No description available.

With the continued development of economy, the energy demand increases continually . The industry is interested in evaluating the technology of heat pump, with applications mostly for water heater. This thesis analyzes and compares the heating efficiency of electric heater, gas heater and heat pump heater . A fuzzy theory is employed to the developed heating algorithm to raise the efficiency of the heat pump heater and suppress the unnecessary heating at the high temperature. According to the experiment, the heat pump heater could reach 60% energy saving while gas heater could attain 23% in comparison with the electric heater under the same temperature, The system could work all year around and can provide users with water at a proper temperature. In the winter, COP of heat pump heater could reache 2.1~2.5 while in the summer around 2.61~2.95. The energy saving is obvious.

No description available.

No description available.

This thesis focuses on soft sensor development based on fuzzy logic used for real time online monitoring of anaerobic digestion to improve methane output and for robust fermentation. Important process parameter indicators such as pH, biogas production, daily difference in pH and daily difference in biogas production were used to infer alkalinity, a reliable indicator of process stability. Additionally, a fuzzy logic and a rule-based controller were developed and tested with single stage anaerobic digesters operating with cow slurry and cellulose. Alkalinity predictions from the fuzzy logic algorithm were used by both controllers to regulate the organic loading rate that aimed to optimise the biogas process. The predictive performance of a software sensor determining alkalinity that was designed using fuzzy logic and subtractive clustering and was validated against multiple linear regression models that were developed (Partner N° 2, Rothamsted Research 2010) for the same purpose. More accurate alkalinity predictions were achieved by utilizing a fuzzy software sensor designed with less amount of data compared to a multiple linear regression model whose design was based on a larger database. Those models were utilised to control the organic loading rate of a twostage, semi-continuously fed stirred reactor system. Three 5l reactors without support media and three 5l reactors with different support media (burst cell reticulated polyurethane foam coarse, burst cell reticulated polyurethane foam medium and sponge) were operated with cow slurry for a period of seven weeks and twenty weeks respectively. Reactors with support media were proven to be more stable than the reactors without support media but did not exhibit higher gas productivity. Biomass support media were found to influence digester recovery positively by reducing the recovery period. Optimum process parameter ranges were identified for reactors with and without support media. Increased biogas production was found to occur when the loading rates were 3-3.5g VS/l/d and 4-5g VS/l/d respectively. Optimum pH ranges were identified between 7.1-7.3 and 6.9-7.2 for reactors with and without support media respectively, whereas all reactors became unstable at ph<6.9. Alkalinity levels for system stability appeared to be above 3500 mg/l of HCO3 - for reactors without media and 3480 mg/l of HCO3 - for reactors with support media. Biogas production was maximized when alkalinity was 3 between 3500-4500 mg/l of HCO3 - for reactors without support media and 3480- 4300 mg/l of HCO3 - for reactors with support media. Two fuzzy logic models predicting alkalinity based on the operation of the three 5l reactors with support media were developed (FIS I, FIS II). The FIS II design was based on a larger database than FIS I. FIS II performance when applied to the reactor where sponge was used as the support media was characterized by quite good MAE and bias values of 466.53 mg/l of HCO3- and an acceptable value for R2= 0.498. The NMSE was close to 0 with a value of 0.03 and a slightly higher FB= 0.154 than desired. The fuzzy system robustness was tested by adding NaHCO3 to the reactor with the burst cell reticulated polyurethane foam medium and by diluting the reactor where sponge was used as the support media with water. FIS I and FIS II were able to follow the system output closely in the first case, but not in the second. FIS II functionality as an alkalinity predictor was tested through the application on a 28l cylindrical reactor with sponge as the biomass support media treating cow manure. If data that was recorded when severe temperature fluctuations occurred (that highly impact digester performance), are excluded, FIS II performance can be characterized as good by having R2= 0.54 and MAE=Bias= 587 mg/l of HCO3-. Predicted alkalinity values followed observed alkalinity values closely during the days that followed NaHCO3 addition and water dilution. In a second experiment a rulebased and a Mamdani fuzzy logic controller were developed to regulate the organic loading rate based on alkalinity predictions from FIS II. They were tested through the operation of five 6.5l reactors with biomass support media treating cellulose. The performance indices of MAE=763.57 mg/l of HCO3-, Bias= 398.39 mg/l of HCO3-, R2= 0.38 and IA= 0.73 indicate a pretty good correlation between predicted and observed values. However, although both controllers managed to keep alkalinity within the desired levels suggested for stability (>3480 mg/l of HCO3-), the reactors did not reach a stable state suggesting that different loading rates should be applied for biogas systems treating cellulose.

The performance of a quadrotor can be significantly disturbed in presence of wind. In this paper, a simple-to-implement attitude controller is proposed to render a robust and accurate trajectory tracking in presence of disturbance and model uncertainties. The attitude controller design is based on Quantitative Feedback Theory (QFT). A fuzzy logic controller is further employed to provide satisfactory position trajectory tracking for the quadrotor. The performances of the controllers, in terms of disturbance rejection and trajectory tracking are experimentally studied. Finally, a flight scenario is performed to compare the performances of the designed QFT-Fuzzy control scheme with the ArduCopter controller. / May 2016

With scarce the energy source and the worsened environment pollution, how to create and use a clean and never exhausted energy is becoming very important day by day. This thesis we proposed the research and development of a solar energy storage system with fuzzy logic control. This solar energy storage system is composed of the solar cell, charger, batteries, buck converter and digital a signal processor. The solar energy storage charging system charger is based on buck circuit control with battery cycle pulse charging. with the fuzzy control theory combined in the tactics of charging , it¡¦s can improve the efficiency of charging, suppress the abnormally battery temperature rise, lengthen the battery¡¦s life, and reduce the waste used. In the experiment, four different charging methods, with the same starting voltage, are compared in terms of temperature control. Among the four methods, the fuzzy logic control proposed in this thesis is able to control the battery temperature at a good 30 Celsius Degree. Experimental and simulation results demonstrate the effectiveness and validity of the system.

In the polymer extrusion process the product quality like mechanical, optical, electrical properties and homogeneity etc. can be achieved by controlling the melt temperature, melt pressure or viscosity within a narrow fluctuation range. In the earlier studies there are many literatures in connection with the extrusion quality and related quality controls; i.e. temperature control, pressure control and viscosity control. In each of the control strategies, it is believed that the most effective to maintain product quality utilising viscosity control, because a polymer viscosity closely correlates with its composition and molecular distribution, and hence the characteristic of the material. In the viscosity control strategy, viscosity is an induced variable calculated from either the (1) flow rate and pressure drop with in-line rheometer or (2) melt temperature, screw speed (or pressure), geometrical dimensions of extruder, and extrusion material constants without in-line rheometer; the former method may interfere the output rate while the latter one does not. On the demand of using viscosity-measuring instruments as sensors to control the quality of the products, we developed an empirical off-line viscosity model, which is used to derive the extrusion viscosity models in the control process without in-line rheometer. The off-line viscosity model is proved more accuracy than other previous suggested models, such as WLF and Andrade¡¦s equations, to fit the experimental data. Polypropylene (PP) was used in this study to test the effectiveness of the extrusion viscosity models. Comparing the calculated results, it was found that the viscosity characteristics obtained by the extrusion viscosity models are in agreement with those obtained by using an in-line rheometer. Both methods can be used to obtain the viscosity in the polymer extrusion process. The objective of this study is to develop extrusion viscosity models together with collected data from several experimental tests and template rule-base to build a Multi-Input Multi-Output (MIMO) fuzzy logic closed-loop controller for the plastics extrusion control. The objective of this controller is to eliminate process variations and to produce the polymer of consistent quality. The fuzzy logic is provided for designing the MIMO closed-loop controller because it is suitable for applying to the polymer extrusion process control with such advantages as handling complex problems like non-linear, time varying behaviour and poor quality measurements happened in the extrusion process, etc. The experimental pre-tests include (1) investigation of the relationship between melt temperature and barrel setting temperatures (2) investigation of the relationship between melt pressure and screw speed and (3) building the relation equation between measured viscosity, melt temperature and speed for the in-line rheometer, etc. In order to test the effectiveness of the MIMO FLC, an off-line simulation program is developed, and the closed-loop tests are performed on the extruder. The test results prove that the designed MIMO FLC can effectively control the quality of products.

Independent mobility is critical to quality of life for people of all ages, and impaired mobility leaves one with both physical and mental disadvantages. Unfortunately, there are some individuals unable to operate an electric wheelchair due to physical, perceptual, or cognitive deficits. The prime objective of this research was to develop a prototype system which can provide mobility assistant to individuals who would otherwise find it difficult or impossible to operate a power wheelchair. To accomplish this goal, a prototype system consisting of several components including an embedded microcontroller and multiple sensors has been designed which can be added to a standard power wheelchair and make it smart. The control system algorithm designed for this prototype model is based on the fuzzy logic control theory and its main purpose is to augment the user ability to navigate the wheelchair and will provide a safe and comfortable journey to the user.

Grasping, the skill to hold objects and tools while doing in-hand manipulation, still is in many cases an unsolvable problem for robotics, but a natural act for humans. An efficient grasping requires not only human-like robotic hands with articulated fingers but also tactile, force, and kinesthetic sensors for the precise control of the forces and motions exerted during the manipulation. As a fully autonomous robotic dexterous manipulation is too difficult to develop for changing and unstructured environments, an alternative approach is to combine the low-level robot computer control with the higher-level perception and task planning abilities of a human operator equipped with an adequate human-computer interface (HCI). This thesis presents theoretical and experimental contributions to the development of an upgraded haptic-enabled anthropomorphic Ring Ada dexterous robotic hand and a biology-inspired synergistic real-time control system for teleoperated grasping of different objects using a CyberTouch HCI data glove. A fuzzy logic controller module was developed to efficiently control the underactuated Ring Ada’ robotic hand during grasping. A machine learning classification system was developed to recognize grasped objects. Experiments have convincingly demonstrated that our novel Ring Ada robotic hand equipped with kinematic position sensors and touch sensors is able to efficiently grasp different lightweight objects through teleoperation.