Signature PSO: A novel inertia weight adjustment using fuzzy signature for LQR tuning

Particle swarm optimization (PSO) is an algorithm that simple and reliable to complete optimization. The balance between exploration exploitation of PSO searching characteristics maintained by inertia weight. Since this parameter has been introduced, there have several different strategies determine the weight during a train run. This paper describes method adjusting weights using fuzzy signatures called signature PSO. Some parameters were used as variable represent particle situation in implementation solve tuning problem linear quadratic regulator (LQR) control also presented paper. Another adjustment strategy comparison performance evaluation integral time absolute error (ITAE). Experimental results show was able give good approximation optimum LQR case.