Automatic Controller Research Articles

Ziegler and Nichols meet Kermack and McKendrick: Parsimony in dynamic models for epidemiology

The COVID-19 crisis popularized the importance of mathematical modeling for managing epidemics. A celebrated pertinent model was developed by Kermack and McKendrick about a century ago. A simplified version of that model has long been used and became widely popular recently, even though it has limitations that its originators had clearly articulated and warned against. A basic limitation is that it unrealistically assumes zero time to recovery for most infected individuals, thus underpredicting the peak of infectious individuals in an epidemic by a factor of as much as about 2. One could avoid this limitation by returning to the original comprehensive model, at the cost of higher complexity. To remedy that, we blend Ziegler-Nichols modeling ideas, developed for automatic controller tuning, with Kermack-McKendrick ideas to develop novel model structures that predict infectious peaks accurately yet retain simplicity. We illustrate these model structures with computer simulations on real epidemiological data.

Essential Oil Steam Distillation: Manufacturing 4.0

Smart sensors, self-configuration, operational flexibility, and automatic learning, among others, are technological attributes from industry 4.0 appliable to the essential oil extraction by the steam distillation process. These operations are recognized by their simplicity. Nevertheless, lack of automatic controls, process monitoring, and self-adjustment lead to uncontrolled extraction, poor yields, low quality of products. It occurs because of overexposure to high temperatures and overspending resources like energy and water. As far as capacity utilization is concerned, the optimized process is key to planning and managing the production activities.

Flight Testing Automatic Landing Control for Unmanned Aircraft Including Curved Approaches

Automatic landing of aircraft is a challenging guidance and control task that requires multiple feedback loops and a precise sequence of actions. Increasing operational flexibility and reducing the dependence on external infrastructure are key challenges for future unmanned aircraft. Usually, an aircraft performs the final approach on a straight line. This paper contributes a complete automatic landing controller capable of using three-dimensional curved approach paths all the way until touchdown. The controller consists of a nonlinear guidance law that steers the aircraft along a predefined spline path, various single-input–single-output control loops for rate and attitude control, and a robust multivariable flare controller. This flare controller ensures a three-point landing, i.e., simultaneous touchdown of all three wheels. Further, practical issues such as bumpless mode transfer and anti-windup compensation are considered. The controller is evaluated in multiple flight test experiments. Both the crabbed approach and the sideslip technique are demonstrated on several different approach paths, such as a steep curve and a helix. These paths are particularly challenging, because the flare maneuver is performed while the aircraft is in a turn. The controller is shown to reliably land the aircraft on an unpaved runway with high precision.

Automatic control of blood flow rate on the arterial-line side during cardiopulmonary bypass.

The operation of the cardiopulmonary bypass (CPB) system requires skilled techniques and experience. Intraoperatively, the perfusionist needs to intermittently manipulate both of the occluders on the venous- and arterial-line sides to achieve the desired blood flow rates. To facilitate the occluder operation, we propose an automatic control system for the arterial-line side blood flow rate based on a dynamic model that addresses the relationship between the occluder operation and blood flow rate in the CPB system. The simulation results demonstrated that the proposed system was able to control the blood flow rate even when the estimation error of the model parameters was presented. Then, we implemented this control system in the CPB system and conducted an experiment to automatically control the arterial-line side blood flow rate. We confirmed that the blood flow rate on the arterial-line side could follow the manually operated venous-line side blood flow rate.Clinical Relevance--- The automatic blood flow rate control system for a cardiopulmonary bypass system, proposed in this paper, contributes to reducing the burden of occluder operation on a perfusionist.

Automatic Control of Electronic Information Transmission Integrity Considering Gabp Neural Algorithm

With the rapid development of the economy and society, information has become an essential social resource and creates wealth continuously. However, open electronic information can be easily lost during transmission control. In this paper, the state of the information network is determined through a series of indexes based on the GABP neural algorithm. At the same time, the rate of information transmission is adjusted based on the state of the information network through self-adaptation, and the integrity of information transmission is controlled by the genetic particle swarm algorithm. Based on reasonable control of the integrity of information transmission, the research on the automatic control technology of open electronic information transmission integrity is accomplished under the condition that the bandwidth and response delay indexes are meeting. The study results indicate that the neural algorithm based on the GABP network can automatically control the electronic information transmission integrity and improve the reliability of information transmission effectively.

Artificial Intelligence of Things (AIoT) Enabled Floor Monitoring System for Smart Home Applications.

To enable smart homes and relative applications, the floor monitoring system with embedded triboelectric sensors has been proven as an effective paradigm to capture the ample sensory information from our daily activities, without the camera-associated privacy concerns. Yet the inherent limitations of triboelectric sensors such as high susceptibility to humidity and long-term stability remain a great challenge to develop a reliable floor monitoring system. Here we develop a robust and smart floor monitoring system through the synergistic integration of highly reliable triboelectric coding mats and deep-learning-assisted data analytics. Two quaternary coding electrodes are configured, and their outputs are normalized with respect to a reference electrode, leading to highly stable detection that is not affected by the ambient parameters and operation manners. Besides, due to the universal electrode pattern design, all the floor mats can be screen-printed with only one mask, rendering higher facileness and cost-effectiveness. Then a distinctive coding can be implemented to each floor mat through external wiring, which permits the parallel-array connection to minimize the output terminals and system complexity. Further integrating with deep-learning-assisted data analytics, a smart floor monitoring system is realized for various smart home monitoring and interactions, including position/trajectory tracking, identity recognition, and automatic controls. Hence, the developed low-cost, large-area, reliable, and smart floor monitoring system shows a promising advancement of floor sensing technology in smart home applications.

Assistive Sliding Mode Control of a Rehabilitation Robot with Automatic Weight Adjustment.

There are approximately 13 million new stroke cases worldwide each year. Research has shown that robotics can provide practical and efficient solutions for expediting post-stroke patient recovery. This simulation study aimed to design a sliding mode controller (SMC) for an end-effector-based rehabilitation robot. A genetic algorithm (GA) was designed for automatic controller weight adjustment. The optimal weights were obtained by minimizing a cost function comprising the end-effector position error, robot input, robot input-rate, and patient input. To promote safe tuner optimization, a model of the human arm was incorporated to generate the human joint torque. A computed-torque proportional derivative controller (CTPD) was designed for the human arm to approximate the central nervous system (CNS) motor control. This controller was adjusted to simulate rehabilitation effects and patient adaptation. The tuner was optimized for a trajectory tracking task with an assistive high-level control scheme. The simulation results showed lower cost compared to seven manual weight settings. The optimal weights provided good tracking performance and suitable robot inputs. This research provides a framework to conduct various simulations before testing our controller on human subjects. The preliminary results of this study will be used as the starting point for online adaptive controller tuning, which will be examined in our future research.

Design of Automatic Controller System for Three Axis 3D Printing Platform

With the development of society and the continuous improvement of the level of automation, automatic three-dimensional work platform is more and more popular, but now the three-dimensional work platform has a single function, and the waste of capacity is a serious problem. Therefore, this paper uses STM32F429 MCU to design a set of replaceable working position of the three axis control platform. The design of the table with replaceable work head, by identifying the ID on the head, change the control mode, enhance the functional diversity of the three-axis platform. In addition, in order to improve the universality of the system, the platform has many external communication interfaces, visual man-machine interface and LAN network communication functions.

Dynamic Electric Dispatch for Wind Power Plants: A New Automatic Controller System Using Evolutionary Algorithms

In this paper, we use an evolutionary swarm intelligence approach to build an automatic electric dispatch controller for an offshore wind power plant (WPP). The optimal power flow (OPF) problem for this WPP is solved by the Canonical Differential Evolutionary Particle Swarm Optimization algorithm (C-DEEPSO). In this paper, C-DEEPSO works as a control system for reactive sources in energy production. The control operation takes place in a daily energy dispatch, scheduled into 15 min intervals and resulting in 96 operating test scenarios. As the nature of the optimization problem is dynamic, a fine-tuning of the initialization parameters of the optimization algorithm is performed at each dispatch interval. Therefore, a version of the C-DEEPSO algorithm has been built to automatically learn the best set of initialization parameters for each scenario. For this, we have coupled C-DEEPSO with the irace tool (an extension of the iterated F-race (I/F-Race)) by using inferential statistic techniques. The experiments carried out showed that the methodology employed here is robust and able to tackle this OPF-like modeling. Moreover, the methodology works as an automatic control system for a dynamic schedule operation.

Applying Precision Agriculture to Artificial Waterfowl Hatching, Using the Black Muscovy Duck as an Example

(1) Background: agriculture practices adopt homogenization-farming processes to enhance product characteristics, with lower costs, standardization, mass production, and production efficiency. (2) Problem: conventional agriculture practices eliminate products when these products are slightly different from the expected status in each phase of the lifecycle due to the changing natural environment and climate. However, this elimination of products can be avoided when they receive customized care to the expected developing path via a universal prediction model, for the quantitative description of biomass changing with time and the environment, and the corresponding automatic environmental controls. (3) Methods: in this study, we built a prediction model to quantitatively predict the hatching rate of each egg by observing the biomass development path along the waterfowl-like production lifecycle and the corresponding environment settings. (4) Results: two experiments using black Muscovy duck hatching as a case study were executed. The first experiment involved finding out the key characteristics, out of 25 characteristics, and building a prediction model to quantitatively predict the survivability of the black Muscovy duck egg. The second experiment was adopted to validate the effectiveness of our prediction mode; the hatching rate rose from 47% in the first experiment to 62% in the second experiment without any human interference from experienced farmers. (5) Contributions: this research builds on an AI-based precision agriculture system prototype as the reference for waterfowl research. The results show that our proposed model is capable of decreasing the training costs and enhancing the product qualification rate for individual agricultural products.

Machine Learning and Survey-based Predictors of InfoSec Non-Compliance

Survey items developed in behavioral Information Security (InfoSec) research should be practically useful in identifying individuals who are likely to create risk by failing to comply with InfoSec guidance. The literature shows that attitudes, beliefs, and perceptions drive compliance behavior and has influenced the creation of a multitude of training programs focused on improving ones’ InfoSec behaviors. While automated controls and directly observable technical indicators are generally preferred by InfoSec practitioners, difficult-to-monitor user actions can still compromise the effectiveness of automatic controls. For example, despite prohibition, doubtful or skeptical employees often increase organizational risk by using the same password to authenticate corporate and external services. Analysis of network traffic or device configurations is unlikely to provide evidence of these vulnerabilities but responses to well-designed surveys might. Guided by the relatively new IPAM model, this study administered 96 survey items from the Behavioral InfoSec literature, across three separate points in time, to 217 respondents. Using systematic feature selection techniques, manageable subsets of 29, 20, and 15 items were identified and tested as predictors of non-compliance with security policy. The feature selection process validates IPAM's innovation in using nuanced self-efficacy and planning items across multiple time frames. Prediction models were trained using several ML algorithms. Practically useful levels of prediction accuracy were achieved with, for example, ensemble tree models identifying 69% of the riskiest individuals within the top 25% of the sample. The findings indicate the usefulness of psychometric items from the behavioral InfoSec in guiding training programs and other cybersecurity control activities and demonstrate that they are promising as additional inputs to AI models that monitor networks for security events.

Development of an Embedded Longitudinal Flight Control Based on X-Plane Flight Simulator

Avionics is a category of electronic systems, equipment and instruments specifically designed for use in aviation. Usually called autopilot, the Automatic Flight Control System, is one of the main systems in avionics. Autopilot systems are designed to automatically control the aircraft piloting, reducing the pilot fatigue caused by the flight. Before being embedded into an aircraft, an autopilot system must be exhaustively evaluated by computational simulations to be validated. The objective of this work is to describe the development of an embedded automatic flight controller aimed to be applied to a Cessna-172SP-Skyhawkmodel aircraft in order to control its altitude. The developed flight controller is based on a tuned PID control and it is embedded in a Raspberry Pi that actually controls the altitude of the aircraft simulated in the X-Plane 11 flight simulator, running on a Desktop PC connected by UDP to the Raspberry Pi. The simulation results validated the proposed flight controller as well as the proposed hardware scheme for validation.

Automatic Railway Gate Controller

Automatic Railway Gate Controller

Towards Safe Human-Quadrotor Interaction: Mixed-Initiative Control via Real-Time NMPC

This article presents a novel algorithm for blending human inputs and automatic controller commands, guaranteeing safety in mixed-initiative interactions between humans and quadrotors. The algorithm is based on nonlinear model predictive control (NMPC) and involves using the state solution to assess whether safety- and/or task-related rules are met to mix control authority. The mixing is attained through the convex combination of human and actual robot costs and is driven by a continuous function that measures the rules' violation. To achieve real-time feasibility, we rely on an efficient real-time iteration (RTI) variant of a sequential quadratic programming (SQP) scheme to cast the mixed-initiative controller. We demonstrate the effectiveness of our algorithm through numerical simulations, where a second autonomous algorithm is used to emulate the behavior of pilots with different skill levels. Simulations show that our scheme provides suitable assistance to pilots, especially novices, in a workspace with obstacles while bolstering computational efficiency.

Automatic (Headlight) Beam Controlling module for two-wheelers

Abstract: Automatic High Beam controller is a device made due to the rising number of accidents at night because of LED headlamps temporarily affecting the vision of the driver on the opposite lane. According to AAA, LED lights do a much better job of illuminating the roadway, particularly in the low-beam application versus a halogen reflector at 150 feet more during testing. But, still, that brings the max vehicle speed to about 52 miles an hour, which is still falling short of highway speeds. So, the users are suggested to drive with high beam on if there is no oncoming traffic within a reasonable distance and the roadway is improperly lit. But in practice most people drive with the high beam settings in places with or without traffic great from the user's standpoint. However, even on low beam, they have such a high intensity that on 2-lane roads, especially when the oncoming driver of a car or small pickup approaches the LED equipped truck at night, in rain, fog, or snow the oncoming driver is blinded at a level equal to or greater than if the LED equipped vehicle were using conventional halogen high beams. This device is made without distance or ambient lighting being deciding factors and entirely based on user’s discretion. The transmitter model is fitted with a button that sends a signal to the receiver model using nrf24L01 modules and AT Mega 8 microcontroller (programmed using Arduino UNO). The pressing of button causes the state of the button to be set to HIGH. This signals the receiving circuit to set the LED pin to LOW. Therefore, the High Beam is set to Low Beam for 5 seconds when the impulse is received. Due to the use of H4 C6 headlamps which are rated for 36W with a minimum power requirement of 12W an adapter was connected to convert 220V AC supply to 12V, 3A DC supply for the LED and the rest of the circuit.

Design of Automatic Intensity Controller of Street Light and it’s Energy Efficiency

Design of Automatic Intensity Controller of Street Light and it’s Energy Efficiency

Neural-Fuzzy-Based Adaptive Sliding Mode Automatic Steering Control of Vision-based Unmanned Electric Vehicles

This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters. Primarily, the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed, and in which the relationship between the look-ahead time and vehicle velocity is revealed. Then, in order to overcome the external disturbances, parametric uncertainties and time-varying features of vehicles, a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles, which includes an equivalent control law and an adaptive variable structure control law. In this novel automatic steering control system of vehicles, a neural network system is utilized for approximating the switching control gain of variable structure control law, and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time. The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory. Finally, the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.

Automatic Water Tank Filling System with Water Level Indicator

In this project, we have worked with an indicator on an automatic water level controller. When we looked up our topic on the internet, we realized that most of the projects used microcontrollers or IC 555, but we didn’t include any of these circuits in our model. Our design is based on the LM324N IC, which functions as a rectifier, oscillator, and comparator. On this foundation, we construct our circuit, and our model is successfully executed at a minimal cost. The project’s goal is to conserve water. Water is a necessary component of our daily life. Water plays a vital role in our everyday life since there is not any water we can’t imagine in our lives. Water is essential for digestion and plays some important roles in the body, such as waste removal, body temperature control, and nutrient transport. Our daily lives began in the upper tank that is the most crucial part of all the houses. Water in your house, including drinking, cooking, bathing, cleaning, and washing, is used almost for all purposes. Appliances such as washing machines and scrubbers require continuous flow. In-house, overhead tanks comply with those requirements. As a result, saving water for humans is important. This problem can be solved by using an automatic water level controller and indicator. The water level controller’s operation is based on the fact that water conducts electricity due to the minerals in it. So As a result, the circuit can be opened or closed using water. The various circuits in the control unit send out different signals as the water level rises or falls. These signals are used to turn ON or OFF the motor pump depending on our requirements. I’m going to install an automatic water level controller so we don’t have to manually turn the motor ON and OFF. The unit tracks the water level and then activates the relay, which activates the Motor. The LM324N IC, carbon level sensor, and relay are the key components in this unit. With this project, we will be able to automatically monitor water wastage and maintain water levels in various systems, such as water tanks, boilers, swimming pools, and so on. Water and energy losses are reduced as a result of this. This also saves manpower because it is no longer necessary to run it manually.

Automatic Water Tank Filling System with Water Level Indicator

In this project, we have worked with an indicator on an automatic water level controller. When we looked up our topic on the internet, we realized that most of the projects used microcontrollers or IC 555, but we didn't include any of these circuits in our model. Our design is based on the LM324N IC, which functions as a rectifier, oscillator, and comparator. On this foundation, we construct our circuit, and our model is successfully executed at a minimal cost. The project's goal is to conserve water. Water is a necessary component of our daily life. Water plays a vital role in our everyday life since there is not any water we can't imagine in our lives. Water is essential for digestion and plays some important roles in the body, such as waste removal, body temperature control, and nutrient transport. Our daily lives began in the upper tank that is the most crucial part of all the houses. Water in your house, including drinking, cooking, bathing, cleaning, and washing, is used almost for all purposes. Appliances such as washing machines and scrubbers require continuous flow. Inhouse, overhead tanks comply with those requirements. As a result, saving water for humans is important. This problem can be solved by using an automatic water level controller and indicator. The water level controller's operation is based on the fact that water conducts electricity due to the minerals in it. So As a result, the circuit can be opened or closed using water. The various circuits in the control unit send out different signals as the water level rises or falls. These signals are used to turn ON or OFF the motor pump depending on our requirements. I'm going to install an automatic water level controller so we don't have to manually turn the motor ON and OFF. The unit tracks the water level and then activates the relay, which activates the Motor. The LM324N IC, carbon level sensor, and relay are the key components in this unit. With this project, we will be able to automatically monitor water wastage and maintain water levels in various systems, such as water tanks, boilers, swimming pools, and so on. Water and energy losses are reduced as a result of this. This also saves manpower because it is no longer necessary to run it manually.

An automatic frequency stabilized laser with hertz-level linewidth

The ultra-stable laser system has been widely used in a variety of fields. Recently, automatic laser frequency stabilization is crucial to some unmanned applications. This paper reports the development of the automatic laser frequency stabilization for the ultra-stable laser system with hertz-level linewidth. The hybrid automatic frequency stabilization circuits are combined with analog high-speed PID circuits and digital automatic controller. An external cavity diode laser is demonstrated to be frequency locked to a reference cavity with a control bandwidth over 2.1 MHz which can be improved. Beating with a second ultra-stable lasers, a median linewidth of 3.86 Hz is obtained via 203 repeated measurements. To characterize the reliability of automatic frequency stabilization, the laser is intendedly interrupted by 4432 times, while the laser frequency is relocked automatically. The mean time for the laser relocking is 4.86 s, and 90 % of the experiments can be relocked within 6 s. Moreover, one week of laser frequency stabilization with automatic relocking is demonstrated. The design of the auto-locking laser system can be applied for field and space applications.