Rafael Vieira de Sousa

Design of CAN-based distributed control systems with optimized configuration

A current trend in distributed control systems is the application of communication networktechnologies such as CAN - Controller Area Network. A recent utilization approach ofthese technologies is the networked control systems (NCS). The fundamental challenges inthe development of NCS are the analysis of the network delay effects and the prediction of the timing behavior of the distributed control system. The common parameters that impact the performance of NCS include response time, network utilization and network delays induced by the communication of messages between the devices. In addition, the performance of a NCS is highly dependent on these messages sampling times. A significant emphasis has been put on development and application of methodologies to handle the network delay effect in these systems and improve their performances. This paper presents a detailed timing analysis and a mathematical model to calculate these network delays in CAN-based networks. With the results of this model, the application of a methodology is proposed to minimize the effects of these delays and to achieve the optimization (networkoperation and utilization) of a CAN-based network. A case study of a CAN-based distributed control system in a mobile robot is described to demonstrate the application of the optimization methodology and the utilization of the CAN mathematical model systemized.

Development and evaluation of a fuzzy logic classifier for assessing beef cattle thermal stress using weather and physiological variables

Fuzzy inference system can develop a model to predict the rectal temperature of cattle.Infrared thermography using soft-computing technique assesses the heat stress of cattle.The level of heat stress in feedlots can be assessed individually and non-invasively. This research was carried out to develop a fuzzy logic classifier that integrates both weather and animal factors to assess individually the level of thermal stress in feedlot finishing cattle. An experiment was performed with two groups of Nellore feedlot finishing cattle for the acquisition of weather and physiological data including the average of surface temperature in different parts of the animal body using infrared thermography. A statistical analysis of the data was applied to seek the best correlation between the weather and physiological measurements and the infrared thermography (IRT) measurements in different parts of the animal body surface and to orient the construction of membership functions. A knowledge-based system was constructed from rules that associate the memberships of the input variables dry bulb temperature, wet bulb temperature and front surface infrared temperature which were found to be suitable for predicting the rectal temperature. Predicted rectal temperature was rated for the level of thermal stress and compared with the real rectal temperature and a traditional temperature-humidity index. The results indicated little correspondence between the fuzzy classifier and temperature-humidity index (29.3%), but the average rectal temperature value during the day showed great consistency (83.2%) between the fuzzy classifier and animals response. In addition, the IRT measurements allowed an accurate assessment and classification of the individual thermal stress of animals in the same day. The proposed fuzzy classifier resulted in better estimates of the thermal stress level when compared to the traditional temperature-humidity index and fuzzy-based systems previously developed.

Modelagem e simulação de redes de comunicação baseadas no protocolo CAN - Controller Area Network

A major trend in industrial systems is the application of communication networks technologies, such as CAN (Controller Area Network), in distributed control systems. A challenging problem in the development of distributed system based on communication networks is the network delay effects in the performance of the system. This fact has motivated the development of simulation tools and models to calculate these delays, to simulate the timing behavioral and evaluate the performance of these systems. This work presents the development of a mathematical model and a Colored Petri Nets model to the simulation of CAN-based distributed systems. The flexibility and potential obtained with the developed models allow determining and analyzing several performance parameters related to communication network and the distributed control. An example of a CAN-based distributed system applied to perform the control of a mobile robot demonstrates the functionalities of the models and its applicability to the analysis of any CAN application.

Fractional PID controller in an active image stabilization system for mitigating vibration effects in agricultural tractors

Abstract Recent demands in sophisticated agricultural machinery require passive or active image sensors to be mounted on vehicle frames. The impact produced by vertical displacements due to tire-soil interaction and mechanical engine vibration causes oscillations that reduce the data quality of any activity performed by equipment such as a camera, spectroradiometer, or scanner laser. This paper presents the modeling and simulation of an active system for stabilization of oscillations using a fractional order PID (Proportional-Integral-Derivative) controller. A method for tuning the fractional order PID is presented for a closed-loop dynamic system. Experiments based on simulations are carried out to compare the performance of the active stabilization system with fractional and integer order PID controllers. Common excitation functions are used to assess the performance of the active stabilization system, along with some common vibration disturbances acquired by a field experiment with a tractor-implement set. The results show that the active stabilization system presents better performance, mitigating vibration displacements and accelerations through a closed-loop system with a fractional PID controller. Additionally, numerical results confirm the superior capacity of the fractional controller based system for attenuating the vibration disturbance compared to the classical PID system for different machinery operational conditions such as forward speed and load.

A Row Crop Following Behavior based on Primitive Fuzzy Behaviors for Navigation System of Agricultural Robots

Abstract The work presents a methodology for generating and implementing a complex row crop following robotic for a mobile agricultural robot. Fuzzy rules are used to compose and coordinate the simple behaviors using the specific agricultural contexts. Also, is proposed a method for coordinating the simple behaviors based on multiples arbiters that operate in different stages on the robotic architecture to perform the path tracking. A commercial robotic platform is adapted to simulate and support the behavior based on architecture to allow the experiment performed in order to evaluate the implemented behaviors and to evaluate the operational ability of the robotic platform on a simulated agricultural environment. The modularity of the architecture using decentralized arbiters simplifies the implementation of the robotic architecture. The results show the feasibility method to implement the behavior coordination and to compose complex behaviors based on fuzzy and non-fuzzy simple context dependent behaviors.

Predictive model based on artificial neural network for assessing beef cattle thermal stress using weather and physiological variables

Abstract The performance of feedlot cattle is adversely affected by thermal stress but the approach to assess the status of animal stress can be laborious, invasive, and/or stressful. To overcome these constraints, the present study proposes a model based on an artificial neural network (neural model), for individual assessment of the level of thermal stress in feedlot finishing cattle considering both weather and animal factors. An experiment was performed using two different groups of Nellore cattle. Physiological and weather data were collected during both experiments including surface temperatures for four selected spots, using infrared thermography (IRT). The data were analyzed (in terms of Pearson’s correlation) to determine the best correlation between the weather and physiological measurements and the IRT measurements for defining the best body location and physiological variable to support the neural model. The neural model had a feed-forward and multi-layered architecture, was trained by supervised learning, and accepted IRT, dry bulb temperature, and wet bulb temperature as inputs to estimate the rectal temperature (RT). A regression model was built for comparison, and the predicted and measured RTs were classified on levels of thermal stress for comparing with the classification based on the traditional temperature–humidity index (THI). The results suggested that the neural model has a good predictive ability, with an R2 of 0.72, while the regression model yielded R2 of 0.57. The thermal stress predicted by the neural model was strongly correlated with the measured RT (94.35%), and this performance was much better than that of the THI method. In addition, the neural model demonstrated good performance on previously unseen data (ability to generalize), and allowed the individual assessment of the animal thermal stress conditions during the same period of day.

Application of systematic methods in the electromechanical design of an agricultural mobile robot

Abstract A current trend in the agricultural area is the development of mobile robots and autonomous vehicles for precision agriculture. One of the major challenges in the design of these robots is the development of the electromechanical components. This platform has as main characteristics four-wheel propulsion and independent steering, adjustable gauge, ground clearance of 1.80 m, diesel engine, hydraulic system, and a CAN-based networked control system. The aim of this work is to describe the project of an experimental platform for data acquisition in field for the study of the spatial variability and development of agricultural robotics technologies to operate in agricultural environments. This proposal is based on a description of the design process and definition of the design parameters utilized.

A methodology for composing and coordinating primitive fuzzy behaviors to guide mobile agricultural robots

This work presents a method for developing complex navigational behavior by combining some simple fuzzy behaviors and simple non-fuzzy behaviors for a mobile agricultural robot (MAR). Fuzzy rules are used to compose and coordinate the simple behaviors using the specific agricultural contexts. A new strategy to coordinate behaviors based on multiples arbiters that operate in different stages on the robotic architecture to perform guidance and navigation actions. An experimental robotic platform to simulate and support the researches on behavior based on architecture for agricultural robots is proposed. Experiments have been performed in order to evaluate the implemented behaviors and to evaluate the operational ability of the robotic platform on a simulated agricultural environment. The results show the feasibility of the proposed approach. The modularity of the architecture using decentralized arbiters simplifies the implementation of the robotic architecture. The strategy based on multiple arbiters is a feasible method to implement the behavior coordination and to compose complex behaviors.

Object oriented C++ library IsoAgLib study and implementation from the remote CAN-Based Distributed Control System

The multidisciplinary practices of Precision Agriculture (PA) which use embedded electronic and remote sensing in agricultural machinery has demanded researches of sensors and communication networks for data acquisition and control in the farm field. The CAN-Based Distributed Control System (DCS) according to ISO 11783 (or ISOBUS) standard provides the interconnection of electronic devices embedded in agricultural machinery and implements through a control network and serial data communication. The IsoAgLib is an Object Oriented C++ library that has the communication services and needed management systems according with the ISO 11783 standard. This library allows building ISOBUS compatible equipment without the protocols implementation contained in this standard. This work presents the remote access of CAN-Based DCS workbench for the IsoAgLib study and implementation to support the development of the CAN-Based DCS systems, the ISO 11783 standard parts, the PA and the Information and Communication Technology (ICT). The CAN-Based DCS workbench consists in two Personal Computers (PC), one desktop and one notebook. The DCS connection between two PCs is by embedded CAN hardware from Vector CANtech Inc.. The IsoAgLib library is implemented, compiled and executed on the desktop. In the notebook, there is an Electronic Control Units (ECU) called Virtual Terminal (VT) simulator of Vector CANtech Inc., which allows the visualization of the IsoAgLib executable from desktop. To remotely access this workbench, is used the web service LogMeIn Free from LogMeIn Inc. with the web browser Mozilla Firefox from Mozilla Foundation. The evaluation of the connection was done by analyzing the log messages of the remote access and the log messages thorough CAN-bus between IsoAgLib executable and the VT simulator. The remote connection of the CAN-Based DCS workbench provides free access to expensive hardware and software (Vector CANtech Inc. products). Provides distance learning for researchers and professionals of ISO 11783 extensive standard, and for the PA and ICT applications, in CAN-Based DCS automation area.