Structure Optimization Using Adaptive Particle Swarm Optimization

Panigrahi, S.K.; Sahu, Amaresh; Pattnaik, Sabyasachi

doi:10.1016/j.procs.2015.04.218

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…The technique is based on the concept of interaction and behavior among birds or fishes where birds and fishes gather, organize, compete and co-ordinate among themselves to find food [1,4]. A similar concept is seen in Particle Swarm Optimization where there is a population known as swarm which consists of a number of random solutions known as particles [15]. These particles are free to move around in the search-space based on certain formulae in a multi-dimensional space based on their previous movements and also considering the movements of their neighbors [29,27].…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Bio Inspired Modified Internal Model Control Approach for Improved Disturbance Rejection of Piezo Micro Manipulator

Shome¹,

Jana²,

Mukherjee³

et al. 2018

STUD INFORM CONTROL

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Classical Internal Model Control based approach for controller design has been used in different industrial control applications as it allows good set point tracking performance, especially for processes neglecting time delay. However, in many process control applications including nonlinear piezo electric actuation (PZA), disturbance rejection plays an important role compared to set point tracking. The present research firstly proposes an optimal filter design in series with a Modified Internal Model Control (M-IMC) based Proportional-Integral-Derivative (PID) controller for better set point tracking, improved disturbance rejection with reduced controller hardware resource requirement compared to classical IMC. Two efficient swarm intelligence based evolutionary soft computational techniques viz. Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization (BFO) are then exploited towards optimizing a control evaluation index based fitness function to design the M-IMC control parameters, including filter time constant. The distillation of bio inspired principles in control is seen to exhibit exciting results when the optimized parameters are utilized in the piezo plant modeled using a Dahl based second order system. The performance of the controller has been evaluated by subjecting the plant to several perturbations as well as to external disturbances. The results illustrate the efficiency of the PSO based M-IMC over other controllers.

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Section: Particle Swarm Optimizationmentioning

confidence: 99%

Bio Inspired Modified Internal Model Control Approach for Improved Disturbance Rejection of Piezo Micro Manipulator

Shome¹,

Jana²,

Mukherjee³

et al. 2018

STUD INFORM CONTROL

View full text Add to dashboard Cite

show abstract

“…Herein, natural environmental processes and behaviours are the main inspiration [2]. Commonly used metaheuristics are: the Genetic Algorithm [3], the Gravitational Search Algorithm [4], Cuckoo Search [5], Earthworm Optimization Algorithm [6], Harmony Search [7], the Firefly Algorithm [8], Particle Swarm Optimization [9], [10], Ant Colony Optimization [11], the Bat Algorithm [12], the Differential Evolution [13] and the Autonomy-oriented computing methodology [14]. Newer algorithms, have been recently introduced for this tasking.…”

Section: Introductionmentioning

confidence: 99%

On the Use of Nature Inspired Metaheuristic in Computer Game

Kowalski¹,

Łukasik²,

Charytanowicz³

et al. 2017

Annals of Computer Science and Information Systems

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Abstract-This paper describes the use of a new swarm-based metaheuristic, namely Krill Herd Algorithm (KHA), in computer gaming. In this work, KHA is employed to find a bots movement strategy in a computer racing game. The complete algorithm is implemented using a Unity Engine in C# language. Herein, the triggering of the metaheuristic optimization task was conducted by the way of a KHA internal parameter investigation. In this approach, the goal of the race (the KHA evaluation function) for both the human and computer player is to finish a lap in the shortest time possible.

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Empirical Study on Clustering Based on Modified Teaching Learning Based Optimization

Panigrahi¹,

Pattnaik

2016

Procedia Computer Science

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Structure Optimization Using Adaptive Particle Swarm Optimization

Cited by 4 publications

References 21 publications

Bio Inspired Modified Internal Model Control Approach for Improved Disturbance Rejection of Piezo Micro Manipulator

Bio Inspired Modified Internal Model Control Approach for Improved Disturbance Rejection of Piezo Micro Manipulator

On the Use of Nature Inspired Metaheuristic in Computer Game

Empirical Study on Clustering Based on Modified Teaching Learning Based Optimization

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