scholarly journals On Comparing the Performance of Swarm-Based Algorithms with Human-Based Algorithm for Nonlinear Systems

2021 ◽  
Author(s):  
Vishal Srivastava ◽  
Smriti Srivastava ◽  
Gopal Chaudhary ◽  
Xiomarah Guzmán-Guzmán ◽  
Vicente García-Díaz
Keyword(s):  
Nonlinear Systems ◽  
Teacher Learning ◽  
Pid Controller ◽  
Inverted Pendulum ◽  
External Disturbance ◽  
Optimization Techniques ◽  
Heuristic Optimization ◽  
Parameter Perturbation ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization

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.

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 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

Sine-cosine optimization algorithm for the conceptual design of automobile components

2020 ◽  
Vol 62 (7) ◽  
pp. 744-748 ◽  
Author(s):  
A. B. S. Yıldız ◽  
N. Pholdee ◽  
S. Bureerat ◽  
A. R. Yıldız ◽  
S. M. Sait
Keyword(s):  
Shape Optimization ◽  
Optimization Algorithm ◽  
Optimization Techniques ◽  
Stress Constraint ◽  
Element Analysis ◽  
Surface Method ◽  
Grasshopper Optimization Algorithm ◽  
Sine Cosine Algorithm ◽  
Automobile Components ◽  
Grasshopper Optimization

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.

scholarly journals Optimization of nonlinear controller with an enhanced biogeography approach

2014 ◽  
Vol 4 (2) ◽  
pp. 77-87
Author(s):  
Mohammed Salem ◽  
Mohamed Fayçal Khelfi
Keyword(s):  
Genetic Algorithm ◽  
Nonlinear Systems ◽  
Pid Controller ◽  
Inverted Pendulum ◽  
Optimal Solution ◽  
Optimization Process ◽  
Nonlinear Controller ◽  
Local Optima ◽  
Nonlinear Controllers ◽  
Mass Spring

This paper is dedicated to the optimization of nonlinear controllers basing of an enhanced Biogeography Based Optimization (BBO) approach. Indeed, The BBO is combined to a predator and prey model where several predators are used with introduction of a modified migration operator to increase the diversification along the optimization process so as to avoid local optima and reach the optimal solution quickly. The proposed approach is used in tuning the gains of PID controller for nonlinear systems. Simulations are carried out over a Mass spring damper and an inverted pendulum and has given remarkable results when compared to genetic algorithm and BBO. 

scholarly journals An Efficient Energy Management in Office Using Bio-Inspired Energy Optimization Algorithms

Processes ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 142 ◽  
Author(s):  
Ibrar Ullah ◽  
Zar Khitab ◽  
Muhammad Khan ◽  
Sajjad Hussain
Keyword(s):  
Energy Consumption ◽  
Power Flow ◽  
Average Power ◽  
Energy Optimization ◽  
Optimization Techniques ◽  
Electricity Bill ◽  
Maximum Benefit ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Smart Technologies

Energy is one of the valuable resources in this biosphere. However, with the rapid increase of the population and increasing dependency on the daily use of energy due to smart technologies and the Internet of Things (IoT), the existing resources are becoming scarce. Therefore, to have an optimum usage of the existing energy resources on the consumer side, new techniques and algorithms are being discovered and used in the energy optimization process in the smart grid (SG). In SG, because of the possibility of bi-directional power flow and communication between the utility and consumers, an active and optimized energy scheduling technique is essential, which minimizes the end-user electricity bill, reduces the peak-to-average power ratio (PAR) and reduces the frequency of interruptions. Because of the varying nature of the power consumption patterns of consumers, optimized scheduling of energy consumption is a challenging task. For the maximum benefit of both the utility and consumers, to decide whether to store, buy or sale extra energy, such active environmental features must also be taken into consideration. This paper presents two bio-inspired energy optimization techniques; the grasshopper optimization algorithm (GOA) and bacterial foraging algorithm (BFA), for power scheduling in a single office. It is clear from the simulation results that the consumer electricity bill can be reduced by more than 34.69% and 37.47%, while PAR has a reduction of 56.20% and 20.87% with GOA and BFA scheduling, respectively, as compared to unscheduled energy consumption with the day-ahead pricing (DAP) scheme.

Optimal tuning of PID controller in time delay system: a review on various optimization techniques

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Thomas George ◽  
V. Ganesan
Keyword(s):  
Time Delay ◽  
Pid Control ◽  
Pid Controller ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Delay Systems ◽  
Pid Controllers ◽  
Time Delay Systems ◽  
Process Industries ◽  
First Order

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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