Optimizing the Load Frequency of a Two-Area Interlinked Power System using Artificial Intelligence Techniques

Power costs are increasing on a daily basis, generating changes in system frequency and causing serious concerns with system stability. It has become a major problem to offer customers with uninterrupted and high-quality power. To mitigate these issues, a linked power system's load distribution and network frequency should be constantly reviewed. Load frequency control adjusts the generator's energy output and tie line power between prescribed limits. As well as regulating generator output power, load frequency control also adjusts tie line power. The disturbance in the frequency due to different load changes is regulated using the proposed scheme. In this article, a two-area load frequency control system is constructed and evaluated using various control approaches, including a proportional integral derivative (PID) controller, a proportional integral (PI) controller, a fuzzy logic-based controller, and an Artificial Neural Network (ANN). The goal is to assess the power system's resilience under different loading conditions with these control schemes. The performance of the controllers is compared based on peak-undershoot, peak-overshoot, and settling time, focusing on tie line power and frequency response. To achieve this, the design is implemented using MATLAB/SIMULINK software

Second Order Integral Fuzzy Logic Control Based Rocket Tracking Control

Fuzzy logic is a logic that has a degree of membership in the vulnerable 0 to 1. Fuzzy logic is used to translate a quantity that is expressed using language. Fuzzy logic is used as a control system because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this paper is to present a fuzzy control system implemented in a rocket tracking control system. The fuzzy control system is used to keep the rocket on track and traveling at a certain speed. The signal from the fuzzy logic control system is used to control the rocket thrust. The fuzzy Logic System was chosen as the controller because it is able to work well on non-linear systems and offers convenience in program design. Fuzzy logic systems have a weakness when working on systems that require very fast control such as rockets. With this problem, fuzzy logic is modified by adding second-order integral control to the modified fuzzy logic. The proposed algorithm shows that the missile can slide according to the ramp path at 12 m altitude of 12.78 at 12 seconds with a steady-state error of 0.78 under FLC control, at 10 m altitude of 10.68 at 10 seconds with a steady-state error of 0.68 with control integral FCL, at a height of 4 m is 4.689 at 4 seconds with a steady-state error of 0.689 with a second-order integral control of FCL. The missile can also slide according to the parabolic path with the second-order integral control of FCL at an altitude of 15.47 in the 4th minute with a steady-state error of 0

Metodologia baseada em algoritmos evolutivos para otimização de controladores de ordem fracionária

Orientador: Gustavo Henrique da Costa OliveiraCoorientador: Gideon Villar LeandroTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Engenharia Elétrica. Defesa : Curitiba, 06/12/2022Inclui referências: p. 159-171Área de concentração: Engenharia ElétricaResumo: Nos últimos anos, o cálculo de ordem fracionária ganhou muita atenção, especialmente no campo da teoria de sistemas dinâmicos e do projeto de sistemas de controle. Algoritmos de controle com ordem fracionária permitem expandir a quantidade de parâmetros de projeto visando melhorar o desempenho do sistema em malha fechada. No entanto, os graus de liberdade são acompanhados com uma complexidade na síntese. Dentro dessa perspectiva, encontra-se o controlador PID de ordem fracionária (FOPID), que possui as ordens integral e diferencial ajustáveis, criando a possibilidade de fornecer melhor desempenho de controle, desde que corretamente sintonizado. Da mesma forma, a sintonia do controlador CRONE e suas gerações também é um desafio, onde a escolha incorreta dos parâmetros pode comprometer o desempenho do controlador. Em vista disso, este trabalho apresenta três objetivos principais, sendo o primeiro uma nova estratégia híbrida de controle, chamada AFOPID. Nesta estratégia, os cinco parâmetros do FOPID são sintonizados online de forma que, na ocorrência de alguma perturbação, a Lógica Fuzzy atualiza os coeficientes kp, ki e kd do FOPID para adaptar a malha fechada à nova condição de operação. Em seguida, os coeficientes fracionários (lambda) e µ, que são as ordens integral e diferencial do controlador, são atualizados usando um algoritmo de Evolução Diferencial (DE). Para fins de validação da metodologia proposta, uma planta de uma usina hidrelétrica baseada em um sistema real é utilizada. Através dos resultados, percebeu-se que o sistema híbrido melhorou a solução geral, fornecendo melhor desempenho em malha fechada do que soluções semelhantes, o que pôde ser comprovado através da análise dos índices de desempenho ISE, ITAE e ITSE. O segundo objetivo desta tese consiste na proposta de um algoritmo de otimização multiobjetivo para os controladores CRONE gerações 1 e 2. Para tanto, utiliza-se o algoritmo NSGA-II Multiobjetivo baseado em dois objetivos principais: (i) Minimizar o sinal de controle; (ii) Reduzir o erro em regime permanente. Os resultados mostraram que além de facilitar o processo de escolha dos parâmetros, não dependendo tanto do conhecimento do projetista, o controlador otimizado conseguiu fornecer bons níveis de desempenho, ou seja, minimizou o sinal de controle e reduziu o erro em regime permanente. Por fim, como terceiro objetivo deste trabalho, tem-se o desenvolvimento de uma plataforma computacional chamada UFPR-FracControl. A plataforma contém os controladores CRONE 1 e 2, convencional e otimizado, FOPID, PID convencional e, visa a utilização desses controladores por usuários não especialistas. Os resultados demonstraram que esta nova plataforma facilitará o uso de sistemas de controle de ordem fracionária pelo fato de ser leve, não depender de instalação, não depender de licenças e pelo fato de ser de fácil implementação. Por fim, conclui-se que os três objetivos aqui propostos obtiveram sucesso em melhorar o desempenho e facilitar o uso dos controladores de ordem fracionária.Abstract: In recent years, fractional order calculus has gained a lot of attention, especially in the field of dynamical system theory and control system design. Control algorithms with fractional order allow expanding the number of design parameters to improve the performance of the closed-loop system. However, the degrees of freedom are accompanied by complexity in the synthesis. Within this perspective, there is the fractional order PID controller (FOPID), which has adjustable integral and differential orders, creating the possibility of providing better control performance, as long as it is correctly tuned. Likewise, the tuning of the CRONE controller and its generations is also a challenge, where the incorrect choice of parameters can compromise the performance of the controller. Given this, this work presents three main objectives, the first being a new hybrid control strategy, called AFOPID. In this strategy, the five parameters of the FOPID are tuned online so that, in the event of any disturbance, the Logic Fuzzy updates the coefficients kp, ki and kd of the FOPID to adapt the closed loop to the new operating condition. Next, the fractional coefficients (lambda) and µ, which are the integral and differential orders of the controller, are updated using a Differential Evolution (DE) algorithm. To validate the proposed methodology, a plant of a hydroelectric plant based on a real system is used. Through the results, it was noticed that the hybrid system improved the overall solution, providing better closed-loop performance than similar solutions, which could be proven through the analysis of the ISE, ITAE, and ITSE performance indexes. The second objective of this thesis consists in proposing a multiobjective optimization algorithm for CRONE controllers generations 1 and 2. For this purpose, the NSGA-II Multiobjective algorithm is used based on two main objectives: (i) Minimize the control signal; (ii) Reduce the steady-state error. The results showed that in addition to facilitating the process of choosing the parameters, not depending so much on the designer's knowledge, the optimized controller was able to provide good levels of performance, that is, it minimized the control signal and reduced the steady-state error. Finally, as the third objective of this work, there is the development of a computational platform called UFPR-FracControl. The platform contains CRONE 1 and 2 controllers, conventional and optimized, FOPID, and conventional PID, and aims to use these controllers by non-specialist users. The results showed that this new platform will facilitate the use of fractional order control systems because it is lightweight, does not depend on installation, does not depend on licenses, and because it is easy to implement. Finally, it is concluded that the three objectives proposed here were successful in improving performance and facilitating the use of fractional order controllers