Auto-landing of UAVs with variable centre of mass using the backstepping and dynamic inversion control

We introduce a method for edge detection which is based on clustering the pixels representing any given digital image into two sets (the edge pixels and the non-edge ones). The process is based on associating to each pixel an appropriate vector representing the differences in brightness w.r.t. the surrounding pixels. Clustering is driven by the norms of such vectors, thus it takes place in $$\mathbb {R}$$
 , which allows us to use a (simple) DC (Difference of Convex) optimization algorithm to get the clusters. A novel thinning technique, based on calculation of the edge phase angles, refines the classification obtained by the clustering algorithm. The results of some numerical experiments are also provided.

A DC optimization-based clustering technique for edge detection

In this paper, a novel observer structure for nonlinear fractional-order systems is presented to estimate the states of fractional-order nonlinear chaotic system with unknown dynamical model. A new fractional error back-propagation learning algorithm is derived to adapt weights of the artificial neural network, by taking advantage of the Lyapunov stability strategy of fractional-order systems which is called Miattag–Leffler stability. The main contribution is the extension of neural observer for fractional dynamics in a way that satisfies Miattag–Leffler conditions. Observer design procedure guarantees the convergence of observer error to the neighborhood of zero. Furthermore, the robustness of the proposed estimator against uncertainties and external disturbances are the main benefits of the proposed method. Simulation results show the effectiveness and capabilities of the proposed observer.

Fractional neural observer design for a class of nonlinear fractional chaotic systems

This contribution deals with the proposal of direct torque control (DTC) for Induction Motor (IM) with the use of artificial neural networks (ANN) to increase the system's performance. Model Reference Adaptive System (MRAS) method is used for the estimation and regulation of rotor's speed. The whole structure of DTC is designed by Matlab/Simulink. The neural controller is designed using neural Toolbox, and the system's performance is compared with conventional DTC.

Direct torque control of Induction Motor based on artificial neural networks speed control using MRAS and neural PID controller

Due to the wind characteristic, wind speed measure requires more than one sensor. However, to track the maximum power point of the wind, knowing the wind speed or mechanical speed is necessary. So,...

Artificial neural network–based sensorless control of wind energy conversion system driving a permanent magnet synchronous generator:

In this paper, we investigate the problem of Neural Network (NN) observer for nonlinear systems Therefore, it can be applied to systems with higher degree of nonlinearity with any a priory knowledge about system dynamics The proposed neuro-observer is a three-layer feedforward neural network, which is trained extensively with the error backpropagation learning algorithm including a correction term to guarantee good tracking as well as bounded NN weights Furthermore, the Lyapunov’s direct method is used in order to ensuring the stability of the proposed non-conventional observer and of the NN weight errors The effectiveness of the proposed state observer scheme is demonstrated through numerical simulation to reconstruct the unavailable state variables of an induction motor (IM) and especially the rotor flux despite the effect of the arisen parameters such as the load torque which is also reconstructed using the NN observer

Neural Network Observer for Nonlinear Systems Application to Induction Motors 1

Edge detection is a problem of fundamental importance in image analysis. Many approaches for edge detection have already revealed more are waiting to be. But edge detection using K-means algorithm is the most heuristic and unique approach. In this paper, we have proposed an algorithmic technique to detect the edge of any kind of true gray scale images considering the artificial features of the image as the feature set which is fed to K-Means algorithm for clustering the image and there to detect clearly the edges of the objects present in the considered image. The artificial features, which we have considered here, are mean, standard deviation, entropy and busyness of pixel intensity values.

A Novel Approach for Edge Detection of Images

At present, information Management using mobile phone in Wireless Sensor Network is the commonest factor. Mobile phone will be the main access point in Wireless Sensor Network. The system will be as simple as possible providing all the facilities those are available in web based rather PC based applications regarding this. A wireless mesh network furnishes the WSN and the mobile phones are going to be the nodes or access points of this network Not only the queries of mobile users, some predefined activities like error messages or warning messages after sensing the system environment can also be available in this system. A simple user friendly GUI is implemented for user. There is a server to authenticate the logged in user, listen to the requests submitted by user and replies them accordingly. The user has two choices using which he/she can get the required information namely (i) get the reports regarding all/individual tags and or routes, emergency messages, sensors and also the location information; (ii) send actuation command to the server using which immediate decision about the system can be taken from server side. The user can see the report in their phone’s display screen. Thus to communicate with WSN anywhere, anytime can assist any remote user most efficiently.

Urban Computing and Information Management System Using Mobile Phones in Wireless Sensor Network

This paper is meant for a heuristic approach for the refinements of corpus based on regular expressions and its possible applications in the field of Opinion Mining. Corpus which is the plural form of ‘corpora’ is nothing but the collection of linguistic data. And here the proposed work is based on a corpus of reviews; more specifically product reviews. The reviews are in the html files which are easily available in popular review sites like Cnet.com. The revolution in information and technologies has given a new era in the development of language industries. The versatility in technological development, along with the translations available in different languages has lead to use of this corpus for specific machine learning mechanism as well as various automatic translation applications. But the prime objective of researchers as well as the naive users is to give a fast developing technique of machine learning systems that should be both exact and effective. Most of the time it becomes a very tedious job to create exact dataset for the work due to the crisis of accurate corpus regarding respective research work. And that is why; we have proposed an algorithm for creating a corpus for opinion mining research field.

Refine Crude Corpus for Opinion Mining

Extracting specific information from a collection of documents is called Information Extraction (IE). In general, the information on the web is well structured in HTML or XML format. And the work of IE from structured documents (in HTML or XML), basically uses learning techniques for pattern matching in the content. In this paper, we have proposed a novel approach for interactive information extraction technique. Here, we have described how this approach enables any naive user to extract Indian regional language based document from a web document efficiently which is quite similar to a standard search engine. It is just similar to a pre-programmed information extraction engine.

Kheyali Mitra

Papers

Neural Network Observer for Nonlinear Systems Application to Induction Motors 1

A Novel Approach for Edge Detection of Images

Urban Computing and Information Management System Using Mobile Phones in Wireless Sensor Network

Refine Crude Corpus for Opinion Mining

A Novel Approach for Designing Indian Regional Language Based Raw-Text Extractor and Unicode Font-Mapping Tool