R
Rabindra Kumar Sahu
Researcher at Veer Surendra Sai University of Technology
Publications - 68
Citations - 3337
Rabindra Kumar Sahu is an academic researcher from Veer Surendra Sai University of Technology. The author has contributed to research in topics: PID controller & Control theory. The author has an hindex of 21, co-authored 61 publications receiving 2552 citations. Previous affiliations of Rabindra Kumar Sahu include KIIT University & Indian Institute of Technology Madras.
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DE optimized parallel 2-DOF PID controller for load frequency control of power system with governor dead-band nonlinearity
TL;DR: In this article, a two area thermal system with governor dead-band nonlinearity is considered for the design and analysis purpose and differential evolution (DE) algorithm based on parallel 2-Degree Freedom of Proportional-Integral-Derivative (2-DOF PID) controller for Load Frequency Control (LFC) of interconnected power system is presented.
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A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems
TL;DR: The superiority of the proposed fuzzy PI controller has been shown by comparing the results with Bacteria Foraging Optimization Algorithm (BFOA), Genetic Al algorithm (GA), conventional Ziegler Nichols (ZN), Differential Evolution (DE) and hybrid BFOA and PSO based PI controllers for the same interconnected power system.
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A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems
TL;DR: In this paper, a hybrid Firefly Algorithm and Pattern Search (hFA-PS) technique is proposed for automatic generation control of multi-area power systems with the consideration of Generation Rate Constraint (GRC).
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Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system
TL;DR: In this paper, the design and performance analysis of differential evolution algorithm based Proportional Integral Time multiply Absolute Error (ITAE), damping ratio of dominant eigenvalues and settling time with appropriate weight coefficients are derived in order to increase the performance of the controller.
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Teaching learning based optimization algorithm for automatic generation control of power system using 2-DOF PID controller
TL;DR: The supremacy of the proposed 2-DOF PID controller has been shown by comparing the results with recently published technique such as conventional ZN, GA, BFOA, DE and hBFOA-PSO based PI controllers for the same system.