Otimização por enxame de partículas aplicado em controladores PI

• Main Author: Roncaglio, Mateus Maruzka
• Publication Date: 2020
• Format: Bachelor thesis
• Language: por
• Source: Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
• Download full: http://repositorio.utfpr.edu.br/jspui/handle/1/35279
• topic: Python (Linguagem de programação de computador); Sistemas lineares; Controle automático; Python (Computer program language); Linear systems; Automatic control; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA

This final work presents a study and implementation of a stochastic optimization population based algorithm, known as Particle Swarm Optimization (PSO). The optimization's target is a PID control system, simulated in Python language. This choice was made because of the popularity of PID control in the industry. Therefore, the algorithm must find the proportional and integrative gains of a discrete-time PI controller. The solutions were evaluated using the quality indicators Integral Squared Error (ISE), Integral of absolute error (IAE), Integral of time-weighted error (1TAE) and Total Variation Control (TVC) using as case study a fourth order linear time-invariant process. The results show a improvement in the transient response compared to the classical methods.