The paper focuses on the problem of robust fault detection using neurofuzzy model based strategies. The main objective of the work is to show how to employ bounding error approach to determine the uncertainty of the neurofuzzy model and next utilize this knowledge for robust fault detection. The paper presents also how to tackle the problem of choosing the right structure of the neurofuzzy mode...

Agriculture is the most important sector in Indian economy. India world's second-largest producer of sugarcane. Study undertaken at Shirol tehsil. Kolhapur district, Maharashtra state, with aim modeling sugarcane production forecasting using supervised machine learning algorithms. Sugarcane mostly cultivated crop this area. We applied for productivity village wise based on ten year’s data about...

Abstract: A paper deals with application of stochastic methods for dynamic neural network training. The considered network is composed of dynamic neurons, which contain inner feedbacks. This network can be used as a part of a fault diagnosis system to generate residuals. Up-to-date training algorithms, based on the classical back propagation, suffer from entrapment in local minima of an error f...

The early detection of faults (just beginning and still developing) can help avoid system shutdown, breakdown and even catastrophes involving human fatalities and material damage. Computational intelligence techniques are being investigated as an extension to the traditional fault diagnosis methods. This paper discusses the neuro-fuzzy approach to modelling and fault diagnosis, based on the TSK...

This paper shows the application of a 2DOF robust discrete deadtime compensator to a evaporation process in a sugar factory. The proposed controller is tuned using performance and robustness specifications and it is specially designed for integrative plants as is the case of the level control of the principal unit of the evaporator. A comparative analysis with the PID installed in the unit is p...

Silica presents a particularly challenging problem to the Silica remains one of the most common and problematic components in cane sugar juice evaporator scale. The relationship between silica concentration in clear juice and its precipitation in the evaporator train is considered. Methods of reducing silica levels in clear juice through changes in the extraction conditions are investigated thr...

sugar beet cyst nematode (heterodera schachtii schmidt) is transferred to sugar factories along with the sugar beet root and its surrounding soil, so called depot soil. because of high infestation and the possible transfer and distribution of this soil, disinfestations of the depot soil should be taken into considerations. in order to assess the possibility for disinfestations of the depot soil...

The paper addresses the development of neural observer schemes for process fault diagnosis. The design is based on a generalised functional-link neural network with internal dynamics. An evolutionary search of genetic type and multiobjective optimisation in the Pareto-sense is used to determine the optimal architecture of the dynamic network. Symptoms characterising the current state of the pro...

This study investigated the different performance levels of the workers in the Chittoor Sugar factory located at the Chittoor town of South India. It was also studied how the factors education and work experience influence the performance levels of the workers in the firm. Upon study it has been understood that the two variables under investigation have direct effect on the performance of the w...

The early detection of faults (just beginning and still developing) can help avoid system shutdown, breakdown and even catastrophes involving human fatalities and material damage. Computational intelligence techniques are being investigated as extension of the traditional fault diagnosis methods. This paper discusses the properties of the TSK/Mamdani approaches and neuro-fuzzy (NF) fault diagno...