Actuators and sensors for application in agricultural robots: A review

In recent years, with the rapid development of science and technology, agricultural robots have gradually begun to replace humans, to complete various agricultural operations, changing traditional agricultural production methods. Not only is the labor input reduced, but also the production efficiency can be improved, which invariably contributes to the development of smart agriculture. This paper reviews the core technologies used for agricultural robots in non-structural environments. In addition, we review the technological progress of drive systems, control strategies, end-effectors, robotic arms, environmental perception, and other related systems. This research shows that in a non-structured agricultural environment, using cameras and light detection and ranging (LiDAR), as well as ultrasonic and satellite navigation equipment, and by integrating sensing, transmission, control, and operation, different types of actuators can be innovatively designed and developed to drive the advance of agricultural robots, to meet the delicate and complex requirements of agricultural products as operational objects, such that better productivity and standardization of agriculture can be achieved. In summary, agricultural production is developing toward a data-driven, standardized, and unmanned approach, with smart agriculture supported by actuator-driven-based agricultural robots. This paper concludes with a summary of the main existing technologies and challenges in the development of actuators for applications in agricultural robots, and the outlook regarding the primary development directions of agricultural robots in the near future

Rakennusten energiasuorituskyvyn parantaminen hyödyntämällä saatavilla olevaa dataa

The objective of this research is to find out how the energy performance of buildings can be improved effectively by exploiting available data in the operations and maintenance phase. In this research building automation systems, open data and Internet of Things are studied as value generating technological solutions. The research process is based on reviewing research literature, conducting interviews and analyzing measurement data recorded by the building automation system of a case office building. The study identified 11 initiatives to close existing energy performance gaps. These initiatives belonged to categories of developing building services equipment control, increasing the extent of available data, observing the state of user experience and facilitating maintenance processes. Then the three most effective were chosen for a feasibility study. This effectiveness of an initiative was judged by evaluating it in the dimensions of expected benefits and challenge to implement in an indicative manner by 13 interviewees in four stakeholder groups. This simple evaluation method turned out to serve its purpose well: Vague evaluation dimensions covered both quantitative and qualitative aspects, while stakeholder groups had different perspectives on the initiatives. Thus the method is recommended for similar problems, as long as only indicative results are pursued. Out of the 11 initiatives, the most effective ones were considered to be those that are simple and do not require any installation work, or at the most the installation of transmitters or sensors: 1) adaptive heating control, 2) user satisfaction measurement systems, 3) energy performance monitoring systems and 4) selected equipment group control interfaces. Feasibility studies suggested that adaptive heating control has the potential to increase energy performance with negligible installation work, user satisfaction measurement system would be sensible to pilot as a service, energy efficiency monitoring in small-scale would be convenient to purchase as a service and selected group control interfaces enable large savings with small trouble. The least effective initiatives were considered to be the ones that are complex, risk user satisfaction or require the integration of numerous systems.Tämän tutkimuksen tavoitteena on selvittää miten rakennusten energiasuorituskykyä voidaan parantaa tehokkaasti hyödyntämällä saatavilla olevaa dataa käyttö- ja ylläpitovaiheessa. Tutkimuksessa arvoa tuottavina teknologisina osaratkaisuina tutkitaan rakennusautomaatiojärjestelmiä, avointa dataa ja Esineiden Internetiä. Tutkimusmenetelminä käytetään kirjallisuustutkimusta, haastatteluja ja toimistorakennuksen rakennusautomaatiojärjestelmän tuottaman mittaustiedon analysointia. Tutkimus tuotti 11 energiasuorituskyvyn ongelmakohtien korjaamiseen tähtäävää aloitetta. Näiden aloitteiden päämäärinä oli taloteknisten laitteiden ohjauksen kehittäminen, käytettävissä olevan datan lisääminen, käyttäjätyytyväisyyden tarkkailu tai ylläpidon prosessien helpottaminen. Aloitteista kolmelle tehokkaimmiksi arvioiduille tehtiin tarkempi toteutettavuustutkimus. Tehokkuusarviointi perustui neljään sidosryhmään jaetun 13 haastateltavan suuntaa-antavaan näkemykseen aloitteiden toimeenpanon hyödyistä ja haasteista. Tämä yksinkertainen arviointitapa osoittautui toimivaksi: Moniselitteiset arviointiulottuvuudet kattoivat sekä määrälliset että laadulliset näkökulmat, kun taas eri sidosryhmät painottivat aloitteiden eri ominaisuuksia. Näin ollen kyseinen arviointimenetelmä soveltuu samankaltaisiin ongelmiin, kunhan tulosten suuntaa-antava taso on riittävä tutkimuksen tavoitteisiin nähden. Näistä 11 aloitteesta tehokkaimmiksi koettiin pääosin sellaiset, jotka ovat yksinkertaisia eivätkä vaadi laajaa asennustyötä: 1) adaptiivinen lämmityksen säätö, 2) käyttäjätyytyväisyyden mittausjärjestelmä, 3) energiatehokkuuden seurantajärjestelmä ja 4) laitteiden ryhmähallintaan perustuvat käyttöliittymät. Toteutettavuustutkimusten perusteella adaptiivinen lämmityksensäätö voisi parantaa energiasuorituskykyä pienellä asennustyöllä, käyttäjätyytyväisyyden mittausjärjestelmää olisi järkevää aluksi kokeilla palveluna, energiatehokkuuden seuranta pienessä mittakaavassa olisi kätevää ostaa palveluna ja ryhmäohjaukseen perustuvat käyttöliittymät voisivat säästää huomattavasti energiaa pienellä vaivalla. Tehottomimmiksi arvioidut aloitteet olivat monimutkaisia, vaaransivat käyttäjätyytyväisyyden tai vaativat useiden järjestelmien yhteensovittamista

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154106/1/kampfner1998.pd

Advances and Trends in Mathematical Modelling, Control and Identification of Vibrating Systems

This book introduces novel results on mathematical modelling, parameter identification, and automatic control for a wide range of applications of mechanical, electric, and mechatronic systems, where undesirable oscillations or vibrations are manifested. The six chapters of the book written by experts from international scientific community cover a wide range of interesting research topics related to: algebraic identification of rotordynamic parameters in rotor-bearing system using finite element models; model predictive control for active automotive suspension systems by means of hydraulic actuators; model-free data-driven-based control for a Voltage Source Converter-based Static Synchronous Compensator to improve the dynamic power grid performance under transient scenarios; an exact elasto-dynamics theory for bending vibrations for a class of flexible structures; motion profile tracking control and vibrating disturbance suppression for quadrotor aerial vehicles using artificial neural networks and particle swarm optimization; and multiple adaptive controllers based on B-Spline artificial neural networks for regulation and attenuation of low frequency oscillations for large-scale power systems. The book is addressed for both academic and industrial researchers and practitioners, as well as for postgraduate and undergraduate engineering students and other experts in a wide variety of disciplines seeking to know more about the advances and trends in mathematical modelling, control and identification of engineering systems in which undesirable oscillations or vibrations could be presented during their operation

A quick review of the applications of artificial neural networks (ANN) in the modelling of thermal systems

Thermal systems play a main role in many industrial sectors. This study is an elucidation of the utilization of artificial neural networks (ANNs) in the modelling of thermal systems. The focus is on various heat transfer applications like steady and dynamic thermal problems, heat exchangers, gas-solid fluidized beds, and others. Solving problems related to thermal systems using a traditional or classical approach often results to near feasible solutions. As a result of the stochastic nature of datasets, using the classical models to advance exclusive designs from the experimental dataset is often a function of trial and error. Conventional correlations or fundamental equations will not proffer satisfactory solutions as they are in most cases suitable and applicable to the problems from where they are generated. A preferable option is the application of computational intelligence techniques focused on the artificial neural network model with different structures and configurations for effective analysis of the experimental dataset. The main aim of current study is to review research work related to artificial neural network techniques and the contemporary improvements in the use of these modelling techniques, its up-and-coming application in addressing variability of heat transfer problems. Published research works presented in this paper, show that problems solved using the ANN model with regression analysis produced good solutions. Limitations of the classical and computational intelligence models have been exposed and recommendations have been made which focused on creative algorithms and hybrid models for future modelling of thermal systems.http://www.etasr.com/index.php/ETASR/indexdm2022Mechanical and Aeronautical Engineerin

Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

A Framework for Life Cycle Cost Estimation of a Product Family at the Early Stage of Product Development

A cost estimation method is required to estimate the life cycle cost of a product family at the early stage of product development in order to evaluate the product family design. There are difficulties with existing cost estimation techniques in estimating the life cycle cost for a product family at the early stage of product development. This paper proposes a framework that combines a knowledge based system and an activity based costing techniques in estimating the life cycle cost of a product family at the early stage of product development. The inputs of the framework are the product family structure and its sub function. The output of the framework is the life cycle cost of a product family that consists of all costs at each product family level and the costs of each product life cycle stage. The proposed framework provides a life cycle cost estimation tool for a product family at the early stage of product development using high level information as its input. The framework makes it possible to estimate the life cycle cost of various product family that use any types of product structure. It provides detailed information related to the activity and resource costs of both parts and products that can assist the designer in analyzing the cost of the product family design. In addition, it can reduce the required amount of information and time to construct the cost estimation system

Evolutionary Algorithms in Engineering Design Optimization

Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following: they do not require any requisite to the objective/fitness evaluation function (continuity, derivability, convexity, etc.); they are not limited by the appearance of discrete and/or mixed variables or by the requirement of uncertainty quantification in the search. Moreover, they can deal with more than one objective function simultaneously through the use of evolutionary multi-objective optimization algorithms. This set of advantages, and the continuously increased computing capability of modern computers, has enhanced their application in research and industry. From the application point of view, in this Special Issue, all engineering fields are welcomed, such as aerospace and aeronautical, biomedical, civil, chemical and materials science, electronic and telecommunications, energy and electrical, manufacturing, logistics and transportation, mechanical, naval architecture, reliability, robotics, structural, etc. Within the EA field, the integration of innovative and improvement aspects in the algorithms for solving real world engineering design problems, in the abovementioned application fields, are welcomed and encouraged, such as the following: parallel EAs, surrogate modelling, hybridization with other optimization techniques, multi-objective and many-objective optimization, etc