Reliable Control Applications with Wireless Communication Technologies: Application to Robotic Systems

The nature of wireless propagation may reduce the QoS of the applications, such that some packages can be delayed or lost. For this reason, the design of wireless control applications must be faced in a holistic way to avoid degrading the performance of the control algorithms. This paper is aimed at improving the reliability of wireless control applications in the event of communication degradation or temporary loss at the wireless links. Two controller levels are used: sophisticated algorithms providing better performance are executed in a central node, whereas local independent controllers, implemented as back-up controllers, are executed next to the process in case of QoS degradation. This work presents a reliable strategy for switching between central and local controllers avoiding that plants may become uncontrolled. For validation purposes, the presented approach was used to control a planar robot. A Fuzzy Logic control algorithm was implemented as a main controller at a high performance computing platform. A back-up controller was implemented on an edge device. This approach avoids the robot becoming uncontrolled in case of communication failure. Although a planar robot was chosen in this work, the presented approach may be extended to other processes. XBee 900 MHz communication technology was selected for control tasks, leaving the 2.4 GHz band for integration with cloud services. Several experiments are presented to analyze the behavior of the control application under different circumstances. The results proved that our approach allows the use of wireless communications, even in critical control applications.This research was funded by the Basque Government through the project EKOHEGAZ (ELKARTEK KK-2021/00092), by Diputación Foral de Álava (DFA) through the project CONAVANTER, and by UPV/EHU through the project GIU20/063

Algoritmos de control óptimo basados en WNCS aplicados a un levitador neumático

En el presente trabajo se muestra el procedimiento llevado a cabo para realizar la implementación de los controladores LQG, LQI y PID a través de WNCS, aplicados a un levitador neumático, y la comparación del tiempo de estabilización entre los mismos, cuya planta consta de una base de madera con un orificio en el medio, y en esta se ubica por la parte inferior un ventilador, el cual se encarga de enviar aire hacia un embudo colocado en la parte superior, que concentra el aire y lo expulsa a través de una rejilla hacia un tubo plástico para elevar una pieza de cartón prensando ubicada en su interior hasta la altura indicada por el usuario en una interfaz desarrollada por medio de una App de la plataforma de Blynk, que cuenta con: una entrada de texto numérico para determinar el setpoint deseado; un medidor de porcentaje del valor de PWM que controla el ventilador; valor que es entregado por el tipo de controlador seleccionado; y un histograma que refleja el setpoint ingresado y la variación de la altura de la pieza de cartón a lo largo del tiempo. El sistema se implementa sobre una Raspberry Pi 4, en donde se realiza todo el procesamiento de: los algoritmos de control, el flujo de datos establecidos con una tarjeta de desarrollo NODE MCU, con la que se comunica la planta, y con la aplicación de Blynk.This work shows the procedure carried out to implement the LQG, LQI and PID controllers through WNCS applied to a Pneumatic Levitator, and the comparison of the stabilization time between them, whose plant consists of a base made of wood with a hole in the middle, and in this a fan is located at the bottom part, which is responsible for sending air to a funnel placed in the upper part, which concentrates the air and expels it through a grill towards a plastic tube to raise a pressed paperboard piece located inside it to the height indicated by the user in an interface developed through an App of the Blynk platform, which has: a numerical text input to determine the desired setpoint ; a percentage meter of the PWM value that controls the fan; value that is delivered by the selected controller type; and a histogram that reflects the entered setpoint and the variation in the height of the paperboard piece over time. The system is implemented on a Raspberry Pi 4, where to realize all the processing of: the control algorithms; the data flow established with a NODE MCU development card, with which the plant communicates, and with the Blynk application