FOPID Controller Design for Electric Furnace Temperature System Using TLBO Algorithm

In this article, a fractional order proportional–integral–derivative (FOPID) controller using Teaching Learning Based Optimization (TLBO) for furnace temperature system is designed. Having two extra control parameter comparing to PID controller, FOPID controllers benefit from more dynamic flexibility which make achieving the suitable results simpler. Due to increase in the number of parameters, in FOPID design, conventional approach cannot be utilized and optimizing methods are the proper alternates for this design among which TLBO is selected for this paper. A comparison among this optimization method and the others, like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), is performed. Simulation results show that maximum overshoot and settling time in FOPID design are improved using TLBO method for a typical system

Keywords:

FOPID Controller , TLBO Optimization , Electric Furnace Temperature System