903 resultados para Synthetic Control Method
Resumo:
Press forming is nowadays one of the most common industrial methods in use for producing deeper trays from paperboard. Demands for material properties like recyclability and sustainability have increased also in the packaging industry, but there are still limitations related to the formability of paperboard. A majority of recent studies have focused on material development, but the potential of the package manufacturing process can also be improved by the development of tooling and process control. In this study, advanced converting tools (die cutting tools and the press forming mould) are created for production scale paperboard tray manufacturing. Also monitoring methods that enable the production of paperboard trays with enhanced quality, and can be utilized in process control are developed. The principles for tray blank preparation, including creasing pattern and die cutting tool design are introduced. The mould heating arrangement and determination of mould clearance are investigated to improve the quality of the press formed trays. The effect of the spring back of the tray walls on the tray dimensions can be managed by adjusting the heat-related process parameters and estimating it at the mould design stage. This enables production speed optimization as the process parameters can be adjusted more freely. Real-time monitoring of pressing force by using multiple force sensors embedded in the mould structure can be utilized in the evaluation of material characteristics on a modified production machinery. Comprehensive process control can be achieved with a combination of measurement of the outer dimensions of the trays and pressing force monitoring. The control method enables detection of defects and tracking changes in the material properties. The optimized converting tools provide a basis for effective operation of the control system.
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The transformation from high level task specification to low level motion control is a fundamental issue in sensorimotor control in animals and robots. This thesis develops a control scheme called virtual model control which addresses this issue. Virtual model control is a motion control language which uses simulations of imagined mechanical components to create forces, which are applied through joint torques, thereby creating the illusion that the components are connected to the robot. Due to the intuitive nature of this technique, designing a virtual model controller requires the same skills as designing the mechanism itself. A high level control system can be cascaded with the low level virtual model controller to modulate the parameters of the virtual mechanisms. Discrete commands from the high level controller would then result in fluid motion. An extension of Gardner's Partitioned Actuator Set Control method is developed. This method allows for the specification of constraints on the generalized forces which each serial path of a parallel mechanism can apply. Virtual model control has been applied to a bipedal walking robot. A simple algorithm utilizing a simple set of virtual components has successfully compelled the robot to walk eight consecutive steps.
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Since robots are typically designed with an individual actuator at each joint, the control of these systems is often difficult and non-intuitive. This thesis explains a more intuitive control scheme called Virtual Model Control. This thesis also demonstrates the simplicity and ease of this control method by using it to control a simulated walking hexapod. Virtual Model Control uses imagined mechanical components to create virtual forces, which are applied through the joint torques of real actuators. This method produces a straightforward means of controlling joint torques to produce a desired robot behavior. Due to the intuitive nature of this control scheme, the design of a virtual model controller is similar to the design of a controller with basic mechanical components. The ease of this control scheme facilitates the use of a high level control system which can be used above the low level virtual model controllers to modulate the parameters of the imaginary mechanical components. In order to apply Virtual Model Control to parallel mechanisms, a solution to the force distribution problem is required. This thesis uses an extension of Gardner`s Partitioned Force Control method which allows for the specification of constrained degrees of freedom. This virtual model control technique was applied to a simulated hexapod robot. Although the hexapod is a highly non-linear, parallel mechanism, the virtual models allowed text-book control solutions to be used while the robot was walking. Using a simple linear control law, the robot walked while simultaneously balancing a pendulum and tracking an object.
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This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields
Resumo:
Many photovoltaic inverter designs make use of a buck based switched mode power supply (SMPS) to produce a rectified sinusoidal waveform. This waveform is then unfolded by a low frequency switching structure to produce a fully sinusoidal waveform. The Cuk SMPS could offer advantages over the buck in such applications. Unfortunately the Cuk converter is considered to be difficult to control using classical methods. Correct closed loop design is essential for stable operation of Cuk converters. Due to these stability issues, Cuk converter based designs often require stiff low bandwidth control loops. In order to achieve this stable closed loop performance, traditional designs invariably need large, unreliable electrolytic capacitors. In this paper, an inverter with a sliding mode control approach is presented which enables the designer to make use of the Cuk converters advantages, while ameliorating control difficulties. This control method allows the selection of passive components based predominantly on ripple and reliability specifications while requiring only one state reference signal. This allows much smaller, more reliable non-electrolytic capacitors to be used. A prototype inverter has been constructed and results obtained which demonstrate the design flexibility of the Cuk topology when coupled with sliding mode control.
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Pollination is one of the most important ecosystem services in agroecosystems and supports food production. Pollinators are potentially at risk being exposed to pesticides and the main route of exposure is direct contact, in some cases ingestion, of contaminated materials such as pollen, nectar, flowers and foliage. To date there are no suitable methods for predicting pesticide exposure for pollinators, therefore official procedures to assess pesticide risk are based on a Hazard Quotient. Here we develop a procedure to assess exposure and risk for pollinators based on the foraging behaviour of honeybees (Apis mellifera) and using this species as indicator representative of pollinating insects. The method was applied in 13 European field sites with different climatic, landscape and land use characteristics. The level of risk during the crop growing season was evaluated as a function of the active ingredients used and application regime. Risk levels were primarily determined by the agronomic practices employed (i.e. crop type, pest control method, pesticide use), and there was a clear temporal partitioning of risks through time. Generally the risk was higher in sites cultivated with permanent crops, such as vineyard and olive, than in annual crops, such as cereals and oil seed rape. The greatest level of risk is generally found at the beginning of the growing season for annual crops and later in June–July for permanent crops.
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High prevalence of anthelmintic-resistant gastrointestinal nematodes (GIN) in goats has increased pressure to find effective, alternative non-synthetic control methods, one of which is adding forage of the high condensed tannin (CT) legume sericea lespedeza (SL; Lespedeza cuneata) to the animal's diet. Previous work has demonstrated good efficacy of dried SL (hay, pellets) against small ruminant GIN, but information is lacking on consumption of fresh SL, particularly during the late summer–autumn period in the southern USA when perennial warm-season grass pastures are often low in quality. A study was designed to determine the effects of autumn (September–November) consumption of fresh SL forage, grass pasture (predominantly bermudagrass, BG; Cynodon dactylon), or a combination of SL + BG forage by young goats [intact male Spanish kids, 9 months old (20.7 ± 1.1 kg), n = 10/treatment group] on their GIN infection status. Three forage paddocks (0.40 ha) were set up at the Fort Valley State University Agricultural Research Station (Fort Valley, GA) for an 8-week trial. The goats in each paddock were supplemented with a commercial feed pellet at 0.45 kg/head/d for the first 4 weeks of the trial, and 0.27 kg/head/d for the final 4 weeks. Forage samples taken at the start of the trial were analyzed for crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF) content, and a separate set of SL samples was analyzed for CT in leaves, stems, and whole plant using the benzyl mercaptan thiolysis method. Animal weights were taken at the start and end of the trial, and fecal and blood samples were collected weekly for determination of fecal egg counts (FEC) and packed cell volume (PCV), respectively. Adult GIN was recovered from the abomasum and small intestines of all goats at the end of the experiment for counting and speciation. The CP levels were highest for SL forage, intermediate for SL + BG, and lowest for BG forage samples, while NDF and ADF values were the opposite, with highest levels in BG and lowest in SL forage samples. Sericea lespedeza leaves had more CT than stems (16.0 g vs. 3.3 g/100 g dry weight), a slightly higher percentage of PDs (98% vs. 94%, respectively) and polymers of larger mean degrees of polymerization (42 vs. 18, respectively). There were no differences in average daily gain or blood PCV between the treatment groups, but SL goats had lower FEC (P < 0.05) than the BG or SL + BG forage goats throughout most of the trial. The SL + BG goats had lower FEC than the BG forage animals by the end of the trial (week 8, P < 0.05). The SL goats had lower numbers (P < 0.05) of male Haemonchus contortus and tended to have fewer female (P < 0.10) and total (P < 0.07) H. contortus compared with the BG goats. The predominant GIN in all the goats was Trichostrongylus colubriformis (73% of total GIN). As a low-input forage with activity against pathogenic GIN (H. contortus), SL has a potential to reduce producers’ dependence upon synthetic anthelmintics and also to fill the autumn ‘window’ in good-quality fresh forages for goat grazing in the southern USA.
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Model Predictive Control (MPC) is a control method that solves in real time an optimal control problem over a finite horizon. The finiteness of the horizon is both the reason of MPC's success and its main limitation. In operational water resources management, MPC has been in fact successfully employed for controlling systems with a relatively short memory, such as canals, where the horizon length is not an issue. For reservoirs, which have generally a longer memory, MPC applications are presently limited to short term management only. Short term reservoir management can be effectively used to deal with fast process, such as floods, but it is not capable of looking sufficiently ahead to handle long term issues, such as drought. To overcome this limitation, we propose an Infinite Horizon MPC (IH-MPC) solution that is particularly suitable for reservoir management. We propose to structure the input signal by use of orthogonal basis functions, therefore reducing the optimization argument to a finite number of variables, and making the control problem solvable in a reasonable time. We applied this solution for the management of the Manantali Reservoir. Manantali is a yearly reservoir located in Mali, on the Senegal river, affecting water systems of Mali, Senegal, and Mauritania. The long term horizon offered by IH-MPC is necessary to deal with the strongly seasonal climate of the region.
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Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we can model the heteroskedasticity of a linear combination of the errors. We show that this assumption can be satisfied without imposing strong assumptions on the errors in common DID applications. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative inference method that relies on strict stationarity and ergodicity of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment periods. We extend our inference methods to linear factor models when there are few treated groups. We also derive conditions under which a permutation test for the synthetic control estimator proposed by Abadie et al. (2010) is robust to heteroskedasticity and propose a modification on the test statistic that provided a better heteroskedasticity correction in our simulations.
Resumo:
Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we know how the heteroskedasticity is generated, which is the case when it is generated by variation in the number of observations per group. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative application of our method that relies on assumptions about stationarity and convergence of the moments of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment groups. We extend our inference method to linear factor models when there are few treated groups. We also propose a permutation test for the synthetic control estimator that provided a better heteroskedasticity correction in our simulations than the test suggested by Abadie et al. (2010).
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This paper presents a simple but practical feedback control method to suppress the vibration of a flexible structure in the frequency range between 10 Hz and 1 kHz. A dynamic vibration absorber is designed for this, which has a natural frequency of 100 Hz and a normalized bandwidth (twice the damping ratio) of 9.9. The absorber is realized electrically by feeding back the structural acceleration at one position on the host structure to a collocated piezoceramic patch actuator via an analog controller consisting of a second-order lowpass filter. This absorber is equivalent to a single degree-of-freedom mechanical oscillator consisting of a serially connected mass-spring-damper system. A first-order lowpass filter is additionally used to improve stability at very high frequencies. Experiments were conducted on a free-free beam embedded with a piezoceramic patch actuator and an accelerometer at its center. It is demonstrated that the single absorber can simultaneously suppress multiple vibration modes within the control bandwidth. It is further shown that the control system is robust to slight changes in the plant. The method described can be applied to many other practical structures, after retuning the absorber parameters for the structure under control.
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We proposed a simple feedback control method to suppress chaotic behavior in oscillators with limited power supply. The small-amplitude controlling signal is applied directly to the power supply system, so as to alter the characteristic curve of the driving motor. Numerical results are presented showing the method efficiency for a wide range of control parameters. Moreover, we have found that, for some parameters, this kind of control may introduce coexisting periodic attractors with complex basins of attraction and, therefore, serious problems with predictability of the final state the system will asymptote to. (c) 2006 Elsevier Ltd. All rights reserved.
Resumo:
In this paper, we examine the nonlinear control method based on the saturation phenomenon and of systems coupled with quadratic nonlinear ties applied to a shear-building portal plane frame foundation that supports an unbalanced direct cut-rent with limited power supply (non-ideal system). We analyze the equations of motion by using the method of averaging and numerical simulation. The interaction of the non-ideal structure with the saturation controller may lead to the occurrence of interesting phenomena during the forward passage through the several resonance states of the systems. Special attention is focused on passage through resonance when the non-ideal excitation frequency is near the portal frame natural frequency and when the non-ideal system frequency is approximately twice the controller frequency (two-to-one internal resonance).
Resumo:
The nonlinear dynamic response and a nonlinear control method of a particular portal frame foundation for an unbalanced rotating machine with limited power (non-ideal motor) are examined. Numerical simulations are performed for a set of control parameters (depending on the voltage of the motor) related to the static and dynamic characteristics of the motor. The interaction of the structure with the excitation source may lead to the occurrence of interesting phenomena during the forward passage through the several resonance states of the systems. A mathematical model having two degrees of freedom simplifies the non-ideal system. The study of controlling steady-state vibrations of the non-ideal system is based on the saturation phenomenon due to internal resonance.
Resumo:
This paper presents a control method for a class of continuous-time switched systems, using state feedback variable structure controllers. The method is applied to the control of a two-cell dc-dc buck converter and a control circuit design using the software PSpice is proposed. The design is based on Lyapunov-Metzler-SPR systems and the performance of the resulting control system is superior to that afforded by a recently-proposed alternative sliding-mode control technique. The dc-dc power converters are very used in industrial applications, for instance, in power systems of hybrid electric vehicles and aircrafts. Good results were obtained and the proposed design is also inexpensive because it uses electric components that can be easily found for the hardware implementation. Future researches on the subject include the hardware validation of the dc-dc converter controller and the robust control design of switched systems, with structural failures. © 2011 IEEE.