Model-based controller design for a plastic film extrusion process

This paper reports the development and implementation of a model-based cross-directional controller for plastic film extrusion and other web-forming processes. The controller design has a similar structure to that of internal model control (IMC) with the addition of an observer whose gain is designed to minimise process and model mis-match. The observer gain is obtained by solving a multi-objective optimisation through the application of a genetic algorithm and simulation results are presented in this paper demonstrating improvements that can be achieved by the proposed controller over two existing CD controllers

Modeling and control of a plastic film manufacturing web process

This paper is concerned with the modelling of aplastic film manufacturing process and the development and implementation of a model-based Cross-Directional (CD) controller. The model is derived from first-principles and some empirical relationships. The final validated nonlinear model could provide a useful off-line platform for developing control and monitoring algorithms.A new controller is designed which has a similar structureto that of Internal Model Control (IMC) with the addition ofan observer whose gain is designed to minimise process andmodel mis-match. The observer gain is obtained by solving amulti-objective optimisation problem through the application of a genetic algorithm. The controller is applied to the nonlinear model and simulation results are presented demonstrating improvements that can be achieved by the proposed controller over two existing CD controllers

A control and monitoring oriented model of a film manufacturing process

This paper describes the development of a control and monitoring oriented model of a plastic film manufacturing process. The model is mainly derived from first-principles and has been implemented in the Matlab/Simulink dynamic simulation environment. The development of the model forms the first phase of a project that aims to develop a nonlinear sub-space based monitoring, fault detection and trouble shooting system for the film manufacturing process

Model predictive control of a variable-speed pitch-regulated wind turbine

The Model Predictive Controller is designed for a 5MW variable-speed pitch-regulated wind turbine for three operating points – below rated wind speed, just above rated wind speed, and above rated wind speed. At each operating point, the controllers are designed based on two different linear models of the same wind turbine to investigate the impact of using different control design models (i.e. the model used for designing a model-based controller) on the control performance

A Qualitative Exploratory Study of Morning Grooming Rituals

This study conducts qualitative research using participants to identify the ritual characteristics of every-morning grooming and the factors that influence this ritua

Impact Analysis of Transportation Modal Shift on Regional Energy Consumption and Environmental Level: Focused on Electric Automobiles

Many governments have tried to reduce CO2 emissions which are believed to be the main cause for global warming. The deployment of electric automobiles is regarded as an effective way to reduce CO2 emissions. The Korean government has planned to deploy about 200,000 electric automobiles. The policy for the deployment of electric automobiles aims at not only decreasing gasoline consumption but also increasing electricity production. However, if an electricity consuming regions is not consistent with an electricity producing region, the policy generates environmental problems between regions. Hence, this paper has established the energy multi-region input-output model to specifically analyze the impacts of the deployment of electric automobiles on regional energy consumption and CO2 emissions. Finally, the paper suggests policy directions regarding the deployment of electric automobiles

Acceptance of VR Shopping: Examining the Role of Technological Characteristics and Consumer Fashion Involvement

The present study examined the effect of vividness and interactivity, the two technological characteristics of VR, and fashion involvement, a consumer characteristic, on consumer’s intent to use VR stores under the framework of the Technology Acceptance Model (TAM). The subjects of the present study were asked to experience a commercially available fashion-brand VR store through a computer monitor and their responses were measured. The results revealed the effects of the technological characteristics of the VR store on consumer beliefs. The higher the perceived vividness of the VR store, the greater the perception that it is easy to use and playful. A higher level of perceived interactivity meant a higher degree of perceived usefulness, ease of use, and playfulness. The results also showed that consumer fashion involvement had a significant impact on perceived playfulness but not on perceived usefulness and ease of use. In addition, a higher degree of perceived ease of use translated into a higher level of perceived usefulness. Regarding the effect of consumer beliefs on usage intention, the more the VR store was perceived as being useful and the greater the playfulness derived from the experience, the higher the consumer intention to adopt the shopping platform. However, the perceived ease of use had a significantly negative impact on consumer usage intention. This shows that, even if VR stores are perceived as easy to use, a lack of perceived benefits, such as usefulness or playfulness, will negate their positive impact on consumer usage intention

Fault detection and diagnosis of a plastic film extrusion process

This paper presents a new approach to the design of a model-based fault detection and diagnosis system for application to a plastic film extrusion process. The design constructs a residual generator via parity relations. A multi-objective optimisation problem must be solved in order for the residual to be sensitive to faults but insensitive to disturbances and modelling errors. In this paper, we exploit a genetic algorithm for solving this multi-objective optimisation problem and the resulting fault detection and diagnosis system is applied to a first-principles model of a plastic film extrusion process. Simulation results demonstrate that various types of faults can be detected and diagnosed successfully