Gotowe bibliografie tematyczne / Model Following Control

Gotowa bibliografia na temat „Model Following Control”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 5 lutego 2022

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Artykuły w czasopismach na temat "Model Following Control"

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Y.P., Patil. "Discrete Adaptive Model Following Sliding Mode Control Design for Improved Performance". Journal of Advanced Research in Dynamical and Control Systems 12, SP3 (28.02.2020): 557–69. http://dx.doi.org/10.5373/jardcs/v12sp3/20201293.

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TANIGUCHI, Tadanari, i Kazuo TANAKA. "Fuzzy Model Following Control". Transactions of the Society of Instrument and Control Engineers 36, nr 2 (2000): 204–10. http://dx.doi.org/10.9746/sicetr1965.36.204.

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HIKITA, Hiromitsu, Mitsuhisa YAMASHITA i Yuzuru KUBOTA. "Model-following repetitive control." Transactions of the Japan Society of Mechanical Engineers Series C 55, nr 519 (1989): 2792–96. http://dx.doi.org/10.1299/kikaic.55.2792.

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Durham, Wayne C., i Frederick H. Lutze. "Perfect explicit model-following control solution to imperfect model-following control problems". Journal of Guidance, Control, and Dynamics 14, nr 2 (marzec 1991): 391–97. http://dx.doi.org/10.2514/3.20651.

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Skoczowski, Stanislaw, i Stefan Domek. "Robust Model Following Control System". IFAC Proceedings Volumes 33, nr 25 (wrzesień 2000): 143–48. http://dx.doi.org/10.1016/s1474-6670(17)39330-8.

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Skoczowski, Stanisław, i Stefan Domek. "PID Robust Model Following Control". IFAC Proceedings Volumes 33, nr 4 (kwiecień 2000): 37–42. http://dx.doi.org/10.1016/s1474-6670(17)38218-6.

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Skoczowski, Stanisław, Stefan Domek i Krzysztof Pietrusewicz. "Model following PID control system". Kybernetes 32, nr 5/6 (lipiec 2003): 818–28. http://dx.doi.org/10.1108/03684920210443888.

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BAYOUMI, M. M., i R. T. F. CHAN. "Model-following control of manipulators". International Journal of Systems Science 18, nr 2 (styczeń 1987): 269–91. http://dx.doi.org/10.1080/00207728708963966.

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Durham, Wayne C., Frederick H. Lutze, M. Remzi Barlas i Bruce C. Munro. "Nonlinear model-following control application to airplane control". Journal of Guidance, Control, and Dynamics 17, nr 3 (maj 1994): 570–77. http://dx.doi.org/10.2514/3.21235.

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KOSUGE, Kazuhiro, Katsuhisa FURUTA i Tatsuaki YOKOYAMA. "Virtual Internal Model Following Control System". Transactions of the Society of Instrument and Control Engineers 24, nr 1 (1988): 55–62. http://dx.doi.org/10.9746/sicetr1965.24.55.

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Rozprawy doktorskie na temat "Model Following Control"

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Durham, Wayne. "Contributions to model following control theory". Diss., Virginia Polytechnic Institute and State University, 1989. http://hdl.handle.net/10919/54349.

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A standard form for linear and nonlinear perfect model following control problems is introduced, and the associated control laws developed. The error dynamics of such systems are analyzed with respect to stability of the error. The effects on the error dynamics of measurement errors and parameter variations are also analyzed, and it is seen that the perfect model following control problem is reduced to that of an error regulator. The linear problem is analyzed to show that virtually all common problems are equivalent to standard form problems through similarity transformations. In the standard form, simple expressions for the control law and error dynamics are used to solve the problem. The linear problem is also analyzed with respect to problems of different order model and plant systems, resulting in augmented system equations. These augmented systems are chosen so that the original dynamics are retained, and so that the higher order problem is in the standard form. The standard form problem is then solved as before. Imperfect model following control problems are analyzed, with three associated results. First, a new t€St for perfect model following is developed. Pairs of models and plants that fail this or other tests are imperfect model following control problems. Second, the effect of using perfect model following control laws on such problems is determined to be equivalent to the addition of a forcing function on the error regulator problem. Third, a new approach to the solution of imperfect model following control problems is shown. This approach seeks to find models that simultaneously satisfy the criteria for perfect model following while retaining the desired characteristics of the intended model. The methods developed in this analysis are applied to problems that illustrate all the principles addressed. The final example is a detailed application to a nonlinear simulation of the F-18 airplane involving control of all degrees of freedom over a large range of angles of attack.
Ph. D.
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Barlas, Mustafa Remzi. "Model-following control applications to nonlinear mechanical systems". Thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-10312009-020202/.

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Silva, André Luís da. "Nonlinear optimum model following control of flexible aircraft". Instituto Tecnológico de Aeronáutica, 2010. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1099.

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This Doctorate Thesis concerns optimum control of flexible aircraft. Models of a conceptual flexible aircraft are developed for control applications. A general model following problem via output feedback is developed and applied to the conceptual aircraft. The models are determined for 3 aircraft variants with increasing flexibility. The aerodynamics of flexible body is given by the Doublet Lattice method. The dynamics of the flexible structure is obtained via modal superposition. Controllability measures, given from control amplitude and rate constraints, are evaluated. Stabilization of flexible modes is performed via static output feedback. Control channels are defined with support of modal controllability and observability indexes. These applications contribute to determine the configuration of control surfaces. In order to treat the control of flexible aircraft, a rigid body approximation is proposed as the reference model. A general problem is posed, that consists in the determination of an optimum quadratic nonlinear output feedback for nonlinear plant and reference model, in order to approximate the input-output behavior of the reference model, for given performance outputs. Novel optimum and sub-optimum results, involving time variant and invariant linear state and output feedback and nonlinear time invariant output feedback, via neural networks, are developed. All these results are applied to the nonlinear model of conceptual aircraft and respective linear approximation, with comparisons among them. The efficiency and efficacy of the results are shown, and the importance of the nonlinear control is evidenced.
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Kress, Reid Leonard. "Adaptive model-following control for hyperthermia treatment systems". Diss., The University of Arizona, 1988. http://hdl.handle.net/10150/184430.

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The purpose of this research was to develop three real-time adaptive temperature controllers for hyperthermia heating systems. Each scheme is made adaptive by using a transient Gaussian estimation routine to estimate the tissue blood perfusion and by then using these estimated values either in an optimizing routine, or in an observer, or in both. The optimizing routine uses a steady-state Gaussian estimation technique to optimize the power distribution until the best possible match is obtained between the steady-state temperatures predicted by a treatment model and a prespecified ideal temperature distribution. The observer uses a treatment model to control unmeasured locations. The first adaptive control scheme uses the optimizing routine alone, the second uses the observer alone and the third uses both the optimzing routine and observer. The performance of each of the adaptive control schemes is compared to a standard proportional-integral-derivative (PID) control scheme for one-dimensional simulations of typical treatments. Results comparing the deviation of the controlled temperature distribution to the ideal desired temperature distribution for all locations and all times indicate that the adaptive schemes perform better than the PID scheme. It can be concluded that adaptive control yields improved performance if good a priori knowledge of the treated region tissue and perfusion region boundaries is available. While these control schemes were designed for eventual implementation on a scanned focused ultrasound hyperthermia treatment system, the techniques are applicable to any system with the capability to vary specific power with respect to location and with an unknown distributed energy sink proportional to the temperature elevation.
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Tang, Shiming. "Adaptive model following control for the robotics manipulator - PUMA 560". Ohio University / OhioLINK, 1988. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1182871986.

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Hicks, Dawn L. "Optimal design of digital model-following systems". Thesis, University of Salford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284423.

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RÖING, JACOB, i CARL JENSEN. "Modelling and design of PMSM position drivesusing model following control". Thesis, KTH, Skolan för industriell teknik och management (ITM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299844.

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Teenage Engineering is a Swedish electronics company that want to automate their quality control process. For this purpose, they want to develop a test jig that can perform tactile testing of their products. The test jig will utilize PMSM motors for position control of the end-effector. This study aims at designing and developing a position controller for Permanent Magnet Synchronous Machine (PMSM). The study was conducted in two main stages. First, a MATLAB/Simulink model was developed for the PMSM driver using Field Oriented Control (FOC) to reduce speed ripple. Model Following Control (MFC) was introduced to add servo controller capabilities to the PMSM driver. Secondly, a Motor Control Unit (MCU) was designed with all the necessary components to implement the PMSM driver and to meet the stakeholder requirements. The study showed that high precision position control of PMSMs can be achieved with Model Following Control (MFC) in simulation. The study also highlights important aspects to consider when designing a custom PMSM servo driver. Due to delays of manufacturing the MCU, only a subset of the MCU’s functionality could be tested. This subset included the Pulse Width Modulation (PWM), Analogue to digital converter (ADC), current sensing and hall encoder implementations. However, more testing was needed to achieve full verification of the PMSM position driver on the MCU.
Teenage Engineering är ett svenskt elektronikföretag som avser att automatisera kvalitetskontrollen av deras produkter. Av denna anledning vill företaget utveckla en fixtur med möjligheten att genomföra taktila tester på deras produkter. Detta examensarbete undersöker utvecklingsprocessen av en positionskontroller för en synkronmotor med permanenta magneter (PMSM). Fixturen kommer att använda synkronmotorer med permanenta magneter (PMSM) för att styra positionen av delen som interagerar med produkten som ska testas. Studien genomfördes i två huvudfaser. Först och främst utvecklades en simulering i MATLAB/Simulink av positionskontrollern. Kontrollern använder sig av vektorbaseradkontroll (FOC) för att minska hastighetsvariationer samt modellbaserad kontroll i syfte att positionsstyra motorn. Därefter designades en motorkontrollenhet (MCU) med alla nödvändiga komponenter för att implementera den simulerade kontrollern. Studien visade att hög precision av positionsstyrning kan åstadkommas med hjälp av modellbaserad kontroll i simulering. Studien understryker också viktiga avvägningar i designprocessen av en motorkontrollenhet för PMSM motorer. En del av funktionaliteten på motorkontrollenheten testades, men mer testning krävdes för att bedöma positionskontrollerns prestation i att styra motorn. De delarna som testades på motorkontrollenheten var pulsbreddsmodulering (PWM), analog till digital konvertering (ADC), strömavläsning samt vinkelavläsning via halleffektsensorn. Dock behövdes mer testning för att fullständigt kunna verifiera MCUn.
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Lapp, Tiffany Rae 1979. "Guidance and control using model predictive control for low altitude real-time terrain following flight". Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/30278.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2004.
Includes bibliographical references (p. 123-125).
This thesis presents the design and implementation of a model predictive control based trajectory optimization method for Nap-of-the-Earth (NOE) flight. A NOE trajectory reference is generated over a subspace of the terrain. It is then inserted into the cost function and the resulting trajectory tracking error term is weighted for more precise longitudinal tracking than lateral tracking through the introduction of the TF/TA ratio. The TF/TA ratio, control effort penalties and MPC prediction horizon are tuned for this application via simulation and eigenvalue analysis for stability and performance. Steps are taken to reduce complexity in the optimization problem including perturbational linearization in the prediction model generation and the use of control basis functions which are analyzed for their trade-off between approximation of the optimal cost/solution and reduction of the optimization complexity. Obstacle avoidance including preclusion of ground collision is accomplished through the establishment of hard state constraints. These state constraints create a 'safe envelope' within which the optimal trajectory can be found. Results over a variety of sample terrains are provided to investigate the sensitivity of tracking performance to nominal velocities. The mission objective of low altitude and high speed was met satisfactorily without terrain or obstacle collision, however, methods to preclude or deal with infeasibility must be investigated as terrain severity (measured by commanded flight path angle) is increased past 30 degrees or speed is increased to and past 30 knots.
by Tiffany Rae Lapp.
S.M.
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Costa, Giuseppe Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Robust Control For Gantry Cranes". Awarded by:University of New South Wales. Electrical Engineering and Telecommunications, 1999. http://handle.unsw.edu.au/1959.4/17609.

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In this thesis a class of robust non-linear controllers for a gantry crane system are discussed. The gantry crane has three degrees of freedom, all of which are interrelated. These are the horizontal traverse of the cart, the vertical motion of the goods (i.e. rope length) and the swing angle made by the goods during the movement of the cart. The objective is to control all three degrees of freedom. This means achieving setpoint control for the cart and the rope length and cancellation of the swing oscillations. A mathematical model of the gantry crane system is developed using Lagrangian dynamics. In this thesis it is shown that a model of the gantry crane system can be represented as two sub models which are coupled by a term which includes the rope length as a parameter. The first system will consist of the cart and swing dynamics and the other system is the hoist dynamics. The mathematical model of these two systems will be derived independent of the other system. The model that is comprised of the two sub models is verified as an accurate model of a gantry crane system and it will be used to simulate the performance of the controllers using Matlab. For completeness a fully coupled mathematical model of the gantry crane system is also developed. A detailed design of a gain scheduled sliding mode controller is presented. This will guarantee the controller's robustness in the presence of uncertainties and bounded matched disturbances. This controller is developed to achieve cart setpoint and swing control while achieving rope length setpoint control. A non gain scheduled sliding mode controller is also developed to determine if the more complex gain scheduled sliding mode controller gives any significant improvement in performance. In the implementation of both sliding mode controllers, all system states must be available. In the real-time gantry crane system used in this thesis, the cart velocity and the swing angle velocity are not directly available from the system. They will be estimated using an alpha-beta state estimator. To overcome this limitation and provide a more practical solution an optimal output feedback model following controller is designed. It is demonstrated that by expressing the system and the model for which the system is to follow in a non-minimal state space representation, LQR techniques can be used to design the controller. This produces a dynamic controller that has a proper transfer function, and negates the need for the availability of all system states. This thesis presents an alternative method of solving the LQR problem by using a generic eigenvalue solution to solve the Riccati equation and thus determine the optimal feedback gains. In this thesis it is shown that by using a combination of sliding mode and H??? control techniques, a non-linear controller is achieved which is robust in the presence of a wide variety of uncertainties and disturbances. A supervisory controller is also described in this thesis. The supervisory control is made up of a feedforward and a feedback component. It is shown that the feedforward component is the crane operator's action, and the feedback component is a sliding mode controller which compensates as the system's output deviates from the desired trajectory because of the operator's inappropriate actions or external disturbances such as wind gusts and noise. All controllers are simulated using Matlab and implemented in real-time on a scale model of the gantry crane system using the program RTShell. The real-time results are compared against simulated results to determine the controller's performance in a real-time environment.
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Flood, Cecilia. "Real-time Trajectory Optimization for Terrain Following Based on Non-linear Model Predictive Control". Thesis, Linköping University, Department of Electrical Engineering, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1136.

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There are occasions when it is preferable that an aircraft flies asclose to the ground as possible. It is difficult for a pilot to predict the topography when he cannot see beyond the next hill, and this makes it hard for him to find the optimal flight trajectory. With the help of a terrain database in the aircraft, the forthcoming topography can be found in advance and a flight trajectory can be calculated in real-time. The main goal is to find an optimal control sequence to be used by the autopilot. The optimization algorithm, which is created for finding the optimal control sequence, has to be run often and therefore, it has to be fast.

This thesis presents a terrain following algorithm based on Model Predictive Control which is a promising and robust way of solving the optimization problem. By using trajectory optimization, a trajectory which follows the terrain very good is found for the non-linear model of the aircraft.

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Książki na temat "Model Following Control"

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S, Alag Gurbux, i Dryden Flight Research Facility, red. Model-following control for an oblique-wing aircraft. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1986.

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S, Alag Gurbux, i Dryden Flight Research Facility, red. Model-following control for an oblique-wing aircraft. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1986.

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S, Alag Gurbux, i Dryden Flight Research Facility, red. Model-following control for an oblique-wing aircraft. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1986.

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Model-following control for an oblique-wing aircraft. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1986.

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Facility, Dryden Flight Research, red. Output model-following control synthesis for an oblique-wing aircraft. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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Facility, Dryden Flight Research, red. Output model-following control synthesis for an oblique-wing aircraft. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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Facility, Dryden Flight Research, red. Output model-following control synthesis for an oblique-wing aircraft. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1990.

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Lei, Yuan. Ventilator Control Parameters. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198784975.003.0009.

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‘Ventilator Control Parameters’ looks at the individual ventilator settings, which are largely used to quantitatively define the properties of mechanical breaths. Following on from the previous discussion of essential variables, this chapter describes their implementation in the form of controls. This chapter begins by discussing the confusing and non-standardized terminology used for control parameters, providing a list of controls used on major ventilators. Common controls include rate, pressure and flow triggers, inspiratory time, I:E ratio, peak flow, flow cycle, tidal volume, pressure control or pressure support, PEEP, FiO2, rise time, flow pattern, and specific controls for biphasic modes. The chapter includes normal values and uses of the controls.
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Ernst, Alexandra, Chris J. A. Moulin, Celine Souchay, Daniel C. Mograbi i Robin Morris. Anosognosia and Metacognition in Alzheimer’s Disease. Redaktorzy John Dunlosky i Sarah (Uma) K. Tauber. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199336746.013.12.

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While metacognition and anosognosia have long been studied as distinct concepts, more recently we have endeavored to construct a theoretical framework for exploring how metacognition can contribute to our understanding of anosognosia and vice versa. Following this approach, with a particular focus on Alzheimer’s disease (AD), this chapter first gives an overview of the key experimental findings and issues on metacognition in AD patients: in particular, overconfidence and absolute awareness; the sensitivity approach; the fractionation of metacognition in AD; the neural substrates of metacognition in the Alzheimer brain; and metacognitive control in these patients. Second, the chapter discusses the concept of anosognosia in AD patients from a cognitive neuropsychological viewpoint. It addresses models such as the cognitive awareness model and evidence from metacognition studies, and how they contribute to disentangle the issue of measuring anosognosia in AD patients. Finally, it develops the emerging concept of “implicit awareness” in AD patients.
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Jay, Schulkin, red. Preoperative events: Their effects on behavior following brain damage. Hillsdale, N.J: L. Erlbaum Associates, 1989.

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Części książek na temat "Model Following Control"

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Duda, Holger, Gerhard Bouwer, J. Michael Bauschat i Klaus-Uwe Hahn. "A model following control approach". W Robust Flight Control, 116–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0113855.

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Faulwasser, Timm, i Rolf Findeisen. "Nonlinear Model Predictive Path-Following Control". W Nonlinear Model Predictive Control, 335–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01094-1_28.

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Faulwasser, T., M. Mehrez i K. Worthmann. "Predictive Path Following Control Without Terminal Constraints". W Recent Advances in Model Predictive Control, 1–26. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63281-6_1.

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Duda, Holger, Gerhard Bouwer, J. Michael Bauschat i Klaus-Uwe Hahn. "Autopilot design based on the Model Following Control approach". W Robust Flight Control, 360–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0113868.

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Matschek, Janine, Tobias Bäthge, Timm Faulwasser i Rolf Findeisen. "Nonlinear Predictive Control for Trajectory Tracking and Path Following: An Introduction and Perspective". W Handbook of Model Predictive Control, 169–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77489-3_8.

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Pham, Khanh D. "Risk-Averse Control Problems in Model-Following Systems". W SpringerBriefs in Optimization, 67–85. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5079-5_5.

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Luo, Renshi, Zhenyu Yu i Tao Tang. "Accurate Train Stopping by Model Following Sliding Mode Control". W 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings, 245–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34910-2_29.

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Kohl, Anna M., Eleni Kelasidi, Kristin Y. Pettersen i Jan Tommy Gravdahl. "Model-Based LOS Path-Following Control of Planar Underwater Snake Robots". W Sensing and Control for Autonomous Vehicles, 343–63. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55372-6_16.

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Wu, Bing, i ZhiYou Cheng. "Safety Opportunity of U-Turn Model Based on Ship-Following Theory". W Future Computing, Communication, Control and Management, 723–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27326-1_93.

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Rucco, Alessandro, António Pedro Aguiar, Fernando A. C. C. Fontes, Fernando Lobo Pereira i João Borges de Sousa. "A Model Predictive Control-Based Architecture for Cooperative Path-Following of Multiple Unmanned Aerial Vehicles". W Developments in Model-Based Optimization and Control, 141–60. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26687-9_7.

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Streszczenia konferencji na temat "Model Following Control"

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Berk Gezer, R., i Ali Turker Kutay. "Robust model following control design for missile roll autopilot". W 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915107.

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LUTZE, FREDERICK. "A perfect explicit model following control solution to imperfect model following control problems". W Guidance, Navigation and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1989. http://dx.doi.org/10.2514/6.1989-3612.

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FitzSimons, Philip M. "A Robust Model Following Controller". W 1990 American Control Conference. IEEE, 1990. http://dx.doi.org/10.23919/acc.1990.4791199.

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Coleman, Edward E. "Integral LQG Model Following Controller". W 1989 American Control Conference. IEEE, 1989. http://dx.doi.org/10.23919/acc.1989.4790261.

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Hush, D., C. Abdallah i B. Hore. "Model following using multilayer perceptrons". W 29th IEEE Conference on Decision and Control. IEEE, 1990. http://dx.doi.org/10.1109/cdc.1990.203916.

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Durham, Wayne. "Dynamic inversion and model-following control". W Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1996. http://dx.doi.org/10.2514/6.1996-3690.

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Sivaramakumar i Rajgopal. "Adaptive control with optimal model following". W IEEE International Conference on Systems Engineering. IEEE, 1989. http://dx.doi.org/10.1109/icsyse.1989.48636.

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DURHAM, WAYNE, i FREDERICK LUTZE. "Nonlinear model-following control application to airplane control". W Navigation and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-2635.

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Dittmar, C. J. "A Hyperstable Model-Following Flight Control System Used for Reconfiguration Following Aircraft Impairment". W 1988 American Control Conference. IEEE, 1988. http://dx.doi.org/10.23919/acc.1988.4790093.

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Moursi, Z. M., J. Raptis i M. E. Sawan. "A Robust Observer-Based Model-Following Control". W 1988 American Control Conference. IEEE, 1988. http://dx.doi.org/10.23919/acc.1988.4790145.

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Raporty organizacyjne na temat "Model Following Control"

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Salazar, Lina, Ana Claudia Palacios, Michael Selvaraj i Frank Montenegro. Using Satellite Images to Measure Crop Productivity: Long-Term Impact Assessment of a Randomized Technology Adoption Program in the Dominican Republic. Inter-American Development Bank, wrzesień 2021. http://dx.doi.org/10.18235/0003604.

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This study combines three rounds of surveys with remote sensing to measure long-term impacts of a randomized irrigation program in the Dominican Republic. Specifically, Landsat 7 and Landsat 8 satellite images are used to measure the causal effects of the program on agricultural productivity, measured through vegetation indices (NDVI and OSAVI). To this end, 377 plots were analyzed (129 treated and 248 controls) for the period from 2011 to 2019. Following a Differencein-Differences (DD) and Event study methodology, the results confirmed that program beneficiaries have higher vegetation indices, and therefore experienced a higher productivity throughout the post-treatment period. Also, there is some evidence of spillover effects to neighboring farmers. Furthermore, the Event Study model shows that productivity impacts are obtained in the third year after the adoption takes place. These findings suggest that adoption of irrigation technologies can be a long and complex process that requires time to generate productivity impacts. In a more general sense, this study reveals the great potential that exists in combining field data with remote sensing information to assess long-term impacts of agricultural programs on agricultural productivity.
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McPhedran, R., K. Patel, B. Toombs, P. Menon, M. Patel, J. Disson, K. Porter, A. John i A. Rayner. Food allergen communication in businesses feasibility trial. Food Standards Agency, marzec 2021. http://dx.doi.org/10.46756/sci.fsa.tpf160.

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Background: Clear allergen communication in food business operators (FBOs) has been shown to have a positive impact on customers’ perceptions of businesses (Barnett et al., 2013). However, the precise size and nature of this effect is not known: there is a paucity of quantitative evidence in this area, particularly in the form of randomised controlled trials (RCTs). The Food Standards Agency (FSA), in collaboration with Kantar’s Behavioural Practice, conducted a feasibility trial to investigate whether a randomised cluster trial – involving the proactive communication of allergen information at the point of sale in FBOs – is feasible in the United Kingdom (UK). Objectives: The trial sought to establish: ease of recruitments of businesses into trials; customer response rates for in-store outcome surveys; fidelity of intervention delivery by FBO staff; sensitivity of outcome survey measures to change; and appropriateness of the chosen analytical approach. Method: Following a recruitment phase – in which one of fourteen multinational FBOs was successfully recruited – the execution of the feasibility trial involved a quasi-randomised matched-pairs clustered experiment. Each of the FBO’s ten participating branches underwent pair-wise matching, with similarity of branches judged according to four criteria: Food Hygiene Rating Scheme (FHRS) score, average weekly footfall, number of staff and customer satisfaction rating. The allocation ratio for this trial was 1:1: one branch in each pair was assigned to the treatment group by a representative from the FBO, while the other continued to operate in accordance with their standard operating procedure. As a business-based feasibility trial, customers at participating branches throughout the fieldwork period were automatically enrolled in the trial. The trial was single-blind: customers at treatment branches were not aware that they were receiving an intervention. All customers who visited participating branches throughout the fieldwork period were asked to complete a short in-store survey on a tablet affixed in branches. This survey contained four outcome measures which operationalised customers’: perceptions of food safety in the FBO; trust in the FBO; self-reported confidence to ask for allergen information in future visits; and overall satisfaction with their visit. Results: Fieldwork was conducted from the 3 – 20 March 2020, with cessation occurring prematurely due to the closure of outlets following the proliferation of COVID-19. n=177 participants took part in the trial across the ten branches; however, response rates (which ranged between 0.1 - 0.8%) were likely also adversely affected by COVID-19. Intervention fidelity was an issue in this study: while compliance with delivery of the intervention was relatively high in treatment branches (78.9%), erroneous delivery in control branches was also common (46.2%). Survey data were analysed using random-intercept multilevel linear regression models (due to the nesting of customers within branches). Despite the trial’s modest sample size, there was some evidence to suggest that the intervention had a positive effect for those suffering from allergies/intolerances for the ‘trust’ (β = 1.288, p<0.01) and ‘satisfaction’ (β = 0.945, p<0.01) outcome variables. Due to singularity within the fitted linear models, hierarchical Bayes models were used to corroborate the size of these interactions. Conclusions: The results of this trial suggest that a fully powered clustered RCT would likely be feasible in the UK. In this case, the primary challenge in the execution of the trial was the recruitment of FBOs: despite high levels of initial interest from four chains, only one took part. However, it is likely that the proliferation of COVID-19 adversely impacted chain participation – two other FBOs withdrew during branch eligibility assessment and selection, citing COVID-19 as a barrier. COVID-19 also likely lowered the on-site survey response rate: a significant negative Pearson correlation was observed between daily survey completions and COVID-19 cases in the UK, highlighting a likely relationship between the two. Limitations: The trial was quasi-random: selection of branches, pair matching and allocation to treatment/control groups were not systematically conducted. These processes were undertaken by a representative from the FBO’s Safety and Quality Assurance team (with oversight from Kantar representatives on pair matching), as a result of the chain’s internal operational restrictions.
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