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

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

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.

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


2020 ◽  
Vol 62 (7) ◽  
pp. 744-748 ◽  
Author(s):  
A. B. S. Yıldız ◽  
N. Pholdee ◽  
S. Bureerat ◽  
A. R. Yıldız ◽  
S. M. Sait

Abstract In this paper, the sine-cosine optimization algorithm (SCO) is used to solve the shape optimization of a vehicle clutch lever. The design problem is posed for the shape optimization of a clutch lever with a mass objective function and a stress constraint. Actual function evaluations are based on finite element analysis, while the response surface method is used to obtain the equations for objective and constraint functions. Recent optimization techniques such as the salp swarm algorithm, grasshopper optimization algorithm, and sine-cosine algorithm are used for shape optimization. The results show the ability of the sine-cosine optimization algorithm to optimize automobile components in the industry.


Author(s):  
Sujatha Nebarthi

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


Author(s):  
Vishal Srivastava ◽  
Smriti Srivastava ◽  
Gopal Chaudhary ◽  
Xiomarah Guzmán-Guzmán ◽  
Vicente García-Díaz

AbstractThis paper exploits various meta-heuristic optimization techniques to learn PID controller parameters for nonlinear systems. The nonlinear systems considered here are well known ball and beam, inverted pendulum, and robotic arm manipulator. The gain parameters of the controllers are optimized by using two categories of meta-heuristic optimization techniques—swarm-based grasshopper optimization algorithm and particle swarm optimization and human-based, i.e., teacher learning-based optimization. Mean square error has been used to measure the performance of various algorithms. Robustness of these algorithms is studied and compared using parameter perturbation and external disturbance. There are substantial improvements in the performance of these plants using the mentioned algorithms as shown in the simulation results. A detailed comparative analysis of these algorithms has also been done.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Thomas George ◽  
V. Ganesan

AbstractThe processes which contain at least one pole at the origin are known as integrating systems. The process output varies continuously with time at certain speed when they are disturbed from the equilibrium operating point by any environment disturbance/change in input conditions and thus they are considered as non-self-regulating. In most occasions this phenomenon is very disadvantageous and dangerous. Therefore it is always a challenging task to efficient control such kind of processes. Depending upon the number of poles present at the origin and also on the location of other poles in transfer function different types of integrating systems exist. Stable first order plus time delay systems with an integrator (FOPTDI), unstable first order plus time delay systems with an integrator (UFOPTDI), pure integrating plus time delay (PIPTD) systems and double integrating plus time delay (DIPTD) systems are the classifications of integrating systems. By using a well-controlled positioning stage the advances in micro and nano metrology are inevitable in order satisfy the need to maintain the product quality of miniaturized components. As proportional-integral-derivative (PID) controllers are very simple to tune, easy to understand and robust in control they are widely implemented in many of the chemical process industries. In industries this PID control is the most common control algorithm used and also this has been universally accepted in industrial control. In a wide range of operating conditions the popularity of PID controllers can be attributed partly to their robust performance and partly to their functional simplicity which allows engineers to operate them in a simple, straight forward manner. One of the accepted control algorithms by the process industries is the PID control. However, in order to accomplish high precision positioning performance and to build a robust controller tuning of the key parameters in a PID controller is most inevitable. Therefore, for PID controllers many tuning methods are proposed. the main factors that lead to lifetime reduction in gain loss of PID parameters are described in This paper and also the main methods used for gain tuning based on optimization approach analysis is reviewed. The advantages and disadvantages of each one are outlined and some future directions for research are analyzed.


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