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Barjeev Tyagi

Researcher at Indian Institute of Technology Roorkee

Publications -  101
Citations -  1832

Barjeev Tyagi is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Automatic Generation Control & PID controller. The author has an hindex of 17, co-authored 88 publications receiving 1426 citations.

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Optimal placement of different type of DG sources in distribution networks

TL;DR: The particle swarm optimization (PSO) technique has been used to solve the optimal placement of DGs and the optimal power factor for DG supplying, both real and reactive power, has been obtained.
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Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks

TL;DR: In this paper, a hybrid approach has been proposed for optimal placement of multiple DGs of multiple types in power distribution network for reduction of power loss, where the sizes of DGs are evaluated at each bus by analytical method while the locations are determined by PSO based technique.
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Optimal Control of Nonlinear Inverted Pendulum System Using PID Controller and LQR: Performance Analysis Without and With Disturbance Input

TL;DR: Linear quadratic regulator (LQR) and proportional-integral-derivative (PID) control methods, which are generally used for control of linear dynamical systems, are used in this paper to control the nonlinear dynamical system.
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Genetic algorithm based support vector machine for on-line voltage stability monitoring

TL;DR: In this article, a GA-SVM approach for online monitoring of long-term voltage instability has been proposed, which uses the voltage magnitude and phase angle obtained from Phasor Measurement Units (PMUs) as the input vectors to SVM and the output vector is the voltage Stability Margin Index (VSMI).
Proceedings ArticleDOI

Optimal control of nonlinear inverted pendulum dynamical system with disturbance input using PID controller & LQR

TL;DR: Linear quadratic regulator (LQR), an optimal control method, and PID control which are generally used for control of the linear dynamical systems have been used in this paper to control the nonlinear dynamical system.