scholarly journals Enhanced Chaotic Grasshopper Optimization Algorithm Based PID Controller for Automatic Voltage Regulator System

2019 ◽  
Vol 8 (4) ◽  
pp. 348-354
Keyword(s):  
Optimization Algorithm ◽  
Pid Controller ◽  
Controller Design ◽  
System Response ◽  
Voltage Regulator ◽  
Minimum Error ◽  
Avr System ◽  
Grasshopper Optimization Algorithm ◽  
Pid Controller Design ◽  
Grasshopper Optimization

This work presents, the PID controller design for AVR system using Enhanced Chaotic Grasshopper Optimization Algorithm (ECGOA). The system response under the different settings are studied with PID controller for stable and minimum error operation. The gain of the controller revealed from traditional methods to recent optimization algorithm. The ECGOA will be implemented for AVR system with PID controller and the performance in-terms of transient response, robustness, stability and error is compared with existing optimization algorithm. The ECGOA based PID controller provides good response and examined upto ±50% of variation in several component of AVR system

scholarly journals Salp Swarm Optimization Algorithm-Based Fractional Order PID Controller for Dynamic Response and Stability Enhancement of an Automatic Voltage Regulator System

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1472 ◽  
Author(s):  
Ismail Akbar Khan ◽  
Ali S. Alghamdi ◽  
Touqeer Ahmed Jumani ◽  
Arbab Alamgir ◽  
Ahmed Bilal Awan ◽  
...  
Keyword(s):  
Dynamic Response ◽  
Fractional Order ◽  
Optimization Algorithm ◽  
Pid Controller ◽  
Robustness Analysis ◽  
Operating Conditions ◽  
Voltage Regulator ◽  
Swarm Optimization ◽  
Automatic Voltage Regulator ◽  
Avr System

Owing to the superior transient and steady-state performance of the fractional-order proportional-integral-derivative (FOPID) controller over its conventional counterpart, this paper exploited its application in an automatic voltage regulator (AVR) system. Since the FOPID controller contains two more control parameters (µ and λ ) as compared to the conventional PID controller, its tuning process was comparatively more complex. Thus, the intelligence of one of the most recently developed metaheuristic algorithms, called the salp swarm optimization algorithm (SSA), was utilized to select the optimized parameters of the FOPID controller in order to achieve the optimal dynamic response and enhanced stability of the studied AVR system. To validate the effectiveness of the proposed method, its performance was compared with that of the recently used tuning methods for the same system configuration and operating conditions. Furthermore, a stability analysis was carried out using pole-zero and bode stability criteria. Finally, in order to check the robustness of the developed system against the system parameter variations, a robustness analysis of the developed system was undertaken. The results show that the proposed SSA-based FOPID tuning method for the AVR system outperformed its conventional counterparts in terms of dynamic response and stability measures.

APPLICATION OF NOVEL REINFORCEMENT LEARNING AUTOMATA APPROACH IN POWER SYSTEM REGULATION

2009 ◽  
Vol 18 (08) ◽  
pp. 1609-1625 ◽  
Author(s):  
MOHAMMAD KASHKI ◽  
YOUSSEF L. ABDEL-MAGID ◽  
MOHAMMAD A. ABIDO
Keyword(s):  
Reinforcement Learning ◽  
Pid Controller ◽  
Controller Design ◽  
Learning Automata ◽  
Synchronous Generator ◽  
Optimization Method ◽  
Avr System ◽  
Pid Controller Design ◽  
Analytical System ◽  
Reinforcement Learning Automata

In this paper, a novel efficient optimization method based on reinforcement learning automata (RLA) for optimum parameters setting of conventional proportional-integral-derivative (PID) controller for AVR system of power synchronous generator is proposed. The proposed method is Combinatorial Discrete and Continuous Action Reinforcement Learning Automata (CDCARLA) which is able to explore and learn to improve control performance without the knowledge of the analytical system model. This paper demonstrates the full details of the CDCARLA technique and compares its performance with Particle Swarm Optimization (PSO) as an efficient evolutionary optimization method. The proposed method has been applied to PID controller design. The simulation results show the superior efficiency and robustness of the proposed method.

scholarly journals Fractional Order PID Controller Design for an AVR System Using Chaotic Yellow Saddle Goatfish Algorithm

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1182 ◽  
Author(s):  
Mihailo Micev ◽  
Martin Ćalasan ◽  
Diego Oliva
Keyword(s):  
Fractional Order ◽  
Controller Design ◽  
Step Response ◽  
Voltage Regulator ◽  
Performance Tests ◽  
Avr System ◽  
Pid Controller Design ◽  
Novel Method ◽  
Fractional Order Pid ◽  
Fractional Order Pid Controller

This paper presents a novel method for optimal tunning of a Fractional Order Proportional-Integral-Derivative (FOPID) controller for an Automatic Voltage Regulator (AVR) system. The presented method is based on the Yellow Saddle Goatfish Algorithm (YSGA), which is improved with Chaotic Logistic Maps. Additionally, a novel objective function for the optimization of the FOPID parameters is proposed. The performance of the obtained FOPID controller is verified by comparison with various FOPID controllers tuned by other metaheuristic algorithms. A comparative analysis is performed in terms of step response, frequency response, root locus, robustness test, and disturbance rejection ability. Results of the simulations undoubtedly show that the FOPID controller tuned with the proposed Chaotic Yellow Saddle Goatfish Algorithm (C-YSGA) outperforms FOPID controllers tuned by other algorithms, in all of the previously mentioned performance tests.

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