Multi-criteria Genetic Algorithm Optimization Approach for Balancing Bicopter Control

Abstract

Efforts to find the best controller for stabilizing a flying vehicle have been widely developed in recent years. This work aims to join the development track by exploring the use of genetic algorithm (GA) to find the most optimum controller parameter considering settling time and overshoot criteria. Roll attitude control of a balancing bicopter was chosen as the applied plant to confirm the designed method. The controller structure applied in this research is an ideal proportional-integral (PI) controller. Two equations considering the highlighted criteria for the objective function of the GA were developed with one of them involving integral absolute error (IAE) (MCIAE-GA), and the other one does not (MC-GA). Two GAs with both equations were compared to ziegler-nichols and the one with a standalone IAE (IAE-GA). The test results confirm that the proposed MC-GA and MCIAE-GA outperform the comparative controllers at their best performance by keeping the settling time as small as possible without overshooting. Despite the latter showing a slightly faster settling time, the former has better repeatability given a smaller standard deviation for Kp and Ki parameters with a mere 0.0820 and 0.0980, respectively.

Genetic algorithm-enhanced linear quadratic control for balancing bicopter system with non-zero set point

“…Subsequently, equation ( 6) defines the performance index as a K matrix. The P component in equation ( 6) is a positive semidefinite solution to the Algebraic Riccati Equation (ARE) which needs to persuade as written in equation (7).…”

“…This can be explained by a reduction in the number of rotors can lead to lower unit power demand, which improves flight time and saves energy [6]. However, designing a controller for a bicopter can be challenging as it needs to stabilize the bicopter, reduce settling time, and overcome oscillation simultaneously [7]. Furthermore, it is still uncommon to find control methods developed in bicopter technology, particularly those that harness the assistance of artificial intelligence (AI).…”