AGC of a multi - area system using firefly optimized two degree of freedom PID controller

Author(s):  
Puja Dash ◽  
Lalit Chandra Saikia ◽  
Nidul Sinha
2021 ◽  
Vol 11 (15) ◽  
pp. 6693
Author(s):  
Sagar Gupta ◽  
Abhaya Pal Singh ◽  
Dipankar Deb ◽  
Stepan Ozana

Robotic manipulators have been widely used in industries, mainly to move tools into different specific positions. Thus, it has become necessary to have accurate knowledge about the tool position using forward kinematics after accessing the angular locations of limbs. This paper presents a simulation study in which an encoder attached to the limbs gathers information about the angular positions. The measured angles are applied to the Kalman Filter (KF) and its variants for state estimation. This work focuses on the use of fractional order controllers with a Two Degree of Freedom Serial Flexible Links (2DSFL) and Two Degree of Freedom Serial Flexible Joint (2DSFJ) and undertakes simulations with noise and a square wave as input. The fractional order controllers fit better with the system properties than integer order controllers. The KF and its variants use an unknown and assumed process and measurement noise matrices to predict the actual data. An optimisation problem is proposed to achieve reasonable estimations with the updated covariance matrices.


Author(s):  
Debasis Tripathy ◽  
Nalin Behari Dev Choudhury ◽  
Binod Kumar Sahu

Automatic generation control (AGC) is an automation scheme that regulates the output of several generators employed at different areas of an interconnected power system simultaneously in response to load variation in the most economical way. This article implements a fuzzy-two degree of freedom-PID controller considering derivative filter (F-2D-PIDF) optimally tuned through grasshopper optimization algorithms (GOA) for AGC of a three unequal area interconnected power system. Initially, comparative performance analysis is carried out for conventional PID controllers optimally designed by particle swarm optimization, teaching learning-based optimization and GOA techniques. After ensuring better performance from GOA based PID controller, the study extended to establish dominance of the proposed F-2D-PIDF controller over others like PID, PID with derivative filter (PIDF), two degree of freedom-PIDF, and fuzzy-PIDF for the same power system in presence and absence of nonlinearities with GOA framework. In all these above studies, a load perturbation of 0.01 p.u. is applied in area-1. Comparative performance analysis reveals that GOA based F-2D-PIDF controller outperforms other controllers in all aspects. Finally, robustness of the proposed controller verified by varying system parameters and loading condition.


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