. Modeling and control of a dielectric elastomer actuator

    Science.gov (United States)

    Gupta, Ujjaval; Gu, Guo-Ying; Zhu, Jian

    2016-04-01

    The emerging field of soft robotics offers the prospect of applying soft actuators as artificial muscles in the robots, replacing traditional actuators based on hard materials, such as electric motors, piezoceramic actuators, etc. Dielectric elastomers are one class of soft actuators, which can deform in response to voltage and can resemble biological muscles in the aspects of large deformation, high energy density and fast response. Recent research into dielectric elastomers has mainly focused on issues regarding mechanics, physics, material designs and mechanical designs, whereas less importance is given to the control of these soft actuators. Strong nonlinearities due to large deformation and electromechanical coupling make control of the dielectric elastomer actuators challenging. This paper investigates feed-forward control of a dielectric elastomer actuator by using a nonlinear dynamic model. The material and physical parameters in the model are identified by quasi-static and dynamic experiments. A feed-forward controller is developed based on this nonlinear dynamic model. Experimental evidence shows that this controller can control the soft actuator to track the desired trajectories effectively. The present study confirms that dielectric elastomer actuators are capable of being precisely controlled with the nonlinear dynamic model despite the presence of material nonlinearity and electromechanical coupling. It is expected that the reported results can promote the applications of dielectric elastomer actuators to soft robots or biomimetic robots.

  16. Two-strain Tuberculosis Transmission Model under Three Control Strategies

    Science.gov (United States)

    Rayhan, S. N.; Bakhtiar, T.; Jaharuddin

    2017-03-01

    In 1997, Castillo-Chavez and Feng developed a two-strain tuberculosis (TB) model, which is typical TB and resistant TB. Castillo-Chavez and Feng’s model was then subsequently developed by Jung et al. (2002) by adding two control variables. In this work, Jung et al.’s model was modified by introducing a new control variable so that there are three controls, namely chemoprophylaxis and two treatment strategies, with the application of three different scenarios related to the objective functional form and control application. Pontryagin maximum principle was applied to derive the differential equations system as a condition that must be satisfied by the optimal control variables. Furthermore, the fourth-order Runge-Kutta method was exploited to determine the numerical solution of the optimal control problem. In this numerical solution, it is shown that the controls treated on TB transmission model provide a good effect because latent and infected individuals are decreasing, and the number of individuals that is treated effectively is increasing.

  17. Model Oriented Application Generation for Industrial Control Systems

    CERN Document Server

    Copy, B; Blanco Vinuela, E; Fernandez Adiego, B; Nogueira Ferandes, R; Prieto Barreiro, I

    2011-01-01

    The CERN Unified Industrial Control Systems framework (UNICOS) is a software generation methodology and a collection of development tools that standardizes the design of industrial control applications [1]. A Software Factory, named the UNICOS Application Builder (UAB) [2], was introduced to ease extensibility and maintenance of the framework, introducing a stable metamodel, a set of platformindependent models and platformspecific configurations against which code generation plugins and configuration generation plugins can be written. Such plugins currently target PLC programming environments (Schneider and SIEMENS PLCs) as well as SIEMENS WinCC Open Architecture SCADA (previously known as ETM PVSS) but are being expanded to cover more and more aspects of process control systems. We present what constitutes the UNICOS metamodel and the models in use, how these models can be used to capture knowledge about industrial control systems and how this knowledge can be leveraged to generate both code and configuratio...

  18. Control of Weierstrass-Mandelbrot Function Model with Morlet Wavelets

    Science.gov (United States)

    Zhang, Li; Liu, Shutang; Yu, Chenglong

    A Weierstrass-Mandelbrot function (WMF) model with Morlet wavelets is investigated. Its control relationships are derived quantitatively after proving the convergence of the controlled WMF model. Based on these relationships, it is shown that the scope of the WMF series increases with three parameters of the Morlet wavelets. But other parameters have opposite effect on the scope of the series. The results of simulated examples demonstrate the effectiveness of the control method. Moreover, two statistical characteristics of the series are obtained as the parameters change: One is multifractality of the series of the controlled WMF model, and the other is the Hurst exponent whose value stands for the long-time memory effect on the series.

  19. Application of Attribute Based Access Control Model for Industrial Control Systems

    Directory of Open Access Journals (Sweden)

    Erkan Yalcinkaya

    2017-02-01

    Full Text Available The number of reported security vulnerabilities and incidents related to the industrial control systems (ICS has increased recent years. As argued by several researchers, authorization issues and poor access control are key incident vectors. The majority of ICS are not designed security in mind and they usually lack strong and granular access control mechanisms. The attribute based access control (ABAC model offers high authorization granularity, central administration of access policies with centrally consolidated and monitored logging properties. This research proposes to harness the ABAC model to address the present and future ICS access control challenges. The proposed solution is also implemented and rigorously tested to demonstrate the feasibility and viability of ABAC model for ICS.

  20. A comprehensive gaze stabilization controller based on cerebellar internal models

    DEFF Research Database (Denmark)

    Vannucci, Lorenzo; Falotico, Egidio; Tolu, Silvia

    2017-01-01

    based on the coordination of VCR and VOR and OKR. The model, inspired by neuroscientific cerebellar theories, is provided with learning and adaptation capabilities based on internal models. We present the results for the gaze stabilization model on three sets of experiments conducted on the SABIAN robot...... and on the iCub simulator, validating the robustness of the proposed control method. The first set of experiments focused on the controller response to a set of disturbance frequencies along the vertical plane. The second shows the performances of the system under three-dimensional disturbances. The last set...

  1. Information Modeling for Direct Control of Distributed Energy Resources

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Andersen, Palle; Stoustrup, Jakob

    2013-01-01

    a desired accumulated response. In this paper, we design such an information model based on the markets that the aggregator participates in and based on the flexibility characteristics of the remote controlled DERs. The information model is constructed in a modular manner making the interface suitable...... for a whole range of different DERs. The devised information model can serve as input to the international standardization efforts on distributed energy resources....

  2. 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.

  3. RF system modeling and controller design for the European XFEL

    Energy Technology Data Exchange (ETDEWEB)

    Schmidt, Christian

    2011-06-15

    The European XFEL is being constructed at the Deutsche Elektronen Synchrotron DESY to generate intense, ultrashort pulses of highly coherent and monochromatic X-Rays for material science research. X-ray flashes are generated by accelerating electron bunches within superconducting cavities with radio frequency (RF) fields to energies up to 17.5 GeV. The digital control of these fields requires extremely high quality in order to achieve the physical processes of photon generation. DESY offers with FLASH a pilot test facility, allowing to test and develop most necessary components, even before the XFEL is conducted. Current field control is based on a proportional feedback controller in addition to a constant feedforward drive, which do not meet the high requirements of the XFEL. This thesis shows that a model based controller design can achieve the necessary field regulation requirements. A linear, time invariant ''black box model'' is estimated, which characterizes the essential dynamic behavior. This model is not based on physical assumptions, but describes exclusively the transfer behavior of the plant. The acceleration modules are operated in a pulsed mode, in which the RF field must be kept constant for a finite period. The character of the disturbances and variations from pulse-to-pulse, together with the properties of the system, require a combination of controlled feedforward drive and feedback. Generally unpredictable, low frequency pulse-to-pulse variations are suppressed by the feedback controller. The structural design of the complex multivariable feedback controller is given, which constrains the model based design approach to assign the controller parameters only. Estimation of the parameters, which can not be tuned manually, is done by the method of H{sub {infinity}} loop shaping which is often applied in modern control theory. However, disturbances within a pulse are in a high frequency range concerning the short pulse duration

  4. Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

    Energy Technology Data Exchange (ETDEWEB)

    Xavier, MA; Trimboli, MS

    2015-07-01

    This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.

  5. CONTROL OF NONLINEAR PROCESS USING NEURAL NETWORK BASED MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Dr.A.TRIVEDI

    2011-04-01

    Full Text Available This paper presents a Neural Network based Model Predictive Control (NNMPC strategy to control nonlinear process. Multilayer Perceptron Neural Network (MLP is chosen to represent a Nonlinear Auto Regressive with eXogenous signal (NARX model of a nonlinear system. NARX dynamic model is based on feed-forward architecture and offers good approximation capabilities along with robustness and accuracy. Based on the identified neural model, a generalized predictive control (GPC algorithm is implemented to control the composition in acontinuous stirred tank reactor (CSTR, whose parameters are optimally determined by solving quadratic performance index using well known Levenberg-Marquardt and Quasi-Newton algorithm. NNMPC is tuned by selecting few horizon parameters and weighting factor. The tracking performance of the NNMPC is tested using different amplitude function as a reference signal on CSTR application. Also the robustness and performance is tested in the presence of disturbance on random reference signal.

  6. Towards a control model for the highly cybernetic farming ecosystems.

    Science.gov (United States)

    Liao, C M; Lin, W Z

    2000-11-01

    A dynamic model based on the linear systems theory is developed in designing a highly cybernetic farming strategy to efficiently manage residuals generated in farm ecosystems. A linear cybemetic model would be used to describe the dynamic behavior of resource flow in the farm ecosystem in which the state variables are resource quantities, and the control variables are residual quantities. The controlled process is defined as the controlled management strategy change. Cybemetic mechanism shows the application of residuals as control measures have determinate effects on the controlled process as along as the farming system is observable and controllable in the control sense. To illustrate the model algorithm the idea is applied to simulate the dynamic response of residual phosphorus concentrations in an integrated pig/corn farming system located in the south Taiwan region. General results show that the residual phosphorous concentration is influenced by farming activities which are controlled by a system of gross input and net output parameters. This paper demonstrates using input-output analysis technique that residuals generated in the farming system is the most important cybemetic variable,

  7. Health-aware Model Predictive Control of Pasteurization Plant

    Science.gov (United States)

    Karimi Pour, Fatemeh; Puig, Vicenç; Ocampo-Martinez, Carlos

    2017-01-01

    In order to optimize the trade-off between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steady-state offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steady-state error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utility-scale pasteurization plant.

  8. 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....

  9. Mathematical modeling of elastic inverted pendulum control system

    Institute of Scientific and Technical Information of China (English)

    Chao XU; Xin YU

    2004-01-01

    Inverted pendulums are important objects of theoretical investigation and experiment in the area of control theory and engineering.The researches concentrate on the rigid finite dimensional models which are described by ordinary differential equations(ODEs).Complete rigidity is the approximation of practical models;Elasticity should be introduced into mathematical models in the analysis of system dynamics and integration of highly precise controller.A new kind of inverted pendulum,elastic inverted pendulum was proposed,and elasticity was considered.Mathematical model was derived from Hamiltonian principle and variational methods,which were formulated by the coupling of partial differential equations(PDE) and ODE.Because of infinite dimensional,system analysis and control of elastic inverted pendulum is more sophisticated than the rigid one.

  10. On fractional order composite model reference adaptive control

    Science.gov (United States)

    Wei, Yiheng; Sun, Zhenyuan; Hu, Yangsheng; Wang, Yong

    2016-08-01

    This paper presents a novel composite model reference adaptive control approach for a class of fractional order linear systems with unknown constant parameters. The method is extended from the model reference adaptive control. The parameter estimation error of our method depends on both the tracking error and the prediction error, whereas the existing method only depends on the tracking error, which makes our method has better transient performance in the sense of generating smooth system output. By the aid of the continuous frequency distributed model, stability of the proposed approach is established in the Lyapunov sense. Furthermore, the convergence property of the model parameters estimation is presented, on the premise that the closed-loop control system is stable. Finally, numerical simulation examples are given to demonstrate the effectiveness of the proposed schemes.

  11. 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

    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......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...... scenarios include the extreme operating gust and normal power production using stochastic wind field in the full load region. The results show superior performance compared to the PI controller and a performance marginally better compared to the FF+PI controller. The reason for a better performance against...

  12. Intelligent control of HVAC systems. Part I: Modeling and synthesis

    Directory of Open Access Journals (Sweden)

    Adrian TOADER

    2013-03-01

    Full Text Available This is the first part of a work on intelligent type control of Heating, Ventilating and Air-Conditioning (HVAC systems. The study is performed from the perspective of giving a unitary control method to ensure high energy efficiency and air quality improving. To illustrate the proposed HVAC control technique, in this first part it is considered as benchmark problem a single thermal space HVAC system. The construction of the mathematical model is performed only with a view to obtain a framework of HVAC intelligent control validation by numerical simulations. The latter will be reported in a second part of the study.

  13. Game Modeling Research for Urbanization and Epidemic Control

    Institute of Scientific and Technical Information of China (English)

    Bai-Da Qu

    2005-01-01

    To aid in the sustainable development of cities this paper examines methods for urbanization and epidemic control. Using, as a foundation, game theory from modern control theory, a set of strategies for modeling urbanization and epidemic control are examined by analyzing and studying the current condition of China including its population, economy,resources and city management methods. Urbanization and epidemic control solving strategies are probed and the solution to a simulated example is provided. The conclusion from this research is that the speed of Chinese urbanization should be slowed to match the condition of resources and level of city management available.

  14. Process control for sheet-metal stamping process modeling, controller design and shop-floor implementation

    CERN Document Server

    Lim, Yongseob; Ulsoy, A Galip

    2014-01-01

    Process Control for Sheet-Metal Stamping presents a comprehensive and structured approach to the design and implementation of controllers for the sheet metal stamping process. The use of process control for sheet-metal stamping greatly reduces defects in deep-drawn parts and can also yield large material savings from reduced scrap. Sheet-metal forming is a complex process and most often characterized by partial differential equations that are numerically solved using finite-element techniques. In this book, twenty years of academic research are reviewed and the resulting technology transitioned to the industrial environment. The sheet-metal stamping process is modeled in a manner suitable for multiple-input multiple-output control system design, with commercially available sensors and actuators. These models are then used to design adaptive controllers and real-time controller implementation is discussed. Finally, experimental results from actual shopfloor deployment are presented along with ideas for further...

  15. Modeling validation and control analysis for controlled temperature and humidity of air conditioning system.

    Science.gov (United States)

    Lee, Jing-Nang; Lin, Tsung-Min; Chen, Chien-Chih

    2014-01-01

    This study constructs an energy based model of thermal system for controlled temperature and humidity air conditioning system, and introduces the influence of the mass flow rate, heater and humidifier for proposed control criteria to achieve the controlled temperature and humidity of air conditioning system. Then, the reliability of proposed thermal system model is established by both MATLAB dynamic simulation and the literature validation. Finally, the PID control strategy is applied for controlling the air mass flow rate, humidifying capacity, and heating, capacity. The simulation results show that the temperature and humidity are stable at 541 sec, the disturbance of temperature is only 0.14 °C, 0006 kg(w)/kg(da) in steady-state error of humidity ratio, and the error rate is only 7.5%. The results prove that the proposed system is an effective controlled temperature and humidity of an air conditioning system.

  16. Modeling Validation and Control Analysis for Controlled Temperature and Humidity of Air Conditioning System

    Directory of Open Access Journals (Sweden)

    Jing-Nang Lee

    2014-01-01

    Full Text Available This study constructs an energy based model of thermal system for controlled temperature and humidity air conditioning system, and introduces the influence of the mass flow rate, heater and humidifier for proposed control criteria to achieve the controlled temperature and humidity of air conditioning system. Then, the reliability of proposed thermal system model is established by both MATLAB dynamic simulation and the literature validation. Finally, the PID control strategy is applied for controlling the air mass flow rate, humidifying capacity, and heating, capacity. The simulation results show that the temperature and humidity are stable at 541 sec, the disturbance of temperature is only 0.14°C, 0006 kgw/kgda in steady-state error of humidity ratio, and the error rate is only 7.5%. The results prove that the proposed system is an effective controlled temperature and humidity of an air conditioning system.

  17. Construction and control of a physiological articulatory model

    Science.gov (United States)

    Dang, Jianwu; Honda, Kiyoshi

    2004-02-01

    A physiological articulatory model has been constructed using a fast computation method, which replicates midsagittal regions of the speech organs to simulate articulatory movements during speech. This study aims to improve the accuracy of modeling by using the displacement-based finite-element method and to develop a new approach for controlling the model. A ``semicontinuum'' tongue tissue model was realized by a discrete truss structure with continuum viscoelastic cylinders. Contractile effects of the muscles were systemically examined based on model simulations. The results indicated that each muscle drives the tongue toward an equilibrium position (EP) corresponding to the magnitude of the activation forces. The EPs shifted monotonically as the activation force increased. The monotonic shift revealed a unique and invariant mapping, referred to as an EP map, between a spatial position of the articulators and the muscle forces. This study proposes a control method for the articulatory model based on the EP maps, in which co-contractions of agonist and antagonist muscles are taken into account. By utilizing the co-contraction, the tongue tip and tongue dorsum can be controlled to reach their targets independently. Model simulation showed that the co-contraction of agonist and antagonist muscles could increase the stability of a system in dynamic control.

  18. Application of neural models as controllers in mobile robot velocity control loop

    Science.gov (United States)

    Cerkala, Jakub; Jadlovska, Anna

    2017-01-01

    This paper presents the application of an inverse neural models used as controllers in comparison to classical PI controllers for velocity tracking control task used in two-wheel, differentially driven mobile robot. The PI controller synthesis is based on linear approximation of actuators with equivalent load. In order to obtain relevant datasets for training of feed-forward multi-layer perceptron based neural network used as neural model, the mathematical model of mobile robot, that combines its kinematic and dynamic properties such as chassis dimensions, center of gravity offset, friction and actuator parameters is used. Neural models are trained off-line to act as an inverse dynamics of DC motors with particular load using data collected in simulation experiment for motor input voltage step changes within bounded operating area. The performances of PI controllers versus inverse neural models in mobile robot internal velocity control loops are demonstrated and compared in simulation experiment of navigation control task for line segment motion in plane.

  19. 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

    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...... to production is crucial. We present a model for a house with a heat pump used for supplying thermal energy to a floor heating system. The model is a linear state space model and the resulting controller is an Economic MPC formulated as a linear program. The model includes forecasts of both weather...

  20. 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

  1. The Demand-Control Model: Specific demands, specific Control, and well-defined groups

    NARCIS (Netherlands)

    Jonge, J. de; Dollard, M.F.; Dormann, C.; Blanc, P.M.; Houtman, I.L.D.

    2000-01-01

    The purpose of this study was to test the Demand-Control Model (DCM), accompanied by three goals. Firstly, we used alternative, more focused, and multifaceted measures of both job demands and job control that are relevant and applicable to today's working contexts. Secondly, this study intended to

  2. Fault Tolerance Automotive Air-Ratio Control Using Extreme Learning Machine Model Predictive Controller

    OpenAIRE

    Pak Kin Wong; Hang Cheong Wong; Chi Man Vong; Tong Meng Iong; Ka In Wong; Xianghui Gao

    2015-01-01

    Effective air-ratio control is desirable to maintain the best engine performance. However, traditional air-ratio control assumes the lambda sensor located at the tail pipe works properly and relies strongly on the air-ratio feedback signal measured by the lambda sensor. When the sensor is warming up during cold start or under failure, the traditional air-ratio control no longer works. To address this issue, this paper utilizes an advanced modelling technique, kernel extreme learning machine (...

  3. Aeroservoelastic model based active control for large civil aircraft

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A modeling and control approach for an advanced configured large civil aircraft with aeroservoelasticity via the LQG method and control allocation is presented.Mathematical models and implementation issues for the multi-input/multi-output(MIMO) aeroservoelastic system simulation developed for a flexible wing with multi control surfaces are described.A fuzzy logic based optimization approach is employed to solve the constrained control allocation problem via intelligently adjusting the components of output vector and find a proper vector in the attainable moment set(AMS) autonomously.The basic idea is to minimize the L2 norm of error between the desired moment and achievable moment using the designing freedom provided by redundantly allocated actuators and control surfaces.Considering the constraints of control surfaces,in order to obtain acceptable performance of aircraft such as stability and maneuverability,the fuzzy weights are updated by the learning algorithm,which makes the closed-loop system self-adaptation.Finally,an application example of flight control designing for the advanced civil aircraft is discussed as a demonstration.The studies we have performed showed that the advanced configured large civil aircraft has good performance with the proper designed control law designed via the proposed approach.The gust alleviation and flutter suppression are applied with the synergetic effects of elevator,ailerons,equivalent rudders and flaps.The results show good closed loop performance and meet the requirement of constraint of control surfaces.

  4. MULTILEVEL RECURRENT MODEL FOR HIERARCHICAL CONTROL OF COMPLEX REGIONAL SECURITY

    Directory of Open Access Journals (Sweden)

    Andrey V. Masloboev

    2014-11-01

    Full Text Available Subject of research. The research goal and scope are development of methods and software for mathematical and computer modeling of the regional security information support systems as multilevel hierarchical systems. Such systems are characterized by loosely formalization, multiple-aspect of descendent system processes and their interconnectivity, high level dynamics and uncertainty. The research methodology is based on functional-target approach and principles of multilevel hierarchical system theory. The work considers analysis and structural-algorithmic synthesis problem-solving of the multilevel computer-aided systems intended for management and decision-making information support in the field of regional security. Main results. A hierarchical control multilevel model of regional socio-economic system complex security has been developed. The model is based on functional-target approach and provides both formal statement and solving, and practical implementation of the automated information system structure and control algorithms synthesis problems of regional security management optimal in terms of specified criteria. An approach for intralevel and interlevel coordination problem-solving in the multilevel hierarchical systems has been proposed on the basis of model application. The coordination is provided at the expense of interconnection requirements satisfaction between the functioning quality indexes (objective functions, which are optimized by the different elements of multilevel systems. That gives the possibility for sufficient coherence reaching of the local decisions, being made on the different control levels, under decentralized decision-making and external environment high dynamics. Recurrent model application provides security control mathematical models formation of regional socioeconomic systems, functioning under uncertainty. Practical relevance. The model implementation makes it possible to automate synthesis realization of

  5. Optimal vibration control of curved beams using distributed parameter models

    Science.gov (United States)

    Liu, Fushou; Jin, Dongping; Wen, Hao

    2016-12-01

    The design of linear quadratic optimal controller using spectral factorization method is studied for vibration suppression of curved beam structures modeled as distributed parameter models. The equations of motion for active control of the in-plane vibration of a curved beam are developed firstly considering its shear deformation and rotary inertia, and then the state space model of the curved beam is established directly using the partial differential equations of motion. The functional gains for the distributed parameter model of curved beam are calculated by extending the spectral factorization method. Moreover, the response of the closed-loop control system is derived explicitly in frequency domain. Finally, the suppression of the vibration at the free end of a cantilevered curved beam by point control moment is studied through numerical case studies, in which the benefit of the presented method is shown by comparison with a constant gain velocity feedback control law, and the performance of the presented method on avoidance of control spillover is demonstrated.

  6. The eMOSAIC model for humanoid robot control.

    Science.gov (United States)

    Sugimoto, Norikazu; Morimoto, Jun; Hyon, Sang-Ho; Kawato, Mitsuo

    2012-05-01

    In this study, we propose an extension of the MOSAIC architecture to control real humanoid robots. MOSAIC was originally proposed by neuroscientists to understand the human ability of adaptive control. The modular architecture of the MOSAIC model can be useful for solving nonlinear and non-stationary control problems. Both humans and humanoid robots have nonlinear body dynamics and many degrees of freedom. Since they can interact with environments (e.g., carrying objects), control strategies need to deal with non-stationary dynamics. Therefore, MOSAIC has strong potential as a human motor-control model and a control framework for humanoid robots. Yet application of the MOSAIC model has been limited to simple simulated dynamics since it is susceptive to observation noise and also cannot be applied to partially observable systems. Our approach introduces state estimators into MOSAIC architecture to cope with real environments. By using an extended MOSAIC model, we are able to successfully generate squatting and object-carrying behaviors on a real humanoid robot.

  7. A nonlinear regression model-based predictive control algorithm.

    Science.gov (United States)

    Dubay, R; Abu-Ayyad, M; Hernandez, J M

    2009-04-01

    This paper presents a unique approach for designing a nonlinear regression model-based predictive controller (NRPC) for single-input-single-output (SISO) and multi-input-multi-output (MIMO) processes that are common in industrial applications. The innovation of this strategy is that the controller structure allows nonlinear open-loop modeling to be conducted while closed-loop control is executed every sampling instant. Consequently, the system matrix is regenerated every sampling instant using a continuous function providing a more accurate prediction of the plant. Computer simulations are carried out on nonlinear plants, demonstrating that the new approach is easily implemented and provides tight control. Also, the proposed algorithm is implemented on two real time SISO applications; a DC motor, a plastic injection molding machine and a nonlinear MIMO thermal system comprising three temperature zones to be controlled with interacting effects. The experimental closed-loop responses of the proposed algorithm were compared to a multi-model dynamic matrix controller (MPC) with improved results for various set point trajectories. Good disturbance rejection was attained, resulting in improved tracking of multi-set point profiles in comparison to multi-model MPC.

  8. Modeling Supermarket Refrigeration Systems for Supervisory Control in Smart Grid

    DEFF Research Database (Denmark)

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

    2013-01-01

    A modular modeling approach of supermarket refrigeration systems (SRS) which is appropriate for smart grid control purposes is presented in this paper. Modeling and identification are performed by just knowing the system configuration and measured data disregarding the physical details. So......, this approach is extendable to different configurations with different modules. The focus of the work is on estimating the power consumption of the system while estimating the display case temperatures as well. This model can however be employed as a simulation benchmark to develop control methods for SRS...... regarding their power/energy consumptions in the future smart grids. Moreover, the developed model is validated by real data collected from a supermarket in Denmark. The utilization of the produced model is also illustrated by a simple simulation example....

  9. Absorption Cycle Heat Pump Model for Control Design

    DEFF Research Database (Denmark)

    Vinther, Kasper; Just Nielsen, Rene; Nielsen, Kirsten Mølgaard

    2015-01-01

    Heat pumps have recently received increasing interest due to green energy initiatives and increasing energy prices. In this paper, a nonlinear dynamic model of a single-effect LiBr-water absorption cycle heat pump is derived for simulation and control design purposes. The model is based...... on an actual heat pump located at a larger district heating plant. The model is implemented in Modelica and is based on energy and mass balances, together with thermodynamic property functions for LiBr and water and staggered grid representations for heat exchangers. Model parameters have been fitted...... to operational data and different scenarios are simulated to investigate the operational stability of the heat pump. Finally, this paper provides suggestions and examples of derivation of lower order linear models for control design. © Copyright IEEE - All rights reserved....

  10. Expert model process control of composite materials in a press

    Science.gov (United States)

    Saliba, Tony E.; Quinter, Suzanne R.; Abrams, Frances L.

    An expert model for the control of the press processing of thermoset composite materials has been developed. The knowledge base written using the PC PLUS expert system shell was interfaced with models written in FORTRAN. The expert model, which is running on a single computer with a single processor, takes advantage of the symbol-crunching capability of LISP and the number crunching capability of FORTRAN. The Expert Model control system is a qualitative-quantitative process automation (QQPA) system since it includes both quantitative model-based and qualitative rule-based expert system operations. Various physical and mechanical properties were measured from panels processed using the two cycles. Using QQPA, processing time has been reduced significantly without altering product quality.

  11. Self-Triggered Model Predictive Control for Linear Systems Based on Transmission of Control Input Sequences

    Directory of Open Access Journals (Sweden)

    Koichi Kobayashi

    2016-01-01

    Full Text Available A networked control system (NCS is a control system where components such as plants and controllers are connected through communication networks. Self-triggered control is well known as one of the control methods in NCSs and is a control method that for sampled-data control systems both the control input and the aperiodic sampling interval (i.e., the transmission interval are computed simultaneously. In this paper, a self-triggered model predictive control (MPC method for discrete-time linear systems with disturbances is proposed. In the conventional MPC method, the first one of the control input sequence obtained by solving the finite-time optimal control problem is sent and applied to the plant. In the proposed method, the first some elements of the control input sequence obtained are sent to the plant, and each element is sequentially applied to the plant. The number of elements is decided according to the effect of disturbances. In other words, transmission intervals can be controlled. Finally, the effectiveness of the proposed method is shown by numerical simulations.

  12. Simulink Implementation of Indirect Vector Control of Induction Machine Model

    Directory of Open Access Journals (Sweden)

    V. Dhanunjayanaidu

    2014-04-01

    Full Text Available In this paper, a modular Simulink implementation of an induction machine model is described in a step-by-step approach. With the modular system, each block solves one of the model equations; therefore, unlike in black box models, all of the machine parameters are accessible for control and verification purposes.After the implementation, examples are given with the model used in different drive applications, such as open-loop constant V/Hz control and indirect vector control. To implement the induction machine model, the dynamic equivalent circuit of induction motor is taken and the model equations in flux linkage form are derived.Then the model is implemented in Simulink by transforming three phase voltages to d-q frame and the d-q currents back to three phase, also it includes unit vector calculation and induction machine d-q model.The inputs here are three phase voltages, load torque, speed of stator and the outputs are flux linkages and currents, electrical torque and speed of rotor.

  13. Dynamic Modelling and Adaptive Traction Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    A. Albagul

    2008-11-01

    Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as `Low' level controller. The second level is developed to take care of path planning and trajectory generation.

  14. Stability analysis of traffic flow with extended CACC control models

    Science.gov (United States)

    Ya-Zhou, Zheng; Rong-Jun, Cheng; Siu-Ming, Lo; Hong-Xia, Ge

    2016-06-01

    To further investigate car-following behaviors in the cooperative adaptive cruise control (CACC) strategy, a comprehensive control system which can handle three traffic conditions to guarantee driving efficiency and safety is designed by using three CACC models. In this control system, some vital comprehensive information, such as multiple preceding cars’ speed differences and headway, variable safety distance (VSD) and time-delay effect on the traffic current and the jamming transition have been investigated via analytical or numerical methods. Local and string stability criterion for the velocity control (VC) model and gap control (GC) model are derived via linear stability theory. Numerical simulations are conducted to study the performance of the simulated traffic flow. The simulation results show that the VC model and GC model can improve driving efficiency and suppress traffic congestion. Project supported by the National Natural Science Foundation of China (Grant Nos. 71571107 and 11302110). The Scientific Research Fund of Zhejiang Province, China (Grant Nos. LY15A020007, LY15E080013, and LY16G010003). The Natural Science Foundation of Ningbo City (Grant Nos. 2014A610030 and 2015A610299), the Fund from the Government of the Hong Kong Administrative Region, China (Grant No. CityU11209614), and the K C Wong Magna Fund in Ningbo University, China.

  15. Dynamic Modelling and Adaptive Traction Control for Mobile Robots

    Directory of Open Access Journals (Sweden)

    A. Albagul

    2004-09-01

    Full Text Available Mobile robots have received a great deal of research in recent years. A significant amount of research has been published in many aspects related to mobile robots. Most of the research is devoted to design and develop some control techniques for robot motion and path planning. A large number of researchers have used kinematic models to develop motion control strategy for mobile robots. Their argument and assumption that these models are valid if the robot has low speed, low acceleration and light load. However, dynamic modelling of mobile robots is very important as they are designed to travel at higher speed and perform heavy duty work. This paper presents and discusses a new approach to develop a dynamic model and control strategy for wheeled mobile robot which I modelled as a rigid body that roles on two wheels and a castor. The motion control strategy consists of two levels. The first level is dealing with the dynamic of the system and denoted as ‘Low’ level controller. The second level is developed to take care of path planning and trajectory generation.

  16. 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.

  17. Embedded Control System Design A Model Based Approach

    CERN Document Server

    Forrai, Alexandru

    2013-01-01

    Control system design is a challenging task for practicing engineers. It requires knowledge of different engineering fields, a good understanding of technical specifications and good communication skills. The current book introduces the reader into practical control system design, bridging  the gap between theory and practice.  The control design techniques presented in the book are all model based., considering the needs and possibilities of practicing engineers. Classical control design techniques are reviewed and methods are presented how to verify the robustness of the design. It is how the designed control algorithm can be implemented in real-time and tested, fulfilling different safety requirements. Good design practices and the systematic software development process are emphasized in the book according to the generic standard IEC61508. The book is mainly addressed to practicing control and embedded software engineers - working in research and development – as well as graduate students who are face...

  18. Quality guaranteed aggregation based model predictive control and stability analysis

    Institute of Scientific and Technical Information of China (English)

    LI DeWei; XI YuGeng

    2009-01-01

    The input aggregation strategy can reduce the online computational burden of the model predictive controller. But generally aggregation based MPC controller may lead to poor control quality. Therefore, a new concept, equivalent aggregation, is proposed to guarantee the control quality of aggregation based MPC. From the general framework of input linear aggregation, the design methods of equivalent aggregation are developed for unconstrained and terminal zero constrained MPC, which guarantee the actual control inputs exactly to be equal to that of the original MPC. For constrained MPC, quasi-equivalent aggregation strategies are also discussed, aiming to make the difference between the control inputs of aggregation based MPC and original MPC as small as possible. The stability conditions are given for the quasi-equivalent aggregation based MPC as well.

  19. 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....... This approach is then taken into account and an MPC controller is designed for a model WEC 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.......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 additive device attached to the buoy which may include damping, stiffness or similar terms hence will affect the dynamic motion of the buoy. Therefore such a device can be seen as a closed-loop controller. The objective of the wave energy converter is to harvest as much energy from sea as possible...

  20. Modeling of autonomic control in sleep-disordered breathing.

    Science.gov (United States)

    Khoo, Michael C K

    2008-03-01

    There is ample evidence to support the notion that chronic exposure to repetitive episodes of interrupted breathing during sleep can lead to systemic hypertension, heart failure, myocardial infarction and stroke. Recent studies have suggested that abnormal autonomic control may be the common factor linking sleep-disordered breathing (SDB) to these cardiovascular diseases. We have developed a closed-loop minimal model that enables the delineation of the major physiological mechanisms responsible for changes in autonomic system function in SDB, and also forms the basis for a noninvasive technique that enables the early detection of cardiovascular control abnormalities. The model is "minimal" in the sense that all its parameters can be estimated through analysis of the data measured noninvasively from a single experimental procedure. Parameter estimation is enhanced by broadening the frequency content of the subject's ventilatory pattern, either through voluntary control of breathing or involuntary control using ventilator assistance. Although the original form of the model is linear and time-invariant, extensions of the model include the incorporation of nonlinear dynamics in the autonomic control of heart rate, and allowing the transfer functions of the model components to assume time-varying characteristics. The various versions of the model have been applied to different populations of subjects with SDB under different conditions (e.g. supine wakefulness, orthostatic stress, sleep). Our cumulative findings suggest that the minimal model approach provides a more sensitive means of detecting abnormalities in autonomic cardiovascular control in SDB, compared to univariate analysis of heart rate variability or blood pressure variability.