Papers by Keyword: Fuzzy Control

Abstract: The article describes a method to improve the uniformity of electroplating using fuzzy logic. This method provides for the replacement of the non-stationary model of the process dynamics in distributed coordinates with the quasi-stationary model of the process dynamics in lumped coordinates. The production knowledge model with "IF-THEN" rules is developed for the stochastic influences taken into account. The dynamic choice of the defuzzification method is justified by solving the problem of minimizing the absolute deviation of the coating thickness average value obtained from the non-stationary model from the predicted value according to the quasi-stationary model at const values of stochastic influences. As an example, fuzzy control of the current for nickel coating is considered, taking into account the stochastic influence of the electroplating time, detail area, temperature and acidity of the electrolyte. The experimental results prove the effectiveness of the combined defuzzification method in comparison with their independent use in the control process.

Abstract: One of the main aspects of small and medium-sized enterprises is the quality of the products, in a production system several parameters and non-temporal variables must respect very strict variation intervals such as weight measurements, in the chemical industry. This parameter also takes a fundamental part in the quality of the product. The correct production process is based on a given percentage of each material. We chose a food production system where the quality requirements are very high. In this article, we propose a production system modeling by interval constraint Petri net. And we controlled these intervals with a fuzzy type-2 controller for decision making.

Abstract: Interline power flow controller is the control device of FACTS (Flexible AC Transmission Systems) which can adjust trend, enhance stability, improve power grid transmission, etc. Through the analysis of the structure of IPFC, this paper demonstrates that fuzzy control method is an advanced and reasonable control method, which can be independently control bus voltage and the active and reactive power current on a line in the power system.

Abstract: The requirements of CNC machine tools for the feed servo system could generally be summarized as high precision, well stability, fast response, wide range of speed regulation, high torque at low speed and so on. The PID controller of feed servo-system based on intelligent fuzzy control was presented based on traditional PID controller. The main feature of this arithmetic was to change parameters in different degrees according to time-varying working conditions, specially this arithmetic could change its domain intelligently according to different conditions and cooperated with a stable controller in case of system crash so that adaptivity and reliability of the feed servo-system were improved, also this feature made application field of the feed servo-system wider.

Abstract: The article presents use of a linguistic fuzzy-logic control (LFLC) system for mechatronic system modelling and control. The presented applications were verified on real laboratory tasks in the Laboratory of Intelligent Systems at the University of Ostrava. The LFLC system was developed at the University of Ostrava, Institute for Research and Applications of Fuzzy Modeling. This technology enables users to describe the system behaviour and/or the control strategy as a set of fuzzy rules. Input and output variables scales are defined by contexts and their change allows using the same system description for systems with similar behaviour very easily.

Abstract: A type of aircraft that is currently being very reference in the area of ​​control is the quadrotor helicopter, compared to other UAV's (Unmanned Aerial Vehicles UAV's-) has been of great interest for the research groups. Principally were developed for military applications. However, UAVs don’t have only military use, also civilian use and it is in this last field that can have multiple applications. The State variables of the system obtained are, however, in the most general case, internal operation of the system variables whose values ​​can’t be measured directly on physical quantities. An observer is used for to reconstruct partially or completely the state vector of a system from the known inputs, outputs and the dynamic model of this. The reconstruction and calculation of the state variables is performed in a system known as Multiobserver. Applying the fuzzy representation of type Takagi-Sugeno, also known as multi-model [1], in dynamic model of the quadrotor and developing an algorithm based in law control for reconstructed states feedback, the vehicle is stabilized.

Abstract: In the twin roll strip casting process, the control for the molten metal level is difficult owing to non-linear and time-varying of the control parameters. In the paper, on the basis of the geometry shape of the molten metal pool and the continuity of metal, the level mathematic model is built. Then a fuzzy control strategy is adopted to control the level. Moreover GA(Genetic algorithm) is used to obtain better fuzzy parameters. Simulations show the fuzzy controller optimized by GA greatly improves the control performance.

Abstract: Shape memory alloy (SMA) actuators are promising for miniature applications. They accomplish the shape memorization via a temperature dependent phase transformation process. Control of SMA actuators is challenging because the actuators exhibit highly hysteresis behavior. This paper presents a fuzzy-based position control scheme for a SMA actuated mass system. The control system consists of an outer-and an inner-control loop. The inner loop controls the temperature of the SMA actuators using a PI controller, whereas the outer loop, which is affected by the hysteresis of the SMA actuators, controls the position. To deal with the hysteresis in the position control loop, an adaptive fuzzy sliding-mode control method is adopted. Experimental results illustrate the success of the proposed control scheme.

Abstract: This paper analyzes the differences between electric learner-driven vehicle and fuel cars in the process of turning, and establish a multiple parameter control model from the fuzzy control method, to determine driving resistance changes, and using PWM regulating motor armature voltage to control the rotate speed’s change, at the same time, we use the measured speed as feedback signal to regulate the armature voltage again. Realize the electric motor speed steady in the process of turning, make the electric learner-driven vehicle have the similar driving feeling with the fuel learner-driven vehicle.

Abstract: This paper presents the capability of Arduino for responding to the robust controller which has been applied to the 3 phase rectifier and 3 phase inverter. The interface between the converters and the Arduino has been established by using MATLAB-Simulink environment. This is the fastest interface due the Arduino library that is available in the MATLAB which can be used before downloading the program to the board. Two types of controllers have been tested which are, P-Resonant and Fuzzy-PI controller. The voltage or current feedback mechanism also has been applied between the converters with the Arduino input port in order for responding to the design controller for signal generating pattern. At the end, it shows that, the Arduino is capable to receive the signals from the converters, process the signals in the board and generating the signal out for controlling the converters.