Published Paper Details:

In the optimization of the firefly algorithm, the FA algorithm is a meta-heuristics algorithm employed for the tuning of PID parameters kp ki kd using the algorithm. The multi-objective optimization algorithm is used to tune the PID controller parameters by using nature-inspired algorithms and Proportional Integral Derivative controller provides effective results and most of the industrial applications and industrial processes are exact to parameters variations and which provides and the possibility to change the state of unstable and PID controller parameters are tuned for improves the performance and quick response and research present a multi-objective optimization method involving Genetic Algorithm, Particle Swarm Optimization, and Bacterial foraging optimization and performances have been compared with the meta-heuristics Firefly algorithm (FA). The main goal of this study is to develop a multi-objective optimization algorithm real coded PSO PID control self-tuning and optimum for fitness function and then based on the case study. The results show the use of multi-objective optimization comparisons with FA based PID controller-tuning improves the better performance in terms of time-domain specifications and performance index and then based on case study transfer functions taken for simulation using MATLAB and this project shows the comparative approach, proved that better response to tune the PID controller used in the paper machine. From simulations outputs shown that faster and better response results and improves parameters and time domain specifications.