Speed sensorless field oriented control of ac induction motor using model reference adaptive system

In order implement the vector control technique, the motor speed information is required. Incremental encoder, resolvers and tachogenerator, are used to reveal the speed. These sensors require careful mounting and alignment and special attention is required with electrical noises. Sensorless speed vector control is greatly used and applied in induction machine drives instead of scalar control and vector control for their robustness and reliability, and very low maintenance cost. In this project MRAS based techniques are used to estimate the rotor speed based on rotor flux estimation, the estimated speed in the MRAS algorithm is used as a feedback for the vector control system. The model reference adaptive control system is predicated on the comparison between the outputs of adjustable model and reference model. The error between them is employed to drive a suitable adaptation mechanism which generates the estimated rotor speed for the adjustable model. And indirect vector control scheme controls the flux and torque by restricting the torque and flux errors with respective hysteresis bands, and motor flux and torque are controlled by the stator voltage space vectors using optimum inverter switching table. Modeling and simulation of the induction machine and the vector control drives implemented in MATLAB/SIMULINK. Simulation results of proposed MRAS and indirect vector control technique are presented

The Simultaneous Strong Resolving Graph and the Simultaneous Strong Metric Dimension of Graph Families

We consider in this work a new approach to study the simultaneous strong metric dimension of graphs families, while introducing the simultaneous version of the strong resolving graph. In concordance, we consider here connected graphs G whose vertex sets are represented as V(G), and the following terminology. Two vertices u,v is an element of V(G) are strongly resolved by a vertex w is an element of V(G), if there is a shortest w-v path containing u or a shortest w-u containing v. A set A of vertices of the graph G is said to be a strong metric generator for G if every two vertices of G are strongly resolved by some vertex of A. The smallest possible cardinality of any strong metric generator (SSMG) for the graph G is taken as the strong metric dimension of the graph G. Given a family F of graphs defined over a common vertex set V, a set S subset of V is an SSMG for F, if such set S is a strong metric generator for every graph G is an element of F. The simultaneous strong metric dimension of F is the minimum cardinality of any strong metric generator for F, and is denoted by Sds(F). The notion of simultaneous strong resolving graph of a graph family F is introduced in this work, and its usefulness in the study of Sds(F) is described. That is, it is proved that computing Sds(F) is equivalent to computing the vertex cover number of the simultaneous strong resolving graph of F. Several consequences (computational and combinatorial) of such relationship are then deduced. Among them, we remark for instance that we have proved the NP-hardness of computing the simultaneous strong metric dimension of families of paths, which is an improvement (with respect to the increasing difficulty of the problem) on the results known from the literature