A parameter tuning approach of the Sliding Mode Control for a Quadcopter based on Genetic Algorithms

In this work is presented a parameter tuning approach of a Sliding Mode Control (SMC) using Genetic Algorithms (GA). The GA are used for the tuning of the parameters of the Orientation Control and Height of quadcopter, considering all the cases in a sliding surface PD. The objective of GA is to provide a set of parameters that minimizes the integral square error (ISE) of the SMC. The SMC is improved when it is used the GA.

I. Introduction

One of the principles that determines the performance of a system is the tuning of its control parameters. In general, the performance of the laws of control depends on the values of these parameters. The design and calibration of the controllers is carried out based on existing tuning methods, however, in the case of SMC controllers, due to their use in non-linear plants, the calibration of their parameters becomes a work of test and error. On the other hand, it is important to point out that new techniques have been developed, so that the parameters of the controllers can be tuned automatically. Among these new techniques, we can highlight the GA as a tool for the tuning of controllers [1] , [2] .