Using Enviromental Models Approximated by Fuzzy Identification for Hybrid Planning of Mechatronic Systems

2008 ◽  
Author(s):  
Alexander Schmidt ◽  
Philipp Adelt ◽  
Natascha Esau ◽  
Lisa Kleinjohann ◽  
Bernd Kleinjohann
Keyword(s):  
Fuzzy Logic ◽  
Environment Modeling ◽  
Mechatronic Systems ◽  
Fuzzy Identification ◽  
Course Of Action ◽  
Future System ◽  
Continuous Domains ◽  
Adjustment System ◽  
Hybrid Planning

Above the controller level a lot of components are needed in mechatronic systems for the development towards self-optimizing systems. One of these components is a hybrid planning architecture. This architecture integrating discrete and continuous domains is of major importance to support the permanent determination of system objectives and their implementation during the course of action. Through this the principle of self-optimizing mechatronic systems is defined as well. Such a novel hybrid planning architecture is outlined in this paper. In order to plan efficiently and safely, environment models are needed for predicting future system behaviors. In this paper we propose a fuzzy logic based approach to environment modeling and apply it in a railway-bound domain within the context of an air gap adjustment system for a dual-fed linear motor powering a wheeled train.

Hybrid Planning for an Air Gap Adjustment System Using Fuzzy Models

2009 ◽  
Vol 21 (5) ◽  
pp. 647-655 ◽  
Author(s):  
Philipp Adelt ◽  
◽  
Natascha Esau ◽  
Alexander Schmidt ◽  
Keyword(s):  
Air Gap ◽  
System Operation ◽  
Mechatronic Systems ◽  
Fuzzy Models ◽  
Vehicle System ◽  
Ongoing Effort ◽  
Continuous Domains ◽  
Adjustment System ◽  
Planning Problems ◽  
Hybrid Planning

Hybrid planning is an approach to couple continuous domains commonly found in mechatronic systems with discrete planning problems. An ongoing effort to bring self-optimization as a design means of improved overall system operation quality to mechatronic systems is the overall frame that this approach is embedded in. An innovative rail-bound vehicle system propelled by a linear motor employs an Air Gap Adjustment System to control the air gap between the two motor parts and is presented as an application to the concept.

Design of back propagation optimized Nagar-Bardini structure-based interval type-2 fuzzy logic systems for fuzzy identification

2021 ◽  
pp. 014233122110066
Author(s):  
Yang Chen ◽  
Jiaxiu Yang
Keyword(s):  
Fuzzy Logic ◽  
Back Propagation ◽  
Membership Functions ◽  
Identification Problems ◽  
Fuzzy Logic Systems ◽  
Fuzzy Identification ◽  
Logic Systems ◽  
Academic Topic ◽  
Interval Type

In recent years, fuzzy identification based on system identification theory has become a hot academic topic. Interval type-2 fuzzy logic systems (IT2 FLSs) have become a rising technology. This paper designs a type of Nagar-Bardini (NB) structure-based singleton IT2 FLSs for fuzzy identification problems. The antecedents of primary membership functions of IT2 FLSs are chosen as Gaussian type-2 primary membership functions with uncertain standard deviations. Then, the back propagation algorithms are used to tune the parameters of IT2 FLSs according to the chain rule of derivation. Compared with the type-1 fuzzy logic systems, simulation studies show that the proposed IT2 FLSs can obtain better abilities of generalization for fuzzy identification problems.

scholarly journals Hybrid Planning for Self-Optimization in Railbound Mechatronic Systems

10.5772/15451 ◽  
2011 ◽  
Author(s):  
Philipp Adelt ◽  
Natalia Esau ◽  
Christian Hlscher ◽  
Bernd Kleinjohann ◽  
Lisa Kleinjohann ◽  
...  
Keyword(s):  
Mechatronic Systems ◽  
Hybrid Planning

Classification of journal bearing friction states based on acoustic emission signals

2018 ◽  
Vol 85 (6) ◽  
pp. 434-442 ◽  
Author(s):  
Noushin Mokhtari ◽  
Clemens Gühmann
Keyword(s):  
Acoustic Emission ◽  
Time Domain ◽  
Journal Bearing ◽  
Prediction Method ◽  
Support Vector ◽  
Mechatronic Systems ◽  
Prediction Time ◽  
Ae Signals ◽  
Bearing Friction

Abstract For diagnosis and predictive maintenance of mechatronic systems, monitoring of bearings is essential. An important building block for this is the determination of the bearing friction condition. This paper deals with the possibility of monitoring different journal bearing friction states, such as mixed and fluid friction, and examines a new approach to distinguish between different friction intensities under several speed and load combinations based on feature extraction and feature selection methods applied on acoustic emission (AE) signals. The aim of this work is to identify separation effective features of AE signals to subsequently classify the journal bearing friction states. Furthermore, the acquired features give information about the mixed friction intensity, which is significant for remaining useful lifetime (RUL) prediction. Time domain features as well as features in the frequency domain have been investigated in this work. To increase the sensitivity of the extracted features the AE signals were transformed to the frequency-time-domain using continuous wavelet transform (CWT). Significant frequency bands are determined to separate different friction states more effective. A support vector machine (SVM) is used to classify the signals into three different friction classes. In the end the idea for an RUL prediction method by using the already determined information is given and explained.

scholarly journals Penerapan metode fuzzy sugeno untuk prediksi persediaan bahan baku

2019 ◽  
Vol 9 (2) ◽  
pp. 12-20
Author(s):  
Julio Warmansyah ◽  
Dida Hilpiah
Keyword(s):  
Fuzzy Logic ◽  
Raw Materials ◽  
Mean Absolute Percentage Error ◽  
Raw Material ◽  
Percentage Error ◽  
Human Power ◽  
Absolute Percentage Error ◽  
Input Variables ◽  
A Company

 PT. Cahaya Boxindo Prasetya is a company engaged in the manufacture of carton boxes or boxes. The company's activities also include cutting and printing services using machinery and human power. The problem faced in this company is the difficulty of predicting the amount of inventory of raw materials that will be  included in the production. The remaining raw materials for production will be used as the final stock to get the minimum, the goal is to reduce excess stock Overcoming this problem, fuzzy logic is used to predict raw material inventories by focusing on the final stock. In this study using Fuzzy Sugeno, with three input variables, namely: initial inventory, purchase, production, while the output is the final stock. Determination of prediction results using defuzzification using the average concept of MAPE (Mean Absolute Percentage Error). The results obtained, using the Fuzzy Sugeno method can predict the inventory of raw materials with a MAPE value of 38%. 

scholarly journals DETERMINATION OF COST OF PRODUCTION IN CONDITIONS OF UNCERTAINTY OF ORDERS

2016 ◽  
Vol 4 (4) ◽  
pp. 499-504
Author(s):  
Ольга Глод ◽  
Olga Glod ◽  
Виктор Ланкин ◽  
Viktor Lankin
Keyword(s):  
Fuzzy Logic ◽  
Expert Knowledge ◽  
Small Enterprises ◽  
Methodological Basis ◽  
Cost Of Production ◽  
The Cost

The purpose of this paper is to examine the model to determine the cost of production of small enterprises. The methodological basis for the model is a fuzzy logic based on expert knowledge. As a result, in this paper we consider an example of the model, determined the cost of production of confectionery

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