Comparison of Control Algorithms by Simulating Power Consumption of Differential Drive Mobile Robot Motion Control in Vineyard Row

Abstract

The paper deals with comparing electricity power consumption of various control algorithms by simulating differential mobile robot motion control in a vineyard row. In field of autonomous mobile robotics, the quality of control is a crucial aspect. Besides the precision of control, the energy consumption for motion is becoming an increasingly demanding characteristic of a controller due to the increasing costs of fossil fuels and electricity. A simulation model of a differential drive mobile robot motion in a vineyard row was created, including robot dynamics for evaluating motion consumption, and there were implemented commonly used PID, Fuzzy, and LQ control algorithms, the task of which was to navigate the robot through the centre of vineyard row section by measuring distances from trellises on both robot sides. The comparison was carried out using Matlab software and the best results in terms of both power consumption and control accuracy were achieved by LQI controller. The designed model for navigating the robot through the vineyard row centre and optimized controllers were implemented in a real robot and tested under real conditions.

Criterios de desempeño para evaluar algoritmos de navegación de robots móviles: una revisión

“…Criterio: índice, métrica, medición, procedimiento Referencia % éxito en alcanzar la meta (Gridnev et al, 2017) (Graba et al, 2020) Integral del valor absoluto del error -integral absolute error (IAE) (Fernandes et al, 2017); (Caruntu et al, 2019); (Suarin et al, 2019); (Rivera et al, 2020); (Farias et al, 2020) Integral del valor absoluto del error ponderado en el tiempo -Integral time-weighted absolute error (ITAE) (Fernandes et al, 2017); (Suarin et al, 2019); (Farias et al, 2020) Integral del valor absoluto de la señal de control -Integral absolute signal control (IASC) (Fernandes et al, 2017) Integral del cuadrado del error -integral square error (ISE) (Perez et al, 2018); (Suarin et al, 2019); (Farias et al, 2020) integral del cuadrado del error por el tiempo -Integral time square error (ITSE) (Farias et al, 2020) Esfuerzo de control (Rivera et al, 2020) Seguridad (Marvel and Bostelman, 2014); (Munoz et al, 2014) Energía (Munoz et al, 2014); (Fernandes et al, 2017); (Stefek et al, 2020); (Graba et al, 2020); (Wei and Isler, 2020); (Hrubý et al, 2021)…”

“…Otros criterios que se utiliza son la integral del valor absoluto del error IAE y el esfuerzo de control acumulativo. El concepto de esfuerzo de control asimismo se emplea en los criterios de suavidad de la curvatura de una trayectoria que igualmente sirve para estimar el consumo energético (Rivera et al, 2020), (Hrubý et al, 2021).…”

Design Method of Intelligent Ropeway Type Line Changing Robot Based on Lifting Force Control and Synovial Film Controller

“…At the same time, there are a large number of old lines. Old lines may affect the safe operation of the power system, personal safety, and property safety [1][2][3]. At present, the demolition of the old lines of the power grid is basically completed by manual work, and there are many problems such as long construction time, high construction cost, and wide influence range [4,5].…”