Control Engineering Principles Research Articles

Digital twins for land-based aquaculture: A case study for rainbow trout (Oncorhynchus mykiss)

The virtual, digital counterpart of a physical object, referred as digital twin, derives from the Internet of Things (IoT), and involves real-time acquisition and processing of large data sets. A fully implemented system ultimately enables real-time and remote management, as well as the reproduction of real and forecasted scenarios. Under the emerging framework of Precision Fish Farming, which brings control-engineering principles to fish production, we set up digital twin prototypes for land-based finfish farms. The digital twin is aimed at supporting producers in optimizing feeding practices, oxygen supply and fish population management with respect to 1) fish growth performances; 2) fish welfare, and 3) environmental loads. It relies on integrated mathematical models which are fed with data from in-situ sensors and from external sources, and simulate several dynamic processes, allowing the estimation of key parameters describing the ambient environment and the fishes. A conceptual application targeted at rearing cycles of rainbow trout (Oncorhynchus mykiss) in an operational in-land aquafarm in Italy is presented. The digital twin takes into account the disparate levels of automation and control that are found within this farm, and considerations are made on preferential directions for future developments. In spite of its potential, and not only in the aquaculture sector, the development of digital twins is still at its early stage. Furthermore, Precision Fish Farming applications in land-based systems as well as targeted at rainbow trout are novel developments.

Energy and time optimization during exit from torpor in vertebrate endotherms.

Torpor is used in small sized birds and mammals as an energy conservation trait. Considerable effort has been put towards elucidating the mechanisms underlying its entry and maintenance, but little attention has been paid regarding the exit. Firstly, we demonstrate that the arousal phase has a stereotyped dynamic: there is a sharp increase in metabolic rate followed by an increase in body temperature and, then, a damped oscillation in body temperature and metabolism. Moreover, the metabolic peak is around two-fold greater than the corresponding euthermic resting metabolic rate. We then hypothesized that either time or energy could be crucial variables to this event and constructed a model from a collection of first principles of physiology, control engineering and thermodynamics. From the model, we show that the stereotyped pattern of the arousal is a solution to save both time and energy. We extended the analysis to the scaling of the use of torpor by endotherms and show that variables related to the control system of body temperature emerge as relevant to the arousal dynamics. In this sense, the stereotyped dynamics of the arousal phase necessitates a certain profile of these variables which is not maintained as body size increases.

Digital twins for land-based aquaculture: A case study for rainbow trout ( Oncorhynchus mykiss).

The virtual, digital counterpart of a physical object, referred as digital twin, derives from the Internet of Things (IoT), and involves real-time acquisition and processing of large data sets. A fully implemented system ultimately enables real-time and remote management, as well as the reproduction of real and forecasted scenarios. Under the emerging framework of Precision Fish Farming, which brings control-engineering principles to fish production, we set up digital twin prototypes for land-based finfish farms. The digital twin is aimed at supporting producers in optimizing feeding practices, oxygen supply and fish population management with respect to 1) fish growth performances; 2) fish welfare, and 3) environmental loads. It relies on integrated mathematical models which are fed with data from in-situ sensors and from external sources, and simulate several dynamic processes, allowing the estimation of key parameters describing the ambient environment and the fishes. A conceptual application targeted at rearing cycles of rainbow trout ( Oncorhynchus mykiss) in an operational in-land aquafarm in Italy is presented. The digital twin takes into account the disparate levels of automation and control that are found within this farm, and considerations are made on preferential directions for future developments. In spite of its potential, and not only in the aquaculture sector, the development of digital twins is still at its early stage. Furthermore, Precision Fish Farming applications in land-based systems as well as targeted at rainbow trout are novel developments.

Multi node sensors for water quality monitoring towards precision aquaculture

Shrimp culture is carried out by ponds in open areas, especially near coastal areas. The ponds water condition or water quality has a significant impact on the shrimp culture. There are also frequent problems among these shrimp ponds, such as crop failure caused by bad water quality. The water quality monitoring in shrimp ponds is often done manually by the farmer in periodical times. The water quality monitoring that is done manually tends to be impractical, requires high worker wages, and has a high human error rate. With the advances in the field of Information Technology, data may be retrieved through sensors and collected into a server. Then the data may be processed and visualized in order to support precision aquaculture using the Internet of Things (IoT). Precision Fish Farming (PFF) or precision aquaculture is a concept that applies control-engineering principles to aquaculture industries. The PPF concepts allow farmers to have the ability to monitor, control, and document biological processes in aquaculture farms. This research aims were to design and build a multi node sensor and master board to monitor water quality in real time using the prototyping method. The system consists of several sensors for monitoring temperature, pH, and salinity in shrimp ponds that are installed at each node. Nodes are actively sending data to the master board. This model is done to reduce the need for direct data access to the internet. The monitoring system is tested in PB Tunas Baru shrimps pond in order to check if the system may work properly. The sensor is set to retrieve pond water quality data every 5 minutes in a total 100 minute period. The result shows that the model works properly, and the means value of the total error rate for the salinity sensors, pH, and temperature sensors consecutively is 1.65%, 1.25%, and 0%. This information allows the farmers to maintain the water quality precisely in aim to produce high quality shrimp crops toward the precision aquaculture concepts.

Irigacioni sistem kontrolisan Arduino uno mikrokontrolerom

In crop production, a healthy water balance is essential for high quality yields. Under-watered crops suffer from nutrient deficiencies while over-watered plants are more susceptible to diseases pressure and can in some cases lead to root death through suffocation. Also over-watered plants are not able to withstand dry spells during dry season. The aim of this paper is to use control engineering principles and concepts to provide a microcontroller based irrigation system. The system helps in saving money and water and at the same time increasing crops production. The automated irrigation system is controlled using ATmega328 microcontroller based on Arduino platform. The system is programmed via the microcontroller to give interrupt signal to the irrigation system (drip, sprinkler, ditch etc.) depending on the soil moisture levels. The soil moisture/humidity levels are checked using soil moisture sensor. Whenever there is a change in moisture/humidity in the soil, this sensor senses the change and gives an interrupt signal to the micro-controller and thus the watering system is activated or deactivated.

Precision aquaculture: a short review on engineering innovations

Aquaculture is presented as a sustainable alternative to the consumption of wild fish, for example, reducing inputs (such as feed), optimizing outputs, and reducing pollution. Extending to the agricultural framework, in this context, different technologies are being used to diminish those environmental hazards, giving rise to the precision agriculture/aquaculture being this a management concept based on observing, measuring, and responding space/temporal variability of productions. The scope of the precision aquaculture is to apply control-engineering principles to the production, to direct farmers to a better monitoring, control, and documentation of biological processes in fish farms. The aim of this review is to show an overview (enriched by a terms mapping analysis) of the precision aquaculture engineering innovations, with some examples of commercial systems, even if most of them are not specifically addressed in the precision aquaculture framework, in terms of: computer vision for animal monitoring, environmental monitoring tools, and sensor network (i.e., wireless sensor network, and long-range), robotics, and finally data interpretation and decision tools (i.e., algorithms, Internet of Things, and Decision Support Systems). Over the Internet of Things, cyber-physical systems communicate and cooperate with each other and with humans in real-time both internally and across organizational services offered and used by participants of the value chain. To increase the production and ameliorate the fish product quality and animal welfare issues, it is becoming even more important to monitor and control the production process.

Development of a Control-Oriented Model of Social Cognitive Theory for Optimized mHealth Behavioral Interventions.

Mobile health (mHealth) technologies are contributing to the increasing relevance of control engineering principles in understanding and improving health behaviors, such as physical activity. Social Cognitive Theory (SCT), one of the most influential theories of health behavior, has been used as the conceptual basis for behavioral interventions for smoking cessation, weight management, and other health-related outcomes. This paper presents a control-oriented dynamical systems model of SCT based on fluid analogies that can be used in system identification and control design problems relevant to the design and analysis of intensively adaptive interventions. Following model development, a series of simulation scenarios illustrating the basic workings of the model are presented. The model's usefulness is demonstrated in the solution of two important practical problems: 1) semiphysical model estimation from data gathered in a physical activity intervention (the MILES study) and 2) as a means for discerning the range of "ambitious but doable" daily step goals in a closed-loop behavioral intervention aimed at sedentary adults. The model is the basis for ongoing experimental validation efforts, and should encourage additional research in applying control engineering technologies to the social and behavioral sciences.

Providing Water to the Plants Automatically Using Microcontroller

In current situation, the field of agriculture farmers is facing major problems in watering their crops. It’s because they are not aware of about the availability of the power. Even if it is available, they need to pump water and wait until the field is properly watered, which compels them to stop doing other activities which are also important for them, and thus they loss their precious time and efforts. But, there is a solution “An Automatic Plant watering System “not only helps farmers but also others for watering their gardens as well. The aim of the project is to use control engineering principles and concepts to provide a microcontroller based automatic plant watering system. The system will help in saving money and water and at the same time increasing crops production. The automatic plant watering system is controlled using ATmega328 micro controller based on arduino platform. The soil moisture/humidity levels are checked using soil moisture sensor. Whenever there is a change moisture/humidity in the soil the sensor senses change and gives signal to the micro-controller to activate or deactivate watering system.

A New Look at Disease: Parkinson's as Seen Through the Eyes of an Engineer [Book review

This book presents a look at the intersection between control principles in engineering and life sciecnes. It lies at this intersection but is quite different, both in content and style, from these other books. The rather short book is written in a way that is easily accessible to a reader from any background. The style is direct, with some parts of the book very personal, for example, when the author relates his own experiences both in control engineering and with Parkinson´s. As with other neurodegenerative diseases, the number of patients is expected to grow significantly. While Parkinson´s is an area of intensive research, the disease is poorly understand, especially its early preclinical phase. The main reasons for this lack of understanding are that there are a multitude of possible causes-such as head injury, pesticide exposure, and genetic predisposition´ and the disease spreads very slowly, usually over one or more decades. The book consists of four parts. The first part provides a historical perspective underpinning the point that scientific research did not always evolve smoothly, but from time to time new approaches were taken. This perspective is not only discussed but is also nicely illustrated by photographs and reprints from old books. The first part ends by predicting that the time for a change in pharmaceutical research is close. The second part gives an introduction to control engineering principles such as feedback, modeling, and stability. The third part introduces Parkinson´s disease in a very understandable manner, even for nonspecialists. The book discusses the main hypotheses of possible causes of the disease and its propagation as well as the complexity caused by the high variability of disease cases. At this point, the reader may wonder if there is any hope to understanding Parkinson´s.

A process control approach to tactical inventory management in production-inventory systems

Supply chain management (SCM) is concerned with the efficient movement of goods through a network of suppliers and retailers. As delayed and uncertain dynamical systems, supply chains provide an excellent opportunity for demonstrating the benefits of control engineering principles to what is traditionally perceived as a “business” problem. This paper presents a fundamental yet practical approach for applying control-theoretic principles to tactical inventory management problem in a production-inventory system, the basic unit in a supply chain. Beginning with the use of a fluid analogy, we present internal model control (IMC) and model predictive control (MPC) as means for generating a series of increasingly sophisticated decision policies for inventory management. A combined feedback-feedforward multi-degree-of-freedom IMC policy is shown to properly adjust factory starts in the presence of inventory target changes, forecasted shifts in customer demand, and stochastic changes in demand. The MPC policy displays equivalent performance, but incorporates the added functionality of managing inventory in the presence of constraints, an important practical consideration. The MPC policy shows improved performance, greater flexibility, and higher functionality relative to an advanced order-up-to policy based on control engineering principles found in the literature.

Using of particle swarm for control of helicopter

The CE150 Helicopter is one of the ranges offered by HUMUSOFT for teaching systems dynamics and control engineering principles. It has two degrees of freedom and is a MIMO system. We consider only Azimuth system for identification and control. There are many approaches to system identification. We choose NN structure and train it by Back-propagation and then use GA and PSO for optimizing the NN's training. At last we design PSO controller of Azimuth system.

Noise control solutions for indoor firing ranges

Peak sound pressure level measurements conducted at indoor firing ranges ranged from 157�168 decibels (dB). Exposure to high-intensity impulsive noise during target shooting at indoor firing ranges has been identified as a significant contributor to noise-induced hearing loss among shooters. In addition, firing ranges that are constructed with adjacent areas or housed within a larger building structure require minimal sound transmission to occur outside the firing range. Several principles of noise control engineering can be applied to improve the absorption of impulse noise inside the firing ranges and limit the transmission of such impulses to adjacent areas and spaces. Although little can be done to control the direct exposure of shooters to the firing of their own firearms, several noise control solutions are presented to reduce the secondary exposure off reflected surfaces and from other shooters. This paper will provide a general overview of noise control solutions aimed to improve sound absorption inside the firing range and reduce the transmission of airborne and structural-borne sounds to adjacent areas and facilities.

Models for International Stability

Abstract Conflict resolution was dominated by more or less verbal approaches some years ago. Nowadays system engineering methods, based on well known principles of control engineering, mathematics, statistics are applied to such problems. One of the main problems arising is the description of the static and dynamic behaviour of conflict partners or systems in form of mathematical methods. Such models are determined either in a theoretical or experimental way. Theoretical model building yields to complicated models difficult to handle. Therefore simple models are mostly used determined in a heuristic way. In the paper methods for model building are presented and as an example a simple linear time invariant model is used to describe gas or oil supply and consumption of several countries.

Using engineering control principles to inform the design of adaptive interventions: A conceptual introduction

The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice.

Computational Models to Synthesize Human Walking

The synthesis of human walking is of great interest in biomechanics and biomimetic engineering due to its predictive capabilities and potential applications in clinical biomechanics, rehabilitation engineering and biomimetic robotics. In this paper, the various methods that have been used to synthesize human walking are reviewed from an engineering viewpoint. This involves a wide spectrum of approaches, from simple passive walking theories to large-scale computational models integrating the nervous, muscular and skeletal systems. These methods are roughly categorized under four headings: models inspired by the concept of a CPG (Central Pattern Generator), methods based on the principles of control engineering, predictive gait simulation using optimisation, and models inspired by passive walking theory. The shortcomings and advantages of these methods are examined, and future directions are discussed in the context of providing insights into the neural control objectives driving gait and improving the stability of the predicted gaits. Future advancements are likely to be motivated by improved understanding of neural control strategies and the subtle complexities of the musculoskeletal system during human locomotion. It is only a matter of time before predictive gait models become a practical and valuable tool in clinical diagnosis, rehabilitation engineering and robotics.

Industrial noise control engineering principles and standard practices applicable to engineers and industrial hygienists

Industrial organizations have accepted the notion that noise control is no longer 100% of one person’s responsibility, but a collaborative effort among engineers and industrial hygiene professionals. Proven noise control measures exist and are commercially available for many industrial noise sources. There are also noise control concepts and techniques that can be adopted by maintenance and other personnel as standard practices. Awareness of the elements of noise control engineering can offer benefit in areas such as equipment procurement, workplace risk assessment, and manufacturing program planning. The focus of this presentation is to discuss the elements of noise control engineering that manufacturing engineers and industrial hygiene professionals would need to apply out of their university education into practice, and the benefits that would be derived from this information.

Automated product grade transitions, exposing the inherent and latent dangers of neural networks in manufacturing process control: an industrial case study

The proliferation of neural network based solutions in manufacturing process control is causing concern for many engineers in the industry [American Automatic Control Conference (paper FP18-2), Denver, 2003; AIChE Spring Meeting (paper 144f), New Orleans, 2003]. The intrinsic and latent dangers of neural nets (within a control framework) are often overlooked when assessing a suitable technology for real-time control application. This case study examines the intrinsic properties of a neural net that make it wholly unsuitable as a technology directly or indirectly involved in the manipulation of process valves. Of particular concern is the optimization of product grade transitions. Apart from start up and shutdown, product grade transitions are the most safety critical procedures performed on a manufacturing plant. Any control system involved in the automation of such procedures should be of the highest integrity and adhere to sound, intrinsically safe control engineering principles—something neural networks categorically fail to provide. The objectives of this case study are twofold. Firstly, the aim is to raise awareness in the manufacturing industry of the inherent and latent dangers of neural networks in control. The second objective is to provide a platform for best practice guidance on what is and is not acceptable as a modeling paradigm in a manufacturing process control scheme.

Simulation of transient friction of a cylinder between two planes

The need for good friction models for transient motions has increased as a consequence of the increased use of mechatronics and control engineering principles in precision mechanics. The machine elements in such equipment often involve rolling and sliding contacts. Most studies of friction in rolling and sliding contacts running under dry or boundary lubricated conditions have examined steady-state conditions. This paper describes simulations of the motion of a cylinder between two planes, first with a step change in velocity and then with an oscillating motion of the upper plane. The motion of the cylinder is determined by the friction in the contacts and the inertia. The friction in the rolling and sliding contacts is simulated with a brush model. The surfaces are assumed to be ideally smooth. For the step change in velocity, there is initially a period of complete sliding in the upper contact. During the sliding period, the friction force is the maximum possible, but it decreases as the complete sliding ends. The simulations show heavily damped oscillations, with frequencies corresponding to the natural translatory and torsional frequencies of the system. For the oscillating motions the sliding increases with the frequency of the motion, as expected.

How to Teach Topics of Modern Control Systems to Computer Science Students?

Teaching principles of process control engineering to computer science students is an enjoyable but also exhaustive task. In order to run a lecture with an associated practical dedicated to modern control systems for approximately 200 students with acceptable effort, it must be organized carefully and strictly. This article surveys our experiences and efforts regarding the setup of a new practical. We present its contents and give a first outlook on our new equipment based upon fieldbus systems. Finally, we describe some principal issues in question when organizing our next generation computer science practical.

Benchmarking for strategic maintenance quality improvement

Points out that the concepts of total productive maintenance (TPM) were formulated by combining the principles of total quality control (TQC) and maintenance engineering. Claims that the theory of TPM is not yet exhaustive. Proposes a model called “strategic maintenance quality engineering” (SMQE) to make the theory of TPM exhaustive. Deals with the last phase of SMQE which envisages the evaluation of each cycle of SMQE performance. Applies benchmarking with suitable modifications to carry out the last phase of SMQE. Presents the salient features of pilot implementation study conducted in two companies. Suggests that the use of information technology (IT) for benchmarking SMQE would aid in improving strategic maintenance quality more effectively.