Enhancing the Performance of the Particle Filtering Optimization Algorithm for the Tuning of PID Controllers

2017 ◽  
Author(s):  
Douglas A. Plaza-Guingla ◽  
Roger M. Idrovo ◽  
Angel J. Valencia ◽  
Carlos Salazar Lopez
Keyword(s):  
Optimization Algorithm ◽  
Particle Filtering ◽  
Pid Controllers

Jaya Optimization Algorithm Implemented on A New Novel Design of 6-DOF AUV Body: A Case Study

2021 ◽  
Author(s):  
Noorulden Basil ◽  
Hamzah M. Marhoon ◽  
Ahmed R. Ibrahim
Keyword(s):  
Optimization Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Optimization Technique ◽  
Pid Controllers ◽  
The Novel ◽  
Proportional Integral Derivative ◽  
New Novel ◽  
Novel Design ◽  
Optimum Output

Abstract The Novel Jaya Optimization Algorithm (JOA) was utilized in this research to evaluate the efficiency of a new novel design of Autonomous Underwater Vehicle (AUV). The Three Proportional Integral Derivative (PID) controllers were used to obtain the optimum output for the AUV Trajectory, which can be considered as a main side of the research for solving the AUV Performance. The optimization technique has been developed to solving the motion model of the AUV in order to reduce the rotations of trajectory for the AUV 6-DOF Body in the axis’s in x, y and z for the overall positions, velocity... etc., and to execute the optimum output for the dynamic kinematics model based on the Novel Euler-6 DOF AUV Body Equation implemented on MATLAB R2021a Version.

scholarly journals A Fractional PID Controller Based on Particle Swarm Optimization Algorithm

2020 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Yinglei Song
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Pid Controller ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Parameter Tuning ◽  
Parameter Design ◽  
Pid Controllers ◽  
Swarm Optimization ◽  
Control Accuracy

Fractional PID controller is a convenient fractional structure that has been used to solve many problems in automatic control. The fractional scale proportional-integral-differential controller is a generalization of the integer order PID controller in the complex domain. By introducing two adjustable parameters  and , the controller parameter tuning range becomes larger, but the parameter design becomes more complex. This paper presents a new method for the design of fractional PID controllers. Specifically, the parameters of a fractional PID controller are optimized by a particle swarm optimization algorithm. Our simulation results on cold rolling APC system show that the designed controller can achieve control accuracy higher than that of a traditional PID controller.

Grasshopper Optimization Algorithm-Based Fuzzy-2DOF-PID Controller for LFC of Interconnected System With Nonlinearities

2021 ◽  
Vol 12 (3) ◽  
pp. 11-29
Author(s):  
Debasis Tripathy ◽  
Nalin Behari Dev Choudhury ◽  
Binod Kumar Sahu
Keyword(s):  
Optimization Algorithm ◽  
Pid Controller ◽  
Firefly Algorithm ◽  
Pattern Search ◽  
Optimization Techniques ◽  
Degree Of Freedom ◽  
Pid Controllers ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Two Degree Of Freedom

The load frequency control (LFC) is an automation scheme employed for an interconnected power system to overcome the frequency deviation issue because of load variation in the most economical way. This work puts an earliest effort to study the LFC issue of a three-area power systems including nonlinearities using fuzzy-two degree of freedom-PID (F-2DOF-PID) controller optimized with grasshopper optimization algorithm (GOA). Initially, GOA optimized PID controllers are considered for a two area non-reheat thermal system including generation rate constraint to validate the superiority over PID controllers tuned with some recently reported optimization techniques, such as hybrid firefly algorithm-pattern search, firefly algorithm, bacteria foraging optimization algorithm, genetic algorithm, and conventional Ziegler Nichols technique. Then the work is reconsidered for the same system to verify the supremacy of F-2DOF-PID controller over other controllers such as fuzzy-PID, two degree of freedom-PID, and PID with GOA framework. Furthermore, the study is extended to a three-area system considering the effect of nonlinearities to verify effectiveness and robustness of proposed controller.

scholarly journals Comparison between butterfly optimization algorithm and particle swarm optimization for tuning cascade PID control system of PMDC motor

2021 ◽  
Vol 12 (2) ◽  
pp. 736
Author(s):  
Kareem G. Abdulhussein ◽  
Naseer M. Yasin ◽  
Ihsan J. Hasan
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm ◽  
Optimization Methods ◽  
Pso Algorithm ◽  
Modern Method ◽  
Pid Controllers ◽  
Swarm Optimization ◽  
Permanent Magnet Dc Motor ◽  
Tracking Trajectory

In this paper, two optimization methods are used to adjust the gain values for the cascade PID controller. These algorithms are the butterfly optimization algorithm (BOA), which is a modern method based on tracking the movement of butterflies to the scent of a fragrance to reach the best position and the second method is particle swarm optimization (PSO). The PID controllers in this system are used to control the position, velocity, and current of a permanent magnet DC motor (PMDC) with an accurate tracking trajectory to reach the desired position. The simulation results using the Matlab environment showed that the butterfly optimization algorithm is better than the particle swarming optimization (PSO) in terms of performance and overshoot or any deviation in tracking the path to reach the desired position. While an overshoot of 2.557% was observed when using the PSO algorithm, and a position deviation of 7.82 degrees was observed from the reference position.

scholarly journals Operation of Whale Optimization Algorithm in PID Controllers for AVR System

2020 ◽  
Vol 06 (09) ◽  
pp. 1-5
Author(s):  
Sujatha Nebarthi
Keyword(s):  
Transient Response ◽  
Optimization Algorithm ◽  
Pid Controller ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Whale Optimization Algorithm ◽  
Pid Controllers ◽  
Avr System ◽  
Whale Optimization ◽  
Strong Control

In the present paper presents the Whale Optimization Algorithm technique (WOA) it is a partial search algorithm. To advance the improved the performance of the PID controller uses whale optimization algorithm as the optimization technique. The proposed algorithm is used to tuning the controllers very fast and tuning is very high quality in PID Controllers is most effectively. It growths the system by its main transient response and by comparing the all terms of rise time (tr), settling time (ts) and peak overshoot (% Mp). More over the three gains are (proportional (kP), integral (ki) and derivative (Kd)) of the PID controller have been enhanced by the WOA technique to control the Automatic Voltage Regulator system. In this the transient response of the terminal voltage may be observed from the well-conditioned analysis they can be suggest WOA established PID Controller and which reveal a very most upgrade strong control structure for the managing the AVR system in the Electrical Power System. The simulation result of the propounded controller has shown superior result to the other optimization techniques on PID controller along with the transient response parameters and improve and supervise the performance of the System

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