this work presents a comparative study of two different control strategies for a flexible single-link manipulator. The dynamic model of the flexible manipulator involves modeling the rotational base and the flexible link as rigid bodies using the Euler Lagrange's method. The resulting system has one Degree-Of-Freedom (one DOF) and it provide freedom to increase the degree as well. Two types of regulators are studied, the State-Regulator using Pole Placement, and the LinearQuadratic regulator (LQR). The LQR is obtained by resolving the Ricatti equation, in this work, we apply and compare two strategies to control the tip of the flexible link: state-feedback and linear quadratic regulator. These regulators are designed to reduce tip vibrations and increase system stability due to the flexibility of the arm .

This paper presents a new method using GADS Toolbox in MATLAB (A Genetic Algorithm Approach) to find the optimal solution of optimal power flow based transmission losses. Optimal power flow (OPF) is a key area of concern in electric industries. The basic OPF solution is obtained with objective function as production cost minimization while satisfying a set of system operating constraints. For reactive power optimization the OPF problem is formulated as minimization of system active power losses and improvement in voltage stability of the system. In this paper GA based optimal power flow solution is presented for IEEE 30-bus test power system with objective as transmission losses minimization and optimal results by GA are also compared with solution obtained by using Particle Swarm Optimization Technique.

This paper presents the application of GeneticAlgorithm (GA) for solving optimal power flow problems. It is animportant tool for performance analysis of many power systemsproblems. Optimal power flow (OPF) is of very muchsignificance in power system operation analysis underderegulated environment of electricity industry. The OPFoptimizes a power system operating objective function, whilesatisfying a set of system operating constraints. The basic OPFsolution is obtained with production cost minimization as theobjective function and the optimal settings of the power systemare determined. OPF can also be formulated for reactive poweroptimization, as minimization of system active power losses andimproving the voltage stability in the system. In the presentpaper objective function is to reduce transmission losses usingGA, a IEEE 30-bus test power system is studied for optimalpower flow. It is described in the paper that GA based optimalpower flow can provide optimal solution