Genetic Algorithms for Satellite Launcher Attitude Controller Design

For proper attitude control of space-crafts conventional optimal Linear Quadratic (LQ) controllers are designed via trial-and-error selection of the weighting matrices. This time consuming method is inefficient and usually results in a high order complex controller. Therefore, this work proposes a genetic algorithm (GA) for the search problem of the attitude controller gains of a satellite launcher. The GA's fitness function considers some control features as eigenstructure, control goals and constraints. According to simulation results, the search problem of controller parameters with evolutionary algorithms was faster than usual approaches and the designed controller reached all the specifications with satisfactory time responses. These results could improve engineering tasks by speeding up the design process and reducing costs

Multiagent LQR-based Control Design and Gain tuning for Quadcopters Fleet

An LQR-based Control design and gain tuning strategies proposals for a multi-agent system are presented in this article, the agents are connected in an undirected graph. Controller gains tuning are adjusted by selecting the Q and R weighting matrices of the Linear Quadratic Regulator. Agreement (consensus) is one of the fundamental problems in multi-agent control, where a set of agents must agree on a joint state value. In the proposed design, first considering that the behavior of the agreement protocol is undirected and static, the main objective is to highlight the complexity of the relationship between the convergence properties of this protocol and the structure of adjacent interconnections. The effects on the formation due to static geometry are analyzed from the resulting data according to the proximity between the agents, where behavior and stability are analyzed based on the desired formation geometry through the construction of the Laplacian matrix