A knowledge-based intelligent system for control of dirt recognition process in the smart washing machines

In this paper, we propose an intelligence approach based on fuzzy logic to modeling human intelligence in washing clothes. At first, an intelligent feedback loop is designed for perception-based sensing of dirt inspired by human color understanding. Then, when color stains leak out of some colored clothes the human probabilistic decision making is computationally modeled to detect this stain leakage and thus the problem of recognizing dirt from stain can be considered in the washing process. Finally, we discuss the fuzzy control of washing clothes and design and simulate a smart controller based on the fuzzy intelligence feedback loop.

[1]  Wang Xiaoling,et al.  Application of the fuzzy logic in content-based image retrieval , 2005 .

[2]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[3]  Arpan Jain,et al.  Alternative to Water Based Fabric Cleaner in Textile and Detergent Processes , 2017 .

[4]  Nadia Naghavi,et al.  Restraining IPMC Back Relaxation in Large Bending Displacements: Applying Non-Feedback Local Gaussian Disturbance by Patterned Electrodes , 2016, IEEE Transactions on Electron Devices.

[5]  Than Zaw Soe,et al.  Operation System of Washing Machine with Fuzzy Logic Control System and Construction of Detergent box , 2016 .

[6]  Nadia Naghavi,et al.  Nonautoregressive Nonlinear Identification of IPMC in Large Deformation Situations Using Generalized Volterra-Based Approach , 2016, IEEE Transactions on Instrumentation and Measurement.

[7]  Mahdi Saadatmand-Tarzjan,et al.  A New Threshold Selection Method Based on Fuzzy Expert Systems for Separating Text from the Background of Document Images , 2018, Iranian Journal of Science and Technology, Transactions of Electrical Engineering.

[8]  Neamat El Gayar,et al.  A new approach in content-based image retrieval using fuzzy , 2009, Telecommun. Syst..

[9]  N. Naghavi,et al.  Non-uniform deformation and curvature identification of ionic polymer metal composite actuators , 2015 .

[10]  Nadia Naghavi,et al.  From modeling to implementation of a method for restraining back relaxation in ionic polymer–metal composite soft actuators , 2018, Journal of Intelligent Material Systems and Structures.

[11]  Nadia Naghavi,et al.  Nonlinear identification of IPMC actuators based on ANFIS–NARX paradigm , 2014 .

[12]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[13]  Deepak Kumar,et al.  Fuzzy Logic Based Control System for Washing Machines , 2013 .

[14]  Sudha Hatagar,et al.  Three Input - One Output Fuzzy logic control of Washing Machine , 2015 .

[15]  Phil Diamond,et al.  Stability and periodicity in fuzzy differential equations , 2000, IEEE Trans. Fuzzy Syst..

[16]  Babak Nadjar Araabi,et al.  INTELLIGENT MODELING AND CONTROL OF WASHING MACHINE USING LOCALLY LINEAR NEURO-FUZZY (LLNF) MODELING AND MODIFIED BRAIN EMOTIONAL LEARNING BASED INTELLIGENT CONTROLLER (BELBIC) , 2008 .

[17]  Tofigh Allahviranloo,et al.  Uncertain Hermite-Hadamard inequality for functions with (s,m)-Godunova-Levin derivatives via fractional integral , 2016 .

[18]  Lior Shamir,et al.  Human Perception-based Color Segmentation Using Fuzzy Logic , 2006, IPCV.

[19]  S. Kasaei,et al.  Object Modeling for Multicamera Correspondence Using Fuzzy Region Color Adjacency Graphs , 2008, CSICC.

[20]  Alexandre Gonçalves Silva,et al.  Automatic Recognition of Vehicle Attributes –Color Classification and Logo Segmentation , 2008 .

[21]  L. Jamshidi,et al.  Solution of the Fuzzy Boundary Value Differential Equations Under Generalized Differentiability By Shooting Method , 2012 .