Hybrid Systems Control

Abstract At the most fundamental biological level the brain can be regarded as an organ which functions as a controller of basic homeostatic processes. In terms of its primary structure the brain is grossly composed of three parts: the brain stem, the cerebellum, and the cerebrum. Control is carried out at an innate level by the brain stem, and at a learning based level by the cerebellum and cerebrum. The "hybrid" control facilitated by the interaction of the cerebellum and cerebrum involves communication between the two learning based systems, and this is a particularly important feature in relation to understanding psychological processes. It is proposed that, as a starting point for understanding the function of the brain and its relationship to psychological development and psychological processes, the "core architecture" of the brain can most usefully be described a three tier nested hierarchy of brainstem, cerebellum cerebrum.

Named Entity Recognition is a prior task in Natural Language Processing. Named Entity Recognition is a sub task of information extraction and it identifies and classifies proper nouns in to its predefined categories such as person, location, organization, time, date etc. In this document the major focus is given on NER approaches and the work done till now for various languages to identify Named Entities is been discussed. Author have done comparative study to recognize named entity and identified that CRF approach proven best for Indian languages to identify named entity.

—Surveillance missions for multiple autonomous underwater vehicle (AUV) system suggest the use of different modes of operation including organizing and keeping a predefined formation, avoiding obstacles, reaching static and tracking dynamic targets. While exploiting a leader-follower strategy to formation control and the vector Lyapunov function method to controller design, we use discrete-event approach and supervisory control theory to switch between operational modes.

In this paper, a hybrid supervisory control approach adopted for a noninvasive medical robot called Focused Ultrasound Surgical Robot-Breast Surgery (FUSBOT-BS) is elaborated. The system was built for the use in the breast surgery with high intensity focused ultrasound (HIFU) as the means of the treatment. A number of different control strategies such as PID and model-based control were incorporated into a family of controllers to create the hybrid control. Depending on the objective, the supervisory control determines the type of controller used for the specified task so as to maximize the advantages of each of the controllers. Before it was implemented into the actual robotic system the then proposed control approach was modeled and simulated using Matlab®. This control approach was developed based on a review of popular control approaches used in medical robotic systems, in order to look at the feasibility of having a uniform control strategy for a spectrum of medical robotic system. With unified control strategy it is possible to have a safety standard regulation for the medical robotic systems which is currently difficult to be done because of various control strategies adopted by each of the medical robotic systems.

Optical Character Recognition (OCR) is the process which enables a system to without human intervention identifies the scripts or alphabets written into the users' verbal communication. Optical Character identification has grown to be individual of the mainly flourishing applications of knowledge in the field of pattern detection and artificial intelligence. In our survey we study on the various OCR techniques. In this paper we resolve and examine the hypothetical and numerical models of Optical Character Identification. The Optical character identification or classification (OCR) and Magnetic Character Recognition (MCR) techniques are generally utilized for the recognition of patterns or alphabets. In general the alphabets are in the variety of pixel pictures and it could be either handwritten or stamped, of any series, shape or direction etc. Alternatively in MCR the alphabets are stamped with magnetic ink and the studying machine categorize the alphabet on the basis of the exclusive magnetic field that is shaped by every alphabet. Both MCR and OCR discover utilization in banking and different trade appliances. Earlier exploration going on Optical Character detection or recognition has shown that the In Handwritten text there is no limitation lying on the script technique. Hand written correspondence is complicated to be familiar through due to diverse human handwriting style, disparity in angle, size and shape of calligraphy. An assortment of approaches of Optical Character Identification is discussed here all along through their achievement.

Complex systems, which consist of different interdependent and interlocking subsystems, typically have multiple equilibrium points associated with different set points of each operation mode. These systems are usually interpreted as hybrid systems. This paper studies the conditions for dissipativity and some stability properties of a class of hybrid systems with multiple co-existing equilibrium points, modelled as nonlinear hybrid automata. A classification of equilibria for hybrid automata is proposed. The objective is to identify dissipative components as groups of discrete locations within the hybrid automaton, formed according to existing equilibria. An example is provided.

This paper proposes a hybrid control scheme for the synchronization of two chaotic Duffing oscillator system, subject to uncertainties and external disturbances. The novelty of this scheme is that the Linear Quadratic Regulation (LQR) control, Sliding Mode (SM) control and Gaussian Radial basis Function Neural Network (GRBFNN) control are combined to chaos synchronization with respect to external disturbances. By Lyapunov stability theory, SM control is presented to ensure the stability of the controlled system. GRBFNN control is trained during the control process. The learning algorithm of the GRBFNN is based on the minimization of a cost function which considers the sliding surface and control effort. Simulation results demonstrate the ability of the hybrid control scheme to synchronize the chaotic Duffing oscillator systems through the application of a single control signal.

In this paper, we study the Direct Torque Control (DTC) of an Induction Motor coupled to an Inverter (Inv-IM). DTC permits to control directly the stator flux and the torque by selecting the appropriate inverter state. DTC has been introduced because it presents several advantages in comparison to other techniques such as voltage/frequency control, vector control and field control. In this paper, we first model the DTC of Inv-IM as a hybrid system (HS). Then, we abstract the continuous dynamics of the HS in terms of discrete events. We thus obtain a discrete event model of the HS. And finally, we use Supervisory Control Theory of DES to drive Inv-IM to a desired working point.