Current Issue : April - June Volume : 2015 Issue Number : 2 Articles : 7 Articles
This paper presents a dynamic characteristic-based fuzzy adaptive control algorithm (DCbFACA) to avoid the influence of cutting\nforce changing rapidly on the machining stability and precision. The cutting force is indirectly obtained in real time by monitoring\nand extraction of the motorized spindle current, the feed speed is fuzzy adjusted online, and the current was used as a feedback\nto control cutting force and maintain the machining process stable. Different from the traditional fuzzy control methods using the\nexperience-based control rules, and according to the complex nonlinear characteristics of CNC machining, the power bond graph\nmethod is implemented to describe the dynamic characteristics of process, and then the appropriate variation relations are achieved\nbetween current and feed speed, and the control rules are optimized and established based on it.The numerical results indicated\nthat DCbFACA can make the CNC machining process more stable and improve the machining precision....
The emergence of complex machinery and equipment in several areas demands efficient fault diagnosis methods. Several fault\ndiagnosis methods based on different theories and approaches have been proposed in the literature. According to the concept of\nintelligent maintenance, the application of intelligent systems to accomplish fault diagnosis from process historical data has been\nshown to be a promising approach. In problems involving complex nonstationary dynamic systems, an adaptive fault diagnosis\nsystem is required to cope with changes in the monitored process. In order to address fault diagnosis in this scenario, use of the\nso-called ââ?¬Å?evolving intelligent systemsââ?¬Â is suggested. This paper proposes the application of an evolving fuzzy classifier for fault\ndiagnosis based on a new approach that combines a recursive clustering algorithm and a drift detection method. In this approach,\nthe clustering update depends not only on a similarity measure, but also on the monitoring changes in the input data flow. A\nmerging cluster mechanism was incorporated into the algorithm to enable the removal of redundant clusters.Multivariate Gaussian\nmemberships functions are employed in the fuzzy rules to avoid information loss if there is interaction between variables.Thenovel\napproach provides greater robustness to outliers and noise present in data from process sensors. The classifier is evaluated in fault\ndiagnosis of a DC drive system. In the experiments, a DC drive system fault simulator was used to simulate normal operation\nand several faulty conditions. Outliers and noise were added to the simulated data to evaluate the robustness of the fault diagnosis\nmodel....
The scope of this paper is to present a fuzzy logic control of a class of multi-input multi out put (MIMO) nonlinear systems\ncalled ââ?¬Å?system of ball on a sphere,ââ?¬Â such an inherently nonlinear, unstable, and under actuated system, considered truly to be two\nindependent ball and wheel systems around its equilibrium point. In this work, Sugeno method is investigated as a fuzzy controller\nmethod, so it works in a good state with optimization and adaptive techniques, which makes it very attractive in control problems,\nparticularly for such nonlinear dynamic systems.The systemââ?¬â?¢s dynamic is described and the equations are illustrated.The outputs are\nshown in different figures so as to be compared. Finally, these simulation results show the exactness of the controllerââ?¬â?¢s performance....
Since 1965 when the fuzzy logic and fuzzy algebra were introduced by Lotfi Zadeh, the fuzzy theory successfully found its\napplications in the wide range of subject fields. This is mainly due to its ability to process various data, including vague or uncertain\ndata, and provide results that are suitable for the decision making. This paper aims to provide comprehensive overview of literature\non fuzzy control systems used for the management of the road traffic flow at road junctions. Several theoretical approaches\nfrom basic fuzzy models from the late 1970s to most recent combinations of real-time data with fuzzy inference system and\ngenetic algorithms are mentioned and discussed throughout the paper. In most cases, fuzzy logic controllers provide considerable\nimprovements in the efficiency of traffic junctions� management....
Soft sets have been regarded as a useful mathematical tool to deal with uncertainty. In recent years, many scholars have shown\nan intense interest in soft sets and extended standard soft sets to intuitionistic fuzzy soft sets, interval-valued fuzzy soft sets, and\ngeneralized fuzzy soft sets. In this paper, hesitant fuzzy soft sets are defined by combining fuzzy soft sets with hesitant fuzzy sets. And\nsome operations on hesitant fuzzy soft sets based on Archimedean t-norm and Archimedean t-conorm are defined. Besides, four\naggregation operations, such as the HFSWA, HFSWG, GHFSWA, and GHFSWG operators, are given. Based on these operators,\na multicriteria group decision making approach with hesitant fuzzy soft sets is also proposed. To demonstrate its accuracy and\napplicability, this approach is finally employed to calculate a numerical example....
A two-mass fuzzy control system is considered. For fuzzification process, classical both linear and nonlinear membership functions\nare used. To find optimal values of membership function�s parameters, genetic algorithm is used. To take into account values of both\noutput and intermediate parameters of the system, a penalty function is considered. Research is conducted for the case of speed\ncontrol system and displacement control system. Obtained results are compared with the case of the system with classical, crisp\ncontroller....
We give the simple general principle of studying the relations among fuzzy t-filters on residuated lattices.Using the general principle,\nwe can easily determine the relations among fuzzy t-filters on different logical algebras....
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